This file documents the YAP Prolog System version 6.3.4, a high-performance Prolog compiler developed at LIACC, Universidade do Porto. YAP is based on David H. D. Warren's WAM (Warren Abstract Machine), with several optimizations for better performance. YAP follows the Edinburgh tradition, and is largely compatible with DEC-10 Prolog, Quintus Prolog, and especially with C-Prolog. + @subpage Download where to download YAP for your platform. + @subpage Install discusses how to compile and install YAP. + @subpage Syntax describes the syntax of YAP. + @subpage Run describes how to invoke YAP + @subpage Loading_Programs presents the main predicates and directives available to load files and to control the Prolog environment. + @subpage abs_file_name explains how to find a file full path. + @subpage BuilthYins describes predicates providing core YAP functionality. Examples include + @subpage Arithmetic describes the arithmetic predicates + @subpage Control describes the predicates for controlling the execution of Prolog programs. + @subpage Testing_Terms describes the main predicates on terms + @subpage Input_Output goes into Input/Ouput. + @subpage Database discusses the clausal data-base + @subpage Sets Collecting Solutions to a Goal + @subpage Grammars presents Grammar rules in Prolog that are both a convenient way to express definite clause grammars and an extension of the well known context-free grammars. + @subpage OS discusses access to Operating System functionality + @subpage Term_Modification Global and Mutable Terms + @subpage Profiling Profiling Prolog Programs + Libraries + @subpage maplist introduces macros to apply an operation over all elements of a list + @subpage Apply Apply Macros + @subpage Association_Lists Association Lists + @subpage AVL_Trees AVL Trees + @subpage Exo_Intervals Exo Intervals + @subpage Gecode Gecode Interface + @subpage Heaps Heaps + @subpage Lists List Manipulation + @subpage LineUtilities Line Manipulation Utilities + @subpage matrix Matrix Library + @subpage NonhYBacktrackable_Data_Structures Non-Backtrackable Data Structures + @subpage Ordered_Sets Ordered Sets + @subpage Pseudo_Random Pseudo Random Number Integer Generator + @subpage Queues Queues + @subpage Random Random Number Generator + @subpage Read_Utilities Read Utilities + @subpage RedhYBlack_Trees Red-Black Trees + @subpage RegExp Regular Expressions + @subpage shlib SWI-Prolog's shlib library + @subpage Splay_Trees Splay Trees + @subpage String_InputOutput Reading From and Writing To Strings + @subpage System Calling The Operating System from YAP + @subpage Terms Utilities On Terms + @subpage Tries Trie DataStructure + @subpage Cleanup Call Cleanup + @subpage Timeout Calls With Timeout + @subpage Trees Updatable Binary Trees + @subpage UGraphs Unweighted Graphs + @subpage DGraphs Directed Graphs + @subpage UnDGraphs Undirected Graphs + @subpage DBUsage Memory Usage in Prolog Data-Base + @subpage Lambda Lambda Expressions + @subpage LAM LAM + @subpage BDDs Binary Decision Diagrams and Friends + @subpage Block_Diagram Block Diagram + @subpage Invoking_Predicates_on_all_Members_of_a_List Invoking Predicates on all Members of a List + @subpage Forall Forall \author Vitor Santos Costa, \author Luís Damas, \author Rogério Reis \author Rúben Azevedo © 1989-2014 L. Damas, V. Santos Costa and Universidade do Porto. Permission is granted to make and distribute verbatim copies of this manual provided the copyright notice and this permission notice are preserved on all copies. Permission is granted to copy and distribute modified versions of this manual under the conditions for verbatim copying, provided that the entire resulting derived work is distributed under the terms of a permission notice identical to this one. Permission is granted to copy and distribute translations of this manual into another language, under the above conditions for modified versions. \htmlonly This file contains extracts of the SWI-Prolog manual, as written by Jan Wielemaker. Our thanks to the author for his kind permission in allowing us to include his text in this document. \endhtmlonly @section Intro Introduction This document provides User information on version 6.3.4 of YAP (Yet Another Prolog). The YAP Prolog System is a high-performance Prolog compiler developed at LIACC, Universidade do Porto. YAP provides several important features: YAP is based on the David H. D. Warren's WAM (Warren Abstract Machine), with several optimizations for better performance. YAP follows the Edinburgh tradition, and was originally designed to be largely compatible with DEC-10 Prolog, Quintus Prolog, and especially with C-Prolog. YAP implements most of the ISO-Prolog standard. We are striving at full compatibility, and the manual describes what is still missing. The manual also includes a (largely incomplete) comparison with SICStus Prolog. The document is intended neither as an introduction to Prolog nor to the implementation aspects of the compiler. A good introduction to programming in Prolog is the book @cite TheArtOfProlog , by L. Sterling and E. Shapiro, published by "The MIT Press, Cambridge MA". Other references should include the classical @cite ProgrammingInProlog , by W.F. Clocksin and C.S. Mellish, published by Springer-Verlag. YAP 4.3 is known to build with many versions of gcc (\<= gcc-2.7.2, \>= gcc-2.8.1, \>= egcs-1.0.1, gcc-2.95.\*) and on a variety of Unixen: SunOS 4.1, Solaris 2.\*, Irix 5.2, HP-UX 10, Dec Alpha Unix, Linux 1.2 and Linux 2.\* (RedHat 4.0 thru 5.2, Debian 2.\*) in both the x86 and alpha platforms. It has been built on Windows NT 4.0 using Cygwin from Cygnus Solutions (see README.nt) and using Visual C++ 6.0. The overall copyright and permission notice for YAP4.3 can be found in the Artistic file in this directory. YAP follows the Perl Artistic license, and it is thus non-copylefted freeware. If you have a question about this software, desire to add code, found a bug, want to request a feature, or wonder how to get further assistance, please send e-mail to . To subscribe to the mailing list, visit the page . On-line documentation is available for YAP at: Recent versions of YAP, including both source and selected binaries, can be found from this same URL. This manual was written by Vítor Santos Costa, Luís Damas, Rogério Reis, and Rúben Azevedo. The manual is largely based on the DECsystem-10 Prolog User's Manual by D.L. Bowen, L. Byrd, F. C. N. Pereira, L. M. Pereira, and D. H. D. Warren. We have used comments from the Edinburgh Prolog library written by R. O'Keefe. Documentation from many built-ins is originally from the SWI-Prolog manual, with the gracious uathorization from Jan Wielemaker. We would also like to gratefully acknowledge the contributions from Ashwin Srinivasian. We are happy to include in YAP several excellent packages developed under separate licenses. Our thanks to the authors for their kind authorization to include these packages. The packages are, in alphabetical order:
  • The CHR package developed by Tom Schrijvers, Christian Holzbaur, and Jan Wielemaker.
  • The CLP(BN) package and Horus toolkit developed by Tiago Gomes, and Vítor Santos Costa.
  • The CLP(R) package developed by Leslie De Koninck, Bart Demoen, Tom Schrijvers, and Jan Wielemaker, based on the CLP(Q,R) implementation by Christian Holzbaur.
  • The CPLint package developed by Fabrizio Riguzzi's research laboratory at the University of Ferrara. Please see
  • The CUDA interface package developed by Carlos Martínez, Jorge Buenabad, Inês Dutra and Vítor Santos Costa.
  • The GECODE interface package developed by Denys Duchier and Vítor Santos Costa.
  • The JPL (Java-Prolog Library) package developed by .
  • The Logtalk Object-Oriented system is developed at the University of Beira Interior, Portugal, by Paulo Moura: Logtalk is no longer distributed with YAP. Please use the Logtalk standalone installer for a smooth integration with YAP.
  • The minisat SAT solver interface developed by Michael Codish, Vitaly Lagoon, and Peter J. Stuckey.
  • The MYDDAS relational data-base interface developed at the Universidade do Porto by Tiago Soares, Michel Ferreira, and Ricardo Rocha.
  • The PRISM logic-based programming system for statistical modeling developed at the Sato Research Laboratory, TITECH, Japan.
  • The ProbLog 1 system developed by the ProbLog team in the DTAI group of KULeuven. For general information on ProbLog 1 and 2, please see
  • The real R interface package developed by Nicos Angelopoulos, Vítor Santos Costa, João Azevedo, Jan Wielemaker, and Rui Camacho.
  • YAP includes the yap2swi library that ports to YAP code from of SWI's PL interface. This includes the Input/Output Layer, the SWI Foreign Language Interface, and the RDF, archive, clib, http, odbc, plunit, semweb, sgml, and zlib packages written by Jan Wielemaker. Please do refer to the SWI-Prolog home page: for more information on SWI-Prolog and the SWI packages.
@page Download Downloading YAP The latest development version of Yap-6 is yap-6.3.4 and can be obtained from the repositories and Several packages are shared with SWI-Prolog and need to be obtained from separate repositories. Proceed as follows: ~~~~~~ cd yap-6.3 git submodule init git submodule update ~~~~~~ Most of these repositories are basically copies of the original repositories at the SWI-Prolog site. YAP-6 will work either with or without these packages. @page Install Installing YAP To compile YAP it should be sufficient to:
  1. `autoconf`. Recent versions of YAP try to follow GNU conventions on where to place software.
    • The main executable is placed at _$BINDIR_. This executable is actually a script that calls the Prolog engine, stored at _$LIBDIR_.
    • _$LIBDIR_ is the directory where libraries are stored. YAPLIBDIR is a subdirectory that contains the Prolog engine and a Prolog library.
    • _$INCLUDEDIR_ is used if you want to use YAP as a library.
    • _$INFODIR_ is where to store `info` files. Usually /usr/local/info, /usr/info, or /usr/share/info.
  2. `make`.
  3. If the compilation succeeds, try `./yap`.
  4. If you feel satisfied with the result, do `make install`.
  5. `make install-info` will create the info files in the standard info directory.
  6. `make html` will create documentation in html format in the predefined directory.
In most systems you will need to be superuser in order to do `make install` and `make info` on the standard directories. @section Configuration_Options Tuning the Functionality of YAP Compiling YAP with the standard options give you a plain vanilla Prolog. You can tune YAP to include extra functionality by calling `configure` with the appropriate options:
  • `--enable-rational-trees=yes` gives you support for infinite rational trees.
  • `--enable-coroutining=yes` gives you support for coroutining, including freezing of goals, attributed variables, and constraints. This will also enable support for infinite rational trees.
  • `--enable-depth-limit=yes` allows depth limited evaluation, say for implementing iterative deepening.
  • `--enable-low-level-tracer=yes` allows support for tracing all calls, retries, and backtracks in the system. This can help in debugging your application, but results in performance loss.
  • `--enable-wam-profile=yes` allows profiling of abstract machine instructions. This is useful when developing YAP, should not be so useful for normal users.
  • `--enable-condor=yes` allows using the Condor system that support High Throughput Computing (HTC) on large collections of distributively owned computing resources.
  • `--enable-tabling=yes` allows tabling support. This option is still experimental.
  • `--enable-parallelism={env-copy,sba,a-cow}` allows or-parallelism supported by one of these three forms. This option is still highly experimental.
  • `--with-max-workers` allows definition of the maximum number of parallel processes (its value can be consulted at runtime using the flag `max_workers`).
  • `--with-gmp[=DIR]` give a path to where one can find the `GMP` library if not installed in the default path.
  • `--enable-threads` allows using of the multi-threading predicates provided by YAP. Depending on the operating system, the option `--enable-pthread-locking` may also need to be used.
  • `--with-max-threads` allows definition of the maximum number of threads (the default value is 1024; its value can be consulted at runtime using the flag [max_threads](@ref max_threads)).
Next section discusses machine dependent details. @section Machine_Options Tuning YAP for a Particular Machine and Compiler The default options should give you best performance under `GCC`. Although the system is tuned for this compiler we have been able to compile versions of YAP under lcc in Linux, Sun's cc compiler, IBM's xlc, SGI's cc, and Microsoft's Visual C++ 6.0. @section Tuning_for_GCC Tuning YAP for `GCC`. YAP has been developed to take advantage of `GCC` (but not to depend on it). The major advantage of `GCC` is threaded code and explicit register reservation. YAP is set by default to compile with the best compilation flags we know. Even so, a few specific options reduce portability. The option
  • `--enable-max-performance=yes` will try to support the best available flags for a specific architectural model. Currently, the option assumes a recent version of `GCC`.
  • `--enable-debug-yap` compiles YAP so that it can be debugged by tools such as `dbx` or `gdb`.
Here follow a few hints: On x86 machines the flags: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ YAP_EXTRAS= ... -DBP_FREE=1 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ tells us to use the `%bp` register (frame-pointer) as the emulator's program counter. This seems to be stable and is now default. On Sparc/Solaris2 use: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ YAP_EXTRAS= ... -mno-app-regs -DOPTIMISE_ALL_REGS_FOR_SPARC=1 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ and YAP will get two extra registers! This trick does not work on SunOS 4 machines. Note that versions of GCC can be tweaked to recognize different processors within the same instruction set, e.g. 486, Pentium, and PentiumPro for the x86; or Ultrasparc, and Supersparc for Sparc. Unfortunately, some of these tweaks do may make YAP run slower or not at all in other machines with the same instruction set, so they cannot be made default. Last, the best options also depends on the version of GCC you are using, and it is a good idea to consult the GCC manual under the menus "Invoking GCC"/"Submodel Options". Specifically, you should check `-march=XXX` for recent versions of GCC/EGCS. In the case of `GCC2.7` and other recent versions of `GCC` you can check:
  • 486: In order to take advantage of 486 specific optimizations in GCC 2.7.\*: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ YAP_EXTRAS= ... -m486 -DBP_FREE=1 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  • Pentium: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ YAP_EXTRAS= ... -m486 -malign-loops=2 -malign-jumps=2 \ -malign-functions=2 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  • PentiumPro and other recent Intel and AMD machines: PentiumPros are known not to require alignment. Check your version of `GCC` for the best `-march` option.
  • Super and UltraSparcs: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ YAP_EXTRAS= ... -msupersparc ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  • MIPS: if have a recent machine and you need a 64 bit wide address space you can use the abi 64 bits or eabi option, as in: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ CC="gcc -mabi=64" ./configure --... ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Be careful. At least for some versions of `GCC`, compiling with `-g` seems to result in broken code.
  • WIN32: GCC is distributed in the MINGW32 and CYGWIN packages. The Mingw32 environment is available from the URL: You will need to install the `msys` and `mingw` packages. You should be able to do configure, make and make install. If you use mingw32 you may want to search the contributed packages for the `gmp` multi-precision arithmetic library. If you do setup YAP with `gmp` note that libgmp.dll must be in the path, otherwise YAP will not be able to execute. The CygWin environment is available from the URL: and mirrors. We suggest using recent versions of the cygwin shell. The compilation steps under the cygwin shell are as follows: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ mkdir cyg $YAPSRC/configure --enable-coroutining \\ --enable-depth-limit \\ --enable-max-performance make make install ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ By default, YAP will use the `-mno-cygwin` option to disable the use of the cygwin dll and to enable the mingw32 subsystem instead. YAP thus will not need the cygwin dll. It instead accesses the system's CRTDLL.DLL `C` run time library supplied with Win32 platforms through the mingw32 interface. Note that some older WIN95 systems may not have CRTDLL.DLL, in this case it should be sufficient to import the file from a newer WIN95 or WIN98 machine. You should check the default installation path which is set to /YAP in the standard Makefile. This string will usually be expanded into c:\\YAP by Windows. The cygwin environment does not provide gmp on the MINGW subsystem. You can fetch a dll for the gmp library from . It is also possible to configure YAP to be a part of the cygwin environment. In this case you should use: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ mkdir cyg $YAPSRC/configure --enable-max-performance \\ --enable-cygwin=yes make make install ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ YAP will then compile using the cygwin library and will be installed in cygwin's /usr/local. You can use YAP from a cygwin console, or as a standalone application as long as it can find cygwin1.dll in its path. Note that you may use to use `--enable-depth-limit` for Aleph compatibility, and that you may want to be sure that GMP is installed.
@subsection Compiling_Under_Visual_C Compiling Under Visual C++ YAP used to compile cleanly under Microsoft's Visual C++ release 6.0. We next give a step-by-step review on how the core YAP compiled manually using this environment. First, it is a good idea to build YAP as a DLL:
  1. create a project named yapdll using File.New. The project will be a DLL project, initially empty. Notice that either the project is named yapdll or you must replace the preprocessors variable _$YAPDLL_EXPORTS_ to match your project names in the files YAPInterface.h and `c_interface.c`.
  2. add all .c files in the $YAPSRC/C directory and in the $YAPSRC\\OPTYAP directory to the Project's `Source Files` (use FileView).
  3. add all .h files in the _$YAPSRC/H_ directory, _$YAPSRC\\include_ directory and in the _$YAPSRC\\OPTYAP_ subdirectory to the Project's `Header Files`.
  4. Ideally, you should now use `m4` to generate extra .h from .m4 files and use `configure` to create a `config.h`. Or, you can be lazy, and fetch these files from _$YAPSRC\\VC\\include_.
  5. You may want to go to `Build.Set Active Configuration` and set `Project Type` to `Release`
  6. To use YAP's own include directories you have to set the Project option `Project.Project Settings.C/C++.Preprocessor.Additional Include Directories` to include the directories _$YAPSRC\\H_, _$YAPSRC\\VC\\include_, _$YAPSRC\\OPTYAP_ and _$YAPSRC\\include_. The syntax is: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ $YAPSRC\H, $YAPSRC\VC\include, $YAPSRC\OPTYAP, $YAPSRC\include ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  7. Build: the system should generate an yapdll.dll and an yapdll.lib.
  8. Copy the file yapdll.dll to your path. The file yapdll.lib should also be copied to a location where the linker can find it.
Now you are ready to create a console interface for YAP:
  1. create a second project say `wyap` with `File.New`. The project will be a WIN32 console project, initially empty.
  2. add _$YAPSRC\\console\\yap.c_ to the `Source Files`.
  3. add _$YAPSRC\\VC\\include\\config.h_ and the files in _$YAPSRC\\include_ to the `Header Files`.
  4. You may want to go to `Build.Set Active Configuration` and set `Project Type` to `Release`.
  5. you will eventually need to bootstrap the system by booting from `boot.yap`, so write: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ -b $YAPSRC\pl\boot.yap ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ in `Project.Project Settings.Debug.Program Arguments`.
  6. You need the sockets and yap libraries. Add ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ws2_32.lib yapdll.lib ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ to `Project.Project Settings.Link.Object/Library Modules` You may also need to set the `Link Path` so that VC++ will find `yapdll.lib`.
  7. set `Project.Project Settings.C/C++.Preprocessor.Additional Include Directories` to include the _$YAPSRC/VC/include_ and _$YAPSRC/include_. The syntax is: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ $YAPSRC\VC\include, $YAPSRC\include ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  8. Build the system.
  9. Use `Build.Start Debug` to boot the system, and then create the saved state with ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ['$YAPSRC\\pl\\init']. qsave_program('startup.yss'). ^Z ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ That's it, you've got YAP and the saved state!
The $YAPSRC\\VC directory has the make files to build YAP4.3.17 under VC++ 6.0. @subsection Tuning_for_SGI_cc Compiling Under SGI's cc YAP should compile under the Silicon Graphic's `cc` compiler, although we advise using the GNUCC compiler, if available.
  • 64 bit Support for 64 bits should work by using (under Bourne shell syntax): ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ CC="cc -64" $YAP_SRC_PATH/configure --... ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
@page Run Running YAP We next describe how to invoke YAP in Unix systems. @section Running_YAP_Interactively Running YAP Interactively Most often you will want to use YAP in interactive mode. Assuming that YAP is in the user's search path, the top-level can be invoked under Unix with the following command: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ yap [-s n] [-h n] [-a n] [-c IP_HOST port ] [filename] ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ All the arguments and flags are optional and have the following meaning:
  • -? print a short error message.
  • -s _Size_ allocate _Size_ KBytes for local and global stacks. The user may specify M bytes.
  • -h _Size_ allocate _Size_ KBytes for heap and auxiliary stacks
  • -t _Size_ allocate _Size_ KBytes for the trail stack
  • -L _Size_ SWI-compatible option to allocate _Size_ K bytes for local and global stacks, the local stack cannot be expanded. To avoid confusion with the load option, _Size_ must immediately follow the letter `L`.
  • -G _Size_ SWI-compatible option to allocate _Size_ K bytes for local and global stacks; the global stack cannot be expanded
  • -T _Size_ SWI-compatible option to allocate _Size_ K bytes for the trail stack; the trail cannot be expanded.
  • -l _YAP_FILE_ compile the Prolog file _YAP_FILE_ before entering the top-level.
  • -L _YAP_FILE_ compile the Prolog file _YAP_FILE_ and then halt. This option is useful for implementing scripts.
  • -g _Goal_ run the goal _Goal_ before top-level. The goal is converted from an atom to a Prolog term.
  • -z _Goal_ run the goal _Goal_ as top-level. The goal is converted from an atom to a Prolog term.
  • -b _BOOT_FILE_ boot code is in Prolog file _BOOT_FILE_. The filename must define the predicate `'$live'/0`.
  • -c IP_HOST port connect standard streams to host IP_HOST at port port
  • filename restore state saved in the given file
  • -f do not consult initial files
  • -q do not print informational messages
  • -- separator for arguments to Prolog code. These arguments are visible through the [unix/1](@ref unix) built-in predicate.
Note that YAP will output an error message on the following conditions:
  • a file name was given but the file does not exist or is not a saved YAP state;
  • the necessary amount of memory could not be allocated;
  • the allocated memory is not enough to restore the state.
When restoring a saved state, YAP will allocate the same amount of memory as that in use when the state was saved, unless a different amount is specified by flags in the command line. By default, YAP restores the file startup.yss from the current directory or from the YAP library.
  • YAP usually boots from a saved state. The saved state will use the default installation directory to search for the YAP binary unless you define the environment variable YAPBINDIR.
  • YAP always tries to find saved states from the current directory first. If it cannot it will use the environment variable YAPLIBDIR, if defined, or search the default library directory.
  • YAP will try to find library files from the YAPSHAREDIR/library directory.
@section Running_Prolog_Files Running Prolog Files YAP can also be used to run Prolog files as scripts, at least in Unix-like environments. A simple example is shown next (do not forget that the shell comments are very important): ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ #!/usr/local/bin/yap -L -- # # Hello World script file using YAP # # put a dot because of syntax errors . :- write('Hello World'), nl. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ The `#!` characters specify that the script should call the binary file YAP. Notice that many systems will require the complete path to the YAP binary. The `-L` flag indicates that YAP should consult the current file when booting and then halt. The remaining arguments are then passed to YAP. Note that YAP will skip the first lines if they start with `#` (the comment sign for Unix's shell). YAP will consult the file and execute any commands. A slightly more sophisticated example is: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ #!/usr/bin/yap -L -- # # Hello World script file using YAP # . :- initialization(main). main :- write('Hello World'), nl. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ The `initialization` directive tells YAP to execute the goal main after consulting the file. Source code is thus compiled and `main` executed at the end. The `.` is useful while debugging the script as a Prolog program: it guarantees that the syntax error will not propagate to the Prolog code. Notice that the `--` is required so that the shell passes the extra arguments to YAP. As an example, consider the following script `dump_args`: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ #!/usr/bin/yap -L -- #. main( [] ). main( [H|T] ) :- write( H ), nl, main( T ). :- unix( argv(AllArgs) ), main( AllArgs ). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ If you this run this script with the arguments: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ./dump_args -s 10000 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ the script will start an YAP process with stack size `10MB`, and the list of arguments to the process will be empty. Often one wants to run the script as any other program, and for this it is convenient to ignore arguments to YAP. This is possible by using `L --` as in the next version of `dump_args`: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ #!/usr/bin/yap -L -- main( [] ). main( [H|T] ) :- write( H ), nl, main( T ). :- unix( argv(AllArgs) ), main( AllArgs ). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ The `--` indicates the next arguments are not for YAP. Instead, they must be sent directly to the [argv](@ref argv) built-in. Hence, running ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ./dump_args test ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ will write `test` on the standard output. @page Syntax Syntax We will describe the syntax of YAP at two levels. We first will describe the syntax for Prolog terms. In a second level we describe the \a tokens from which Prolog \a terms are built. @section Formal_Syntax Syntax of Terms Below, we describe the syntax of YAP terms from the different classes of tokens defined above. The formalism used will be BNF, extended where necessary with attributes denoting integer precedence or operator type. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ term ----> subterm(1200) end_of_term_marker subterm(N) ----> term(M) [M <= N] term(N) ----> op(N, fx) subterm(N-1) | op(N, fy) subterm(N) | subterm(N-1) op(N, xfx) subterm(N-1) | subterm(N-1) op(N, xfy) subterm(N) | subterm(N) op(N, yfx) subterm(N-1) | subterm(N-1) op(N, xf) | subterm(N) op(N, yf) term(0) ----> atom '(' arguments ')' | '(' subterm(1200) ')' | '{' subterm(1200) '}' | list | string | number | atom | variable arguments ----> subterm(999) | subterm(999) ',' arguments list ----> '[]' | '[' list_expr ']' list_expr ----> subterm(999) | subterm(999) list_tail list_tail ----> ',' list_expr | ',..' subterm(999) | '|' subterm(999) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Notes:
  • \a op(N,T) denotes an atom which has been previously declared with type \a T and base precedence \a N.
  • Since ',' is itself a pre-declared operator with type \a xfy and precedence 1000, is \a subterm starts with a '(', \a op must be followed by a space to avoid ambiguity with the case of a functor followed by arguments, e.g.: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ + (a,b) [the same as '+'(','(a,b)) of arity one] ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ versus ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ +(a,b) [the same as '+'(a,b) of arity two] ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  • In the first rule for term(0) no blank space should exist between \a atom and '('.
  • Each term to be read by the YAP parser must end with a single dot, followed by a blank (in the sense mentioned in the previous paragraph). When a name consisting of a single dot could be taken for the end of term marker, the ambiguity should be avoided by surrounding the dot with single quotes.
@section Tokens Prolog Tokens Prolog tokens are grouped into the following categories: @subsection Numbers Numbers Numbers can be further subdivided into integer and floating-point numbers. @subsubsection Integers Integer numbers are described by the following regular expression: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ := {+|0{xXo}}+ ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ where {...} stands for optionality, \a + optional repetition (one or more times), \a \\\ denotes one of the characters 0 ... 9, \a | denotes or, and \a \\\ denotes the character "'". The digits before the \a \\\ character, when present, form the number basis, that can go from 0, 1 and up to 36. Letters from `A` to `Z` are used when the basis is larger than 10. Note that if no basis is specified then base 10 is assumed. Note also that the last digit of an integer token can not be immediately followed by one of the characters 'e', 'E', or '.'. Following the ISO standard, YAP also accepts directives of the form `0x` to represent numbers in hexadecimal base and of the form `0o` to represent numbers in octal base. For usefulness, YAP also accepts directives of the form `0X` to represent numbers in hexadecimal base. Example: the following tokens all denote the same integer ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 10 2'1010 3'101 8'12 16'a 36'a 0xa 0o12 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Numbers of the form `0'a` are used to represent character constants. So, the following tokens denote the same integer: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 0'd 100 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ YAP (version 6.3.4) supports integers that can fit the word size of the machine. This is 32 bits in most current machines, but 64 in some others, such as the Alpha running Linux or Digital Unix. The scanner will read larger or smaller integers erroneously. @subsubsection Floats Floating-point numbers are described by: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ := +{+} {}+ |++ {{}+} ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ where \a \\\ denotes the decimal-point character '.', \a \\\ denotes one of 'e' or 'E', and \a \\\ denotes one of '+' or '-'. Examples: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 10.0 10e3 10e-3 3.1415e+3 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Floating-point numbers are represented as a double in the target machine. This is usually a 64-bit number. @subsection Strings Character Strings Strings are described by the following rules: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ string --> '"' string_quoted_characters '"' string_quoted_characters --> '"' '"' string_quoted_characters string_quoted_characters --> '\' escape_sequence string_quoted_characters string_quoted_characters --> string_character string_quoted_characters escape_sequence --> 'a' | 'b' | 'r' | 'f' | 't' | 'n' | 'v' escape_sequence --> '\' | '"' | ''' | '`' escape_sequence --> at_most_3_octal_digit_seq_char '\' escape_sequence --> 'x' at_most_2_hexa_digit_seq_char '\' ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ where `string_character` in any character except the double quote and escape characters. Examples: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ "" "a string" "a double-quote:""" ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ The first string is an empty string, the last string shows the use of double-quoting. The implementation of YAP represents strings as lists of integers. Since YAP 4.3.0 there is no static limit on string size. Escape sequences can be used to include the non-printable characters `a` (alert), `b` (backspace), `r` (carriage return), `f` (form feed), `t` (horizontal tabulation), `n` (new line), and `v` (vertical tabulation). Escape sequences also be include the meta-characters `\\`, `"`, `'`, and ```. Last, one can use escape sequences to include the characters either as an octal or hexadecimal number. The next examples demonstrates the use of escape sequences in YAP: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ "\x0c\" "\01\" "\f" "\\" ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ The first three examples return a list including only character 12 (form feed). The last example escapes the escape character. Escape sequences were not available in C-Prolog and in original versions of YAP up to 4.2.0. Escape sequences can be disable by using: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ :- yap_flag(character_escapes,false). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ @subsection Atoms Atoms Atoms are defined by one of the following rules: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ atom --> solo-character atom --> lower-case-letter name-character* atom --> symbol-character+ atom --> single-quote single-quote atom --> ''' atom_quoted_characters ''' atom_quoted_characters --> ''' ''' atom_quoted_characters atom_quoted_characters --> '\' atom_sequence string_quoted_characters atom_quoted_characters --> character string_quoted_characters ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ where: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ denotes one of: ! ; denotes one of: # & * + - . / : < = > ? @ \ ^ ~ ` denotes one of: a...z denotes one of: _ a...z A...Z 0....9 denotes: ' ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ and `string_character` denotes any character except the double quote and escape characters. Note that escape sequences in strings and atoms follow the same rules. Examples: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ a a12x '$a' ! => '1 2' ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Version `4.2.0` of YAP removed the previous limit of 256 characters on an atom. Size of an atom is now only limited by the space available in the system. @subsection Variables Variables Variables are described by: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ + ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ where ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ denotes one of: _ A...Z denotes one of: _ a...z A...Z ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ If a variable is referred only once in a term, it needs not to be named and one can use the character `_` to represent the variable. These variables are known as anonymous variables. Note that different occurrences of `_` on the same term represent different anonymous variables. @subsection Punctuation_Tokens Punctuation Tokens Punctuation tokens consist of one of the following characters: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ( ) , [ ] { } | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ These characters are used to group terms. @subsection Layout Layout Any characters with ASCII code less than or equal to 32 appearing before a token are ignored. All the text appearing in a line after the character \a % is taken to be a comment and ignored (including \a %). Comments can also be inserted by using the sequence `/\*` to start the comment and `\*` followed by `/` to finish it. In the presence of any sequence of comments or layout characters, the YAP parser behaves as if it had found a single blank character. The end of a file also counts as a blank character for this purpose. @section Encoding Wide Character Support YAP now implements a SWI-Prolog compatible interface to wide characters and the Universal Character Set (UCS). The following text was adapted from the SWI-Prolog manual. YAP now supports wide characters, characters with character codes above 255 that cannot be represented in a single byte. Universal Character Set (UCS) is the ISO/IEC 10646 standard that specifies a unique 31-bits unsigned integer for any character in any language. It is a superset of 16-bit Unicode, which in turn is a superset of ISO 8859-1 (ISO Latin-1), a superset of US-ASCII. UCS can handle strings holding characters from multiple languages and character classification (uppercase, lowercase, digit, etc.) and operations such as case-conversion are unambiguously defined. For this reason YAP, following SWI-Prolog, has two representations for atoms. If the text fits in ISO Latin-1, it is represented as an array of 8-bit characters. Otherwise the text is represented as an array of wide chars, which may take 16 or 32 bits. This representational issue is completely transparent to the Prolog user. Users of the foreign language interface sometimes need to be aware of these issues though. Character coding comes into view when characters of strings need to be read from or written to file or when they have to be communicated to other software components using the foreign language interface. In this section we only deal with I/O through streams, which includes file I/O as well as I/O through network sockets. @subsection Stream_Encoding Wide character encodings on streams Although characters are uniquely coded using the UCS standard internally, streams and files are byte (8-bit) oriented and there are a variety of ways to represent the larger UCS codes in an 8-bit octet stream. The most popular one, especially in the context of the web, is UTF-8. Bytes 0...127 represent simply the corresponding US-ASCII character, while bytes 128...255 are used for multi-byte encoding of characters placed higher in the UCS space. Especially on MS-Windows the 16-bit Unicode standard, represented by pairs of bytes is also popular. Prolog I/O streams have a property called encoding which specifies the used encoding that influence `get_code/2` and `put_code/2` as well as all the other text I/O predicates. The default encoding for files is derived from the Prolog flag `encoding`, which is initialised from the environment. If the environment variable `LANG` ends in "UTF-8", this encoding is assumed. Otherwise the default is `text` and the translation is left to the wide-character functions of the C-library (note that the Prolog native UTF-8 mode is considerably faster than the generic `mbrtowc()` one). The encoding can be specified explicitly in [load_files/2](@ref load_files) for loading Prolog source with an alternative encoding, `open/4` when opening files or using `set_stream/2` on any open stream (not yet implemented). For Prolog source files we also provide the `encoding/1` directive that can be used to switch between encodings that are compatible to US-ASCII (`ascii`, `iso_latin_1`, `utf8` and many locales). For additional information and Unicode resources, please visit . YAP currently defines and supports the following encodings:
  • octet Default encoding for binary streams. This causes the stream to be read and written fully untranslated.
  • ascii 7-bit encoding in 8-bit bytes. Equivalent to `iso_latin_1`, but generates errors and warnings on encountering values above 127.
  • iso_latin_1 8-bit encoding supporting many western languages. This causes the stream to be read and written fully untranslated.
  • text C-library default locale encoding for text files. Files are read and written using the C-library functions `mbrtowc()` and `wcrtomb()`. This may be the same as one of the other locales, notably it may be the same as `iso_latin_1` for western languages and `utf8` in a UTF-8 context.
  • utf8 Multi-byte encoding of full UCS, compatible to `ascii`. See above.
  • unicode_be Unicode Big Endian. Reads input in pairs of bytes, most significant byte first. Can only represent 16-bit characters.
  • unicode_le Unicode Little Endian. Reads input in pairs of bytes, least significant byte first. Can only represent 16-bit characters.
Note that not all encodings can represent all characters. This implies that writing text to a stream may cause errors because the stream cannot represent these characters. The behaviour of a stream on these errors can be controlled using `open/4` or `set_stream/2` (not implemented). Initially the terminal stream write the characters using Prolog escape sequences while other streams generate an I/O exception. @subsection BOM BOM: Byte Order Mark From [Stream Encoding](@ref Stream_Encoding), you may have got the impression that text-files are complicated. This section deals with a related topic, making live often easier for the user, but providing another worry to the programmer. *BOM* or Byte Order Marker is a technique for identifying Unicode text-files as well as the encoding they use. Such files start with the Unicode character `0xFEFF`, a non-breaking, zero-width space character. This is a pretty unique sequence that is not likely to be the start of a non-Unicode file and uniquely distinguishes the various Unicode file formats. As it is a zero-width blank, it even doesn't produce any output. This solves all problems, or ... Some formats start of as US-ASCII and may contain some encoding mark to switch to UTF-8, such as the `encoding="UTF-8"` in an XML header. Such formats often explicitly forbid the the use of a UTF-8 BOM. In other cases there is additional information telling the encoding making the use of a BOM redundant or even illegal. The BOM is handled by the `open/4` predicate. By default, text-files are probed for the BOM when opened for reading. If a BOM is found, the encoding is set accordingly and the property `bom(true)` is available through [stream_property/2](@ref stream_property). When opening a file for writing, writing a BOM can be requested using the option `bom(true)` with `open/4`. @page Loading_Programs Loading and Manipulating Programs Next, we present the main predicates and directives available to load files and to control the Prolog environment. @section Compiling Program loading and updating
  • consult(+ _F_) @anchor consult Adds the clauses written in file _F_ or in the list of files _F_ to the program. In YAP [consult/1](@ref consult) does not remove previous clauses for the procedures defined in _F_. Moreover, note that all code in YAP is compiled.
  • reconsult(+ _F_) @anchor reconsult Updates the program replacing the previous definitions for the predicates defined in _F_.
  • [+ _F_] @anchor nil []/1 The same as `consult(F)`.
  • [-+ _F_] @anchor dash_nil [-]/1 The same as `reconsult(F)` Example: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ?- [file1, -file2, -file3, file4]. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ will consult `file1` `file4` and reconsult `file2` and `file3`.
  • compile(+ _F_) @anchor compile In YAP, the same as [reconsult/1](@ref reconsult).
  • load_files(+ _Files_, + _Options_) @anchor load_files General implementation of `consult`. Execution is controlled by the following flags:
    • autoload(+ _Autoload_) SWI-compatible option where if _Autoload_ is `true` predicates are loaded on first call. Currently not supported.
    • derived_from(+ _File_) SWI-compatible option to control make. Currently not supported.
    • encoding(+ _Encoding_) Character encoding used in consulting files. Please (see [Encoding](@ref Encoding)) for supported encodings.
    • expand(+ _Bool_) Not yet implemented. In SWI-Prolog, if `true`, run the filenames through [expand_file_name/2](@ref expand_file_name) and load the returned files. Default is false, except for [consult/1](@ref consult) which is intended for interactive use.
    • if(+ _Condition_) Load the file only if the specified _Condition_ is satisfied. The value `true` the file unconditionally, `changed` loads the file if it was not loaded before, or has been modified since it was loaded the last time, `not_loaded` loads the file if it was not loaded before.
    • imports(+ _ListOrAll_) If `all` and the file is a module file, import all public predicates. Otherwise import only the named predicates. Each predicate is referred to as `\/\`. This option has no effect if the file is not a module file.
    • must_be_module(+ _Bool_) If true, raise an error if the file is not a module file. Used by `use_module/[1,2]`.
    • silent(+ _Bool_) If true, load the file without printing a message. The specified value is the default for all files loaded as a result of loading the specified files.
    • stream(+ _Input_) This SWI-Prolog extension compiles the data from the stream _Input_. If this option is used, _Files_ must be a single atom which is used to identify the source-location of the loaded clauses as well as remove all clauses if the data is re-consulted. This option is added to allow compiling from non-file locations such as databases, the web, the user (see consult/1) or other servers.
    • compilation_mode(+ _Mode_) This extension controls how procedures are compiled. If _Mode_ is `compact` clauses are compiled and no source code is stored; if it is `source` clauses are compiled and source code is stored; if it is `assert_all` clauses are asserted into the data-base.
    • comnsult(+ _Mode_) This extension controls the type of file to load. If _Mode_ is `consult`, clauses are added to the data-base, is `reconsult`, clauses are recompiled, is `db`, these are facts that need to be added to the data-base, is `exo`, these are facts with atoms and integers that need a very compact representation.
  • ensure_loaded(+ _F_) [ISO] @anchor ensure_loaded When the files specified by _F_ are module files, [ensure_loaded/1](@ref ensure_loaded) loads them if they have note been previously loaded, otherwise advertises the user about the existing name clashes and prompts about importing or not those predicates. Predicates which are not public remain invisible. When the files are not module files, [ensure_loaded/1](@ref ensure_loaded) loads them if they have not been loaded before, does nothing otherwise. _F_ must be a list containing the names of the files to load.
  • load_db(+ _Files_) @anchor load_db Load a database of facts with equal structure.
  • exo_files(+ _Files_) @anchor exo_files Load compactly a database of facts with equal structure. Useful when wanting to read in a very compact way database tables.
  • make @anchor make SWI-Prolog built-in to consult all source files that have been changed since they were consulted. It checks all loaded source files. make/0 can be combined with the compiler to speed up the development of large packages. In this case compile the package using ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ sun% pl -g make -o my_program -c file ... ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ If `my_program' is started it will first reconsult all source files that have changed since the compilation.
  • include(+ _F_) [ISO] @anchor include The `include` directive includes the text files or sequence of text files specified by _F_ into the file being currently consulted.
@section Setting_the_Compiler Looking for Files @ref abs_file_name @section Changing_the_CompilerbAs_Behavior Changing the Compiler's Behavior This section presents a set of built-ins predicates designed to set the environment for the compiler.
  • source_mode(- _O_,+ _N_) @anchor source_mode The state of source mode can either be on or off. When the source mode is on, all clauses are kept both as compiled code and in a "hidden" database. _O_ is unified with the previous state and the mode is set according to _N_.
  • source @anchor source After executing this goal, YAP keeps information on the source of the predicates that will be consulted. This enables the use of [listing/0](@ref listing), `listing/1` and [clause/2](@ref clause) for those clauses. The same as `source_mode(_,on)` or as declaring all newly defined static procedures as `public`.
  • no_source @anchor no_source The opposite to `source`. The same as `source_mode(_,off)`.
  • compile_expressions @anchor compile_expressions After a call to this predicate, arithmetical expressions will be compiled. (see example below). This is the default behavior.
  • do_not_compile_expressions @anchor do_not_compile_expressions After a call to this predicate, arithmetical expressions will not be compiled. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ?- source, do_not_compile_expressions. yes ?- [user]. | p(X) :- X is 2 * (3 + 8). | :- end_of_file. ?- compile_expressions. yes ?- [user]. | q(X) :- X is 2 * (3 + 8). | :- end_of_file. :- listing. p(A):- A is 2 * (3 + 8). q(A):- A is 22. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  • hide(+ _Atom_) @anchor hide Make atom _Atom_ invisible.
  • unhide(+ _Atom_) @anchor unhide Make hidden atom _Atom_ visible.
  • hide_predicate(+ _Pred_) @anchor hide_predicate Make predicate _Pred_ invisible to `current_predicate/2`, `listing`, and friends.
  • stash_predicate(+ _Pred_) @anchor stash_predicate Make predicate _Pred_ invisible to new code, and to `current_predicate/2`, `listing`, and friends. New predicates with the same name and functor can be declared.
  • expand_exprs(- _O_,+ _N_) @anchor expand_exprs Puts YAP in state _N_ (`on` or `off`) and unify _O_ with the previous state, where _On_ is equivalent to `compile_expressions` and `off` is equivalent to `do_not_compile_expressions`. This predicate was kept to maintain compatibility with C-Prolog.
  • style_check(+ _X_) @anchor style_check Turns on style checking according to the attribute specified by _X_, which must be one of the following:
    • single_var Checks single occurrences of named variables in a clause.
    • discontiguous Checks non-contiguous clauses for the same predicate in a file.
    • multiple Checks the presence of clauses for the same predicate in more than one file when the predicate has not been declared as `multifile`
    • all Performs style checking for all the cases mentioned above.
    By default, style checking is disabled in YAP unless we are in `sicstus` or `iso` language mode. The [style_check/1](@ref style_check) built-in is now deprecated. Please use the `set_prolog_flag/1` instead.
  • no_style_check(+ _X_) @anchor no_style_check Turns off style checking according to the attribute specified by _X_, which has the same meaning as in [style_check/1](@ref style_check). The [no_style_check/1](@ref no_style_check) built-in is now deprecated. Please use the `set_prolog_flag/1` instead.
  • multifile _P_ [ISO] @anchor multifile Instructs the compiler about the declaration of a predicate _P_ in more than one file. It must appear in the first of the loaded files where the predicate is declared, and before declaration of any of its clauses. Multifile declarations affect [reconsult/1](@ref reconsult) and [compile/1](@ref compile): when a multifile predicate is reconsulted, only the clauses from the same file are removed. Since YAP4.3.0 multifile procedures can be static or dynamic.
  • discontiguous(+ _G_) [ISO] @anchor discontiguous Declare that the arguments are discontiguous procedures, that is, clauses for discontigous procedures may be separated by clauses from other procedures.
  • initialization(+ _G_) [ISO] @anchor initialization The compiler will execute goals _G_ after consulting the current file.
  • initialization(+ _Goal_,+ _When_) Similar to [initialization/1](@ref initialization), but allows for specifying when _Goal_ is executed while loading the program-text:
    • now Execute _Goal_ immediately.
    • after_load Execute _Goal_ after loading program-text. This is the same as initialization/1.
    • restore Do not execute _Goal_ while loading the program, but only when restoring a state (not implemented yet).
  • prolog_to_os_filename(+ _PrologPath_,- _OsPath_) @anchor prolog_to_os_filename This is an SWI-Prolog built-in. Converts between the internal Prolog pathname conventions and the operating-system pathname conventions. The internal conventions are Unix and this predicates is equivalent to =/2 (unify) on Unix systems. On DOS systems it will change the directory-separator, limit the filename length map dots, except for the last one, onto underscores.
  • expand_file_name(+ _WildCard_,- _List_) @anchor expand_file_name This is an SWI-Prolog built-in. Unify _List_ with a sorted list of files or directories matching _WildCard_. The normal Unix wildcard constructs ?, \\\*, [ ... ] and {...} are recognised. The interpretation of {...} is interpreted slightly different from the C shell (csh(1)). The comma separated argument can be arbitrary patterns, including {...} patterns. The empty pattern is legal as well: {.pl,} matches either .pl or the empty string. If the pattern contains wildcard characters, only existing files and directories are returned. Expanding a pattern' without wildcard characters returns the argument, regardless on whether or not it exists. Before expanding wildcards, the construct $var is expanded to the value of the environment variable var and a possible leading ~ character is expanded to the user's home directory. In Windows, the home directory is determined as follows: if the environment variable `HOME` exists, this is used. If the variables `HOMEDRIVE` and `HOMEPATH` exist (Windows-NT), these are used. At initialisation, the system will set the environment variable `HOME` to point to the YAP home directory if neither `HOME` nor `HOMEPATH` and `HOMEDRIVE` are defined.
  • public _P_ [ISO extension] @anchor public Instructs the compiler that the source of a predicate of a list of predicates _P_ must be kept. This source is then accessible through the [clause/2](@ref clause) procedure and through the `listing` family of built-ins. Note that all dynamic procedures are public. The `source` directive defines all new or redefined predicates to be public. Since YAP4.3.0 multifile procedures can be static or dynamic.
@section Conditional_Compilation Conditional Compilation Conditional compilation builds on the same principle as [term_expansion/2](@ref term_expansion), `goal_expansion/2` and the expansion of grammar rules to compile sections of the source-code conditionally. One of the reasons for introducing conditional compilation is to simplify writing portable code. Note that these directives can only be appear as separate terms in the input. Typical usage scenarios include:
  • Load different libraries on different dialects
  • Define a predicate if it is missing as a system predicate
  • Realise totally different implementations for a particular part of the code due to different capabilities.
  • Realise different configuration options for your software.
  • if(+ _Goal_) @anchor if Compile subsequent code only if _Goal_ succeeds. For enhanced portability, _Goal_ is processed by `expand_goal/2` before execution. If an error occurs, the error is printed and processing proceeds as if _Goal_ has failed.
  • else @anchor else Start `else' branch.
  • endif @anchor endif End of conditional compilation.
  • elif(+ _Goal_) @anchor elif Equivalent to `:- else. :-if(Goal) ... :- endif.` In a sequence as below, the section below the first matching elif is processed, If no test succeeds the else branch is processed. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ :- if(test1). section_1. :- elif(test2). section_2. :- elif(test3). section_3. :- else. section_else. :- endif. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
@section Saving Saving and Loading Prolog States
  • save(+ _F_) @anchor save Saves an image of the current state of YAP in file _F_. From *YAP4.1.3* onwards, YAP saved states are executable files in the Unix ports.
  • save(+ _F_,- _OUT_) Saves an image of the current state of YAP in file _F_. From *YAP4.1.3* onwards, YAP saved states are executable files in the Unix ports. Unify _OUT_ with 1 when saving the file and _OUT_ with 0 when restoring the saved state.
  • save_program(+ _F_) @anchor save_program Saves an image of the current state of the YAP database in file _F_.
  • save_program(+ _F_, : _G_) Saves an image of the current state of the YAP database in file _F_, and guarantee that execution of the restored code will start by trying goal _G_.
  • qsave_program(+ _F_, + _ListOfOpts_) @anchor qsave_program Saves the current state of the program to the file _File_. The result is a resource archive containing a saved state that expresses all Prolog data from the running program and all user-defined resources. Depending on the stand_alone option, the resource is headed by the emulator, a Unix shell script or nothing. Options is a list of additional options:
    • stack(+ _KBytes_) Limit for the local and global stack.
    • trail(+ _KBytes_) Limit for the trail stack.
    • goal(: _Callable_) Initialization goal for the new executable (see -g).
    • init_file(+ _Atom_) Default initialization file for the new executable. See -f.
  • restore(+ _F_) @anchor restore Restores a previously saved state of YAP from file _F_. YAP always tries to find saved states from the current directory first. If it cannot it will use the environment variable [YAPLIBDIR](@ref YAPLIBDIR), if defined, or search the default library directory.
@section Modules The Module System Module systems are quite important for the development of large applications. YAP implements a module system compatible with the Quintus Prolog module system. The YAP module system is predicate-based. This means a module consists of a set of predicates (or procedures), such that some predicates are public and the others are local to a module. Atoms and terms in general are global to the system. Moreover, the module system is flat, meaning that we do not support a hierarchy of modules. Modules can automatically import other modules, though. For compatibility with other module systems the YAP module system is non-strict, meaning both that there is a way to access predicates private to a module and that it is possible to declare predicates for a module from some other module. YAP allows one to ignore the module system if one does not want to use it. Last note that using the module system does not introduce any significant overheads. @subsection Module_Concepts Module Concepts The YAP module system applies to predicates. All predicates belong to a module. System predicates belong to the module `primitives`, and by default new predicates belong to the module `user`. Predicates from the module `primitives` are automatically visible to every module. Every predicate must belong to a module. This module is called its source module. By default, the source module for a clause occurring in a source file with a module declaration is the declared module. For goals typed in a source file without module declarations, their module is the module the file is being loaded into. If no module declarations exist, this is the current type-in module. The default type-in module is `user`, but one can set the current module by using the built-in `module/1`. Note that in this module system one can explicitly specify the source mode for a clause by prefixing a clause with its module, say: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ user:(a :- b). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ In fact, to specify the source module for a clause it is sufficient to specify the source mode for the clause's head: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ user:a :- b. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ The rules for goals are similar. If a goal appears in a text file with a module declaration, the goal's source module is the declared module. Otherwise, it is the module the file is being loaded into or the type-in module. One can override this rule by prefixing a goal with the module it is supposed to be executed in, say: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ nasa:launch(apollo,13). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ will execute the goal `launch(apollo,13)` as if the current source module was `nasa`. Note that this rule breaks encapsulation and should be used with care. @subsection Defining_Modules Defining a New Module A new module is defined by a `module` declaration:
  • module(+ _M_,+ _L_) @anchor module This directive defines the file where it appears as a module file; it must be the first declaration in the file. _M_ must be an atom specifying the module name; _L_ must be a list containing the module's public predicates specification, in the form `[predicate_name/arity,...]`. The public predicates of a module file can be made accessible by other files through the directives [use_module/1](@ref use_module), `use_module/2`, [ensure_loaded/1](@ref ensure_loaded) and the predicates [consult/1](@ref consult) or [reconsult/1](@ref reconsult). The non-public predicates of a module file are not visible by other files; they can, however, be accessed by prefixing the module name with the `:/2` operator.
The built-in `module/1` sets the current source module:
  • module(+ _M_,+ _L_, + _Options_) Similar to [module/2](@ref module), this directive defines the file where it appears in as a module file; it must be the first declaration in the file. _M_ must be an atom specifying the module name; _L_ must be a list containing the module's public predicates specification, in the form `[predicate_name/arity,...]`. The last argument _Options_ must be a list of options, which can be:
    • filename the filename for a module to import into the current module.
    • library(file) a library file to import into the current module.
    • hide( _Opt_) if _Opt_ is `false`, keep source code for current module, if `true`, disable.
  • module(+ _M_) Defines _M_ to be the current working or type-in module. All files which are not bound to a module are assumed to belong to the working module (also referred to as type-in module). To compile a non-module file into a module which is not the working one, prefix the file name with the module name, in the form ` _Module_: _File_`, when loading the file.
  • export(+ _PredicateIndicator_) @anchor export Add predicates to the public list of the context module. This implies the predicate will be imported into another module if this module is imported with `use_module/[1,2]`. Note that predicates are normally exported using the directive [module/2](@ref module). [export/1](@ref export) is meant to handle export from dynamically created modules. The directive argument may also be a list of predicates.
  • export_list(? _Mod_,? _ListOfPredicateIndicator_) @anchor export_list The list _ListOfPredicateIndicator_ contains all predicates exported by module _Mod_.
@subsection Using_Modules Using Modules By default, all procedures to consult a file will load the modules defined therein. The two following declarations allow one to import a module explicitly. They differ on whether one imports all predicate declared in the module or not.
  • use_module(+ _F_) @anchor use_module Loads the files specified by _F_, importing all their public predicates. Predicate name clashes are resolved by asking the user about importing or not the predicate. A warning is displayed when _F_ is not a module file.
  • use_module(+ _F_,+ _L_) Loads the files specified by _F_, importing the predicates specified in the list _L_. Predicate name clashes are resolved by asking the user about importing or not the predicate. A warning is displayed when _F_ is not a module file.
  • use_module(? _M_,? _F_,+ _L_) If module _M_ has been defined, import the procedures in _L_ to the current module. Otherwise, load the files specified by _F_, importing the predicates specified in the list _L_.
@subsection MetahYPredicates_in_Modules Meta-Predicates and Modules The module system must know whether predicates operate on goals or clauses. Otherwise, such predicates would call a goal in the module they were defined, instead of calling it in the module they are currently executing. So, for instance, consider a file example.pl: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ :- module(example,[a/1]). a(G) :- call(G) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ We import this module with `use_module(example)` into module `user`. The expected behavior for a goal `a(p)` is to execute goal `p` within the module `user`. However, `a/1` will call `p` within module `example`. The [meta_predicate/1](@ref meta_predicate) declaration informs the system that some arguments of a predicate are goals, clauses, clauses heads or other terms related to a module, and that these arguments must be prefixed with the current source module:
  • meta_predicate _G1_,...., _Gn_ @anchor meta_predicate Each _Gi_ is a mode specification. If the argument is `:`, it does not refer directly to a predicate but must be module expanded. If the argument is an integer, the argument is a goal or a closure and must be expanded. Otherwise, the argument is not expanded. Note that the system already includes declarations for all built-ins. For example, the declaration for [call/1](@ref call) and [setof/3](@ref setof) are: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ :- meta_predicate call(0), setof(?,0,?). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
The previous example is expanded to the following code which explains, why the goal `a(p)` calls `p` in `example` and not in `user`. The goal `call(G)` is expanded because of the meta-predicate declaration for [call/1](@ref call). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ :- module(example,[a/1]). a(G) :- call(example:G) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ By adding a meta-predicate declaration for `a/1`, the goal `a(p)` in module user will be expanded to `a(user:p)` thereby preserving the module information. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ :- module(example,[a/1]). :- meta_predicate a(:). a(G) :- call(G) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ An alternate mechanism is the directive [module_transparent/1](@ref module_transparent) offered for compatibility with SWI-Prolog.
  • module_transparent + _Preds_ @anchor module_transparent _Preds_ is a comma separated sequence of name/arity predicate indicators (like [dynamic/1](@ref dynamic)). Each goal associated with a transparent declared predicate will inherit the context module from its parent goal.
@subsection RehYExporting_Modules Re-Exporting Predicates From Other Modules It is sometimes convenient to re-export predicates originally defined in a different module. This is often useful if you are adding to the functionality of a module, or if you are composing a large module with several small modules. The following declarations can be used for that purpose:
  • reexport(+ _F_) @anchor reexport Export all predicates defined in file _F_ as if they were defined in the current module.
  • reexport(+ _F_,+ _Decls_) Export predicates defined in file _F_ according to _Decls_. The declarations may be of the form:
    • A list of predicate declarations to be exported. Each declaration may be a predicate indicator or of the form `` _PI_ `as` _NewName_'', meaning that the predicate with indicator _PI_ is to be exported under name _NewName_.
    • `except`( _List_) In this case, all predicates not in _List_ are exported. Moreover, if ` _PI_ `as` _NewName_` is found, the predicate with indicator _PI_ is to be exported under name _NewName_ as before.
Re-exporting predicates must be used with some care. Please, take into account the following observations:
  • The `reexport` declarations must be the first declarations to follow the `module` declaration.
  • It is possible to use both `reexport` and `use_module`, but all predicates reexported are automatically available for use in the current module.
  • In order to obtain efficient execution, YAP compiles dependencies between re-exported predicates. In practice, this means that changing a `reexport` declaration and then *just* recompiling the file may result in incorrect execution.
@page BuilthYins Built-In Predicates Library @section Control Control Predicates This chapter describes the predicates for controlling the execution of Prolog programs. In the description of the arguments of functors the following notation will be used:
  • a preceding plus sign will denote an argument as an "input argument" - it cannot be a free variable at the time of the call;
  • a preceding minus sign will denote an "output argument";
  • an argument with no preceding symbol can be used in both ways.
  • + _P_, + _Q_ [ISO] @anchor cO Conjunction of goals (and). Example: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ p(X) :- q(X), r(X). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ should be read as "p( _X_) if q( _X_) and r( _X_)".
  • + _P_ ; + _Q_ [ISO] @anchor mM Disjunction of goals (or). Example: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ p(X) :- q(X); r(X). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ should be read as "p( _X_) if q( _X_) or r( _X_)".
  • true [ISO] @anchor true Succeeds once.
  • fail [ISO] @anchor fail Always fails.
  • false [ISO] @anchor false The same as fail.
  • ! [ISO] @anchor eX Read as "cut". Cuts any choices taken in the current procedure. When first found "cut" succeeds as a goal, but if backtracking should later return to it, the parent goal (the one which matches the head of the clause containing the "cut", causing the clause activation) will fail. This is an extra-logical predicate and cannot be explained in terms of the declarative semantics of Prolog. example: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ member(X,[X|_]). member(X,[_|L]) :- member(X,L). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ With the above definition ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ?- member(X,[1,2,3]). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ will return each element of the list by backtracking. With the following definition: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ member(X,[X|_]) :- !. member(X,[_|L]) :- member(X,L). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ the same query would return only the first element of the list, since backtracking could not "pass through" the cut.
  • \\+ + _P_ [ISO] @anchor bQ Goal _P_ is not provable. The execution of this predicate fails if and only if the goal _P_ finitely succeeds. It is not a true logical negation, which is impossible in standard Prolog, but "negation-by-failure". This predicate might be defined as: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ \+(P) :- P, !, fail. \+(_). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ if _P_ did not include "cuts".
  • not + _P_ @anchor not Goal _P_ is not provable. The same as `'\\+ _P_'`. This predicate is kept for compatibility with C-Prolog and previous versions of YAP. Uses of [not/1](@ref not) should be replace by `(\\+)/1`, as YAP does not implement true negation.
  • + _P_ -\> + _Q_ [ISO] @anchor hYgG Read as "if-then-else" or "commit". This operator is similar to the conditional operator of imperative languages and can be used alone or with an else part as follows:
    • +P -\> +Q "if P then Q".
    • +P -\> +Q; +R "if P then Q else R".
    These two predicates could be defined respectively in Prolog as: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ (P -> Q) :- P, !, Q. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ and ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ (P -> Q; R) :- P, !, Q. (P -> Q; R) :- R. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ if there were no "cuts" in _P_, _Q_ and _R_. Note that the commit operator works by "cutting" any alternative solutions of _P_. Note also that you can use chains of commit operators like: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ P -> Q ; R -> S ; T. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Note that `(-\>)/2` does not affect the scope of cuts in its arguments.
  • + _Condition_ \*-\> + _Action_ ; + _Else_ @anchor sThYgG This construct implements the so-called soft-cut. The control is defined as follows: If _Condition_ succeeds at least once, the semantics is the same as ( _Condition_, _Action_). If _Condition_ does not succeed, the semantics is that of (\\+ _Condition_, _Else_). In other words, If _Condition_ succeeds at least once, simply behave as the conjunction of _Condition_ and _Action_, otherwise execute _Else_. The construct _A \*-\> B_, i.e. without an _Else_ branch, is translated as the normal conjunction _A_, _B_.
  • repeat [ISO] @anchor repeat Succeeds repeatedly. In the next example, `repeat` is used as an efficient way to implement a loop. The next example reads all terms in a file: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ a :- repeat, read(X), write(X), nl, X=end_of_file, !. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ the loop is effectively terminated by the cut-goal, when the test-goal `X=end` succeeds. While the test fails, the goals `read(X)`, `write(X)`, and `nl` are executed repeatedly, because backtracking is caught by the `repeat` goal. The built-in `repeat/1` could be defined in Prolog by: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ repeat. repeat :- repeat. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  • call(+ _P_) [ISO] @anchor call If _P_ is instantiated to an atom or a compound term, the goal `call( _P_)` is executed as if the value of `P` was found instead of the call to [call/1](@ref call), except that any "cut" occurring in _P_ only cuts alternatives in the execution of _P_.
  • incore(+ _P_) @anchor incore The same as [call/1](@ref call).
  • call(+ _Closure_,...,? _Ai_,...) [ISO] @anchor calln Meta-call where _Closure_ is a closure that is converted into a goal by appending the _Ai_ additional arguments. The number of arguments varies between 0 and 10.
  • call_with_args(+ _Name_,...,? _Ai_,...) @anchor call_with_argsn Meta-call where _Name_ is the name of the procedure to be called and the _Ai_ are the arguments. The number of arguments varies between 0 and 10. New code should use `call/N` for better portability. If _Name_ is a complex term, then [call_with_args/n](@ref call_with_argsn) behaves as [call/n](@ref calln): ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ call(p(X1,...,Xm), Y1,...,Yn) :- p(X1,...,Xm,Y1,...,Yn). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  • + _P_ @anchor var_call The same as `call( _P_)`. This feature has been kept to provide compatibility with C-Prolog. When compiling a goal, YAP generates a `call( _X_)` whenever a variable _X_ is found as a goal. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ a(X) :- X. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ is converted to: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ a(X) :- call(X). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  • if(? _G_,? _H_,? _I_) Call goal _H_ once per each solution of goal _H_. If goal _H_ has no solutions, call goal _I_. The built-in `if/3` is similar to `-\>/3`, with the difference that it will backtrack over the test goal. Consider the following small data-base: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ a(1). b(a). c(x). a(2). b(b). c(y). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Execution of an `if/3` query will proceed as follows: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ?- if(a(X),b(Y),c(Z)). X = 1, Y = a ? ; X = 1, Y = b ? ; X = 2, Y = a ? ; X = 2, Y = b ? ; no ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ The system will backtrack over the two solutions for `a/1` and the two solutions for `b/1`, generating four solutions. Cuts are allowed inside the first goal _G_, but they will only prune over _G_. If you want _G_ to be deterministic you should use if-then-else, as it is both more efficient and more portable.
  • once(: _G_) [ISO] @anchor once Execute the goal _G_ only once. The predicate is defined by: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ once(G) :- call(G), !. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Note that cuts inside [once/1](@ref once) can only cut the other goals inside [once/1](@ref once).
  • forall(: _Cond_,: _Action_) @anchor forall For all alternative bindings of _Cond_ _Action_ can be proven. The example verifies that all arithmetic statements in the list _L_ are correct. It does not say which is wrong if one proves wrong. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ?- forall(member(Result = Formula, [2 = 1 + 1, 4 = 2 * 2]), Result =:= Formula). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  • ignore(: _Goal_) @anchor ignore Calls _Goal_ as [once/1](@ref once), but succeeds, regardless of whether `Goal` succeeded or not. Defined as: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ignore(Goal) :- Goal, !. ignore(_). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  • abort @anchor abort Abandons the execution of the current goal and returns to top level. All break levels (see [break/0](@ref break) below) are terminated. It is mainly used during debugging or after a serious execution error, to return to the top-level.
  • break @anchor break Suspends the execution of the current goal and creates a new execution level similar to the top level, displaying the following message: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ [ Break (level ) ] ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ telling the depth of the break level just entered. To return to the previous level just type the end-of-file character or call the end_of_file predicate. This predicate is especially useful during debugging.
  • halt [ISO] @anchor halt Halts Prolog, and exits to the calling application. In YAP, [halt/0](@ref halt) returns the exit code `0`.
  • halt(+ _I_) [ISO] Halts Prolog, and exits to the calling application returning the code given by the integer _I_.
  • catch(+ _Goal_,+ _Exception_,+ _Action_) [ISO] @anchor catch The goal `catch( _Goal_, _Exception_, _Action_)` tries to execute goal _Goal_. If during its execution, _Goal_ throws an exception _E'_ and this exception unifies with _Exception_, the exception is considered to be caught and _Action_ is executed. If the exception _E'_ does not unify with _Exception_, control again throws the exception. The top-level of YAP maintains a default exception handler that is responsible to capture uncaught exceptions.
  • throw(+ _Ball_) [ISO] @anchor throw The goal `throw( _Ball_)` throws an exception. Execution is stopped, and the exception is sent to the ancestor goals until reaching a matching [catch/3](@ref catch), or until reaching top-level.
  • garbage_collect @anchor garbage_collect The goal `garbage_collect` forces a garbage collection.
  • garbage_collect_atoms @anchor garbage_collect_atoms The goal `garbage_collect` forces a garbage collection of the atoms in the data-base. Currently, only atoms are recovered.
  • gc @anchor gc The goal `gc` enables garbage collection. The same as `yap_flag(gc,on)`.
  • nogc @anchor nogc The goal `nogc` disables garbage collection. The same as `yap_flag(gc,off)`.
  • grow_heap(+ _Size_) @anchor grow_heap Increase heap size _Size_ kilobytes.
  • grow_stack(+ _Size_) @anchor grow_stack Increase stack size _Size_ kilobytes.
@section Undefined_Procedures Handling Undefined Procedures A predicate in a module is said to be undefined if there are no clauses defining the predicate, and if the predicate has not been declared to be dynamic. What YAP does when trying to execute undefined predicates can be specified in three different ways:
  • By setting an YAP flag, through the [yap_flag/2](@ref yap_flag) or [set_prolog_flag/2](@ref set_prolog_flag) built-ins. This solution generalizes the ISO standard.
  • By using the [unknown/2](@ref unknown) built-in (this solution is compatible with previous releases of YAP).
  • By defining clauses for the hook predicate `user:unknown_predicate_handler/3`. This solution is compatible with SICStus Prolog.
In more detail:
  • unknown(- _O_,+ _N_) @anchor unknown Specifies an handler to be called is a program tries to call an undefined static procedure _P_. The arity of _N_ may be zero or one. If the arity is `0`, the new action must be one of `fail`, `warning`, or `error`. If the arity is `1`, _P_ is an user-defined handler and at run-time, the argument to the handler _P_ will be unified with the undefined goal. Note that _N_ must be defined prior to calling [unknown/2](@ref unknown), and that the single argument to _N_ must be unbound. In YAP, the default action is to `fail` (note that in the ISO Prolog standard the default action is `error`). After defining `undefined/1` by: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ undefined(A) :- format('Undefined predicate: ~w~n',[A]), fail. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ and executing the goal: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ unknown(U,undefined(X)). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ a call to a predicate for which no clauses were defined will result in the output of a message of the form: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Undefined predicate: user:xyz(A1,A2) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ followed by the failure of that call.
  • yap_flag(unknown,+ _SPEC_) @anchor yap_flag_unknown Alternatively, one can use [yap_flag/2](@ref yap_flag), [current_prolog_flag/2](@ref current_prolog_flag), or [set_prolog_flag/2](@ref set_prolog_flag), to set this functionality. In this case, the first argument for the built-ins should be `unknown`, and the second argument should be either `error`, `warning`, `fail`, or a goal.
  • user:unknown_predicate_handler(+G,+M,?NG) @anchor unknown_predicate_handler The user may also define clauses for `user:unknown_predicate_handler/3` hook predicate. This user-defined procedure is called before any system processing for the undefined procedure, with the first argument _G_ set to the current goal, and the second _M_ set to the current module. The predicate _G_ will be called from within the user module. If `user:unknown_predicate_handler/3` succeeds, the system will execute _NG_. If `user:unknown_predicate_handler/3` fails, the system will execute default action as specified by [unknown/2](@ref unknown).
  • exception(+ _Exception_, + _Context_, - _Action_) @anchor exception Dynamic predicate, normally not defined. Called by the Prolog system on run-time exceptions that can be repaired `just-in-time'. The values for _Exception_ are described below. See also [catch/3](@ref catch) and [throw/1](@ref throw). If this hook predicate succeeds it must instantiate the _Action_ argument to the atom `fail` to make the operation fail silently, `retry` to tell Prolog to retry the operation or `error` to make the system generate an exception. The action `retry` only makes sense if this hook modified the environment such that the operation can now succeed without error.
    • undefined_predicate _Context_ is instantiated to a predicate-indicator ( _Module:Name/Arity_). If the predicate fails Prolog will generate an existence_error exception. The hook is intended to implement alternatives to the SWI built-in autoloader, such as autoloading code from a database. Do not use this hook to suppress existence errors on predicates. See also `unknown`.
    • undefined_global_variable _Context_ is instantiated to the name of the missing global variable. The hook must call [nb_setval/2](@ref nb_setval) or [b_setval/2](@ref b_setval) before returning with the action retry.
@section Messages Message Handling The interaction between YAP and the user relies on YAP's ability to portray messages. These messages range from prompts to error information. All message processing is performed through the builtin [print_message/2](@ref print_message), in two steps:
  • The message is processed into a list of commands
  • The commands in the list are sent to the `format/3` builtin in sequence.
The first argument to [print_message/2](@ref print_message) specifies the importance of the message. The options are:
  • error error handling
  • warning compilation and run-time warnings,
  • informational generic informational messages
  • help help messages (not currently implemented in YAP)
  • query query used in query processing (not currently implemented in YAP)
  • silent messages that do not produce output but that can be intercepted by hooks.
The next table shows the main predicates and hooks associated to message handling in YAP:
  • print_message(+ _Kind_, _Term_) @anchor print_message The predicate print_message/2 is used to print messages, notably from exceptions in a human-readable format. _Kind_ is one of `informational`, `banner`, `warning`, `error`, `help` or `silent`. A human-readable message is printed to the stream [user_error](@ref user_error). If the Prolog flag [verbose](@ref verbose) is `silent`, messages with _Kind_ `informational`, or `banner` are treated as silent.@c See \\cmdlineoption{-q}. This predicate first translates the _Term_ into a list of `message lines' (see [print_message_lines/3](@ref print_message_lines) for details). Next it will call the hook [message_hook/3](@ref message_hook) to allow the user intercepting the message. If [message_hook/3](@ref message_hook) fails it will print the message unless _Kind_ is silent. If you need to report errors from your own predicates, we advise you to stick to the existing error terms if you can; but should you need to invent new ones, you can define corresponding error messages by asserting clauses for `prolog:message/2`. You will need to declare the predicate as multifile.
  • print_message_lines(+ _Stream_, + _Prefix_, + _Lines_) @anchor print_message_lines Print a message (see [print_message/2](@ref print_message)) that has been translated to a list of message elements. The elements of this list are:
    • `\`-`\` Where _Format_ is an atom and _Args_ is a list of format argument. Handed to `format/3`.
    • `flush` If this appears as the last element, _Stream_ is flushed (see `flush_output/1`) and no final newline is generated.
    • `at_same_line` If this appears as first element, no prefix is printed for the first line and the line-position is not forced to 0 (see `format/1`, `~N`).
    • `\` Handed to `format/3` as `format(Stream, Format, [])`.
    • nl A new line is started and if the message is not complete the _Prefix_ is printed too.
  • user:message_hook(+ _Term_, + _Kind_, + _Lines_) @anchor message_hook Hook predicate that may be define in the module `user` to intercept messages from [print_message/2](@ref print_message). _Term_ and _Kind_ are the same as passed to [print_message/2](@ref print_message). _Lines_ is a list of format statements as described with [print_message_lines/3](@ref print_message_lines). This predicate should be defined dynamic and multifile to allow other modules defining clauses for it too.
  • message_to_string(+ _Term_, - _String_) @anchor message_to_string Translates a message-term into a string object. Primarily intended for SWI-Prolog emulation.
@section Testing_Terms Predicates on terms
  • var( _T_) [ISO] @anchor var Succeeds if _T_ is currently a free variable, otherwise fails.
  • atom( _T_) [ISO] @anchor atom Succeeds if and only if _T_ is currently instantiated to an atom.
  • atomic(T) [ISO] @anchor atomic Checks whether _T_ is an atomic symbol (atom or number).
  • compound( _T_) [ISO] @anchor compound Checks whether _T_ is a compound term.
  • db_reference( _T_) @anchor db_reference1C Checks whether _T_ is a database reference.
  • float( _T_) [ISO] @anchor float Checks whether _T_ is a floating point number.
  • rational( _T_) @anchor rational Checks whether `T` is a rational number.
  • integer( _T_) [ISO] @anchor integer Succeeds if and only if _T_ is currently instantiated to an integer.
  • nonvar( _T_) [ISO] @anchor nonvar The opposite of `var( _T_)`.
  • number( _T_) [ISO] @anchor number Checks whether `T` is an integer, rational or a float.
  • primitive( _T_) @anchor primitive Checks whether _T_ is an atomic term or a database reference.
  • simple( _T_) @anchor simple Checks whether _T_ is unbound, an atom, or a number.
  • callable( _T_) [ISO] @anchor callable Checks whether _T_ is a callable term, that is, an atom or a compound term.
  • numbervars( _T_,+ _N1_,- _Nn_) @anchor numbervars Instantiates each variable in term _T_ to a term of the form: `'$VAR'( _I_)`, with _I_ increasing from _N1_ to _Nn_.
  • unnumbervars( _T_,+ _NT_) @anchor unnumbervars Replace every `'$VAR'( _I_)` by a free variable.
  • ground( _T_) [ISO] @anchor ground Succeeds if there are no free variables in the term _T_.
  • acyclic_term( _T_) [ISO] @anchor acyclic_term Succeeds if there are loops in the term _T_, that is, it is an infinite term.
  • arg(+ _N_,+ _T_, _A_) [ISO] @anchor arg Succeeds if the argument _N_ of the term _T_ unifies with _A_. The arguments are numbered from 1 to the arity of the term. The current version will generate an error if _T_ or _N_ are unbound, if _T_ is not a compound term, of if _N_ is not a positive integer. Note that previous versions of YAP would fail silently under these errors.
  • functor( _T_, _F_, _N_) [ISO] @anchor functor The top functor of term _T_ is named _F_ and has arity _N_. When _T_ is not instantiated, _F_ and _N_ must be. If _N_ is 0, _F_ must be an atomic symbol, which will be unified with _T_. If _N_ is not 0, then _F_ must be an atom and _T_ becomes instantiated to the most general term having functor _F_ and arity _N_. If _T_ is instantiated to a term then _F_ and _N_ are respectively unified with its top functor name and arity. In the current version of YAP the arity _N_ must be an integer. Previous versions allowed evaluable expressions, as long as the expression would evaluate to an integer. This feature is not available in the ISO Prolog standard.
  • _T_ =.. _L_ [ISO] @anchor qQdOdO The list _L_ is built with the functor and arguments of the term _T_. If _T_ is instantiated to a variable, then _L_ must be instantiated either to a list whose head is an atom, or to a list consisting of just a number.
  • _X_ = _Y_ [ISO] @anchor qQ Tries to unify terms _X_ and _Y_.
  • _X_ \\= _Y_ [ISO] @anchor bQqQ Succeeds if terms _X_ and _Y_ are not unifiable.
  • unify_with_occurs_check(?T1,?T2) [ISO] @anchor unify_with_occurs_check Obtain the most general unifier of terms _T1_ and _T2_, if there is one. This predicate implements the full unification algorithm. An example:n ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ unify_with_occurs_check(a(X,b,Z),a(X,A,f(B)). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ will succeed with the bindings `A = b` and `Z = f(B)`. On the other hand: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ unify_with_occurs_check(a(X,b,Z),a(X,A,f(Z)). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ would fail, because `Z` is not unifiable with `f(Z)`. Note that `(=)/2` would succeed for the previous examples, giving the following bindings `A = b` and `Z = f(Z)`.
  • copy_term(? _TI_,- _TF_) [ISO] @anchor copy_term Term _TF_ is a variant of the original term _TI_, such that for each variable _V_ in the term _TI_ there is a new variable _V'_ in term _TF_. Notice that:
    • suspended goals and attributes for attributed variables in _TI_ are also duplicated;
    • ground terms are shared between the new and the old term.
    If you do not want any sharing to occur please use [duplicate_term/2](@ref duplicate_term).
  • duplicate_term(? _TI_,- _TF_) @anchor duplicate_term Term _TF_ is a variant of the original term _TI_, such that for each variable _V_ in the term _TI_ there is a new variable _V'_ in term _TF_, and the two terms do not share any structure. All suspended goals and attributes for attributed variables in _TI_ are also duplicated. Also refer to [copy_term/2](@ref copy_term).
  • is_list(+ _List_) @anchor is_list True when _List_ is a proper list. That is, _List_ is bound to the empty list (nil) or a term with functor '.' and arity 2.
  • ? _Term1_ =@= ? _Term2_ @anchor qQaAqQ Same as [variant/2](@ref variant), succeeds if _Term1_ and _Term2_ are variant terms.
  • subsumes_term(? _Subsumer_, ? _Subsumed_) @anchor subsumes_term Succeed if _Submuser_ subsumes _Subsuned_ but does not bind any variable in _Subsumer_.
  • term_subsumer(? _T1_, ? _T2_, ? _Subsumer_) @anchor term_subsumer Succeed if _Subsumer_ unifies with the least general generalization over _T1_ and _T2_.
  • term_variables(? _Term_, - _Variables_) [ISO] @anchor term_variables Unify _Variables_ with the list of all variables of term _Term_. The variables occur in the order of their first appearance when traversing the term depth-first, left-to-right.
  • rational_term_to_tree(? _TI_,- _TF_) @anchor rational_term_to_tree The term _TF_ is a tree representation (without cycles) for the Prolog term _TI_. Loops are replaced by terms of the form `_LOOP_( _LevelsAbove_)` where _LevelsAbove_ is the size of the loop.
  • tree_to_rational_term(? _TI_,- _TF_) @anchor tree_to_rational_term Inverse of above. The term _TI_ is a tree representation (without cycles) for the Prolog term _TF_. Loops replace terms of the form `_LOOP_( _LevelsAbove_)` where _LevelsAbove_ is the size of the loop.
@section Predicates_on_Atoms Predicates on Atoms The following predicates are used to manipulate atoms:
  • name( _A_, _L_) @anchor name The predicate holds when at least one of the arguments is ground (otherwise, an error message will be displayed). The argument _A_ will be unified with an atomic symbol and _L_ with the list of the ASCII codes for the characters of the external representation of _A_. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ name(yap,L). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ will return: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ L = [121,97,112]. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ and ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ name(3,L). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ will return: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ L = [51]. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  • atom_chars(? _A_,? _L_) [ISO] @anchor atom_chars The predicate holds when at least one of the arguments is ground (otherwise, an error message will be displayed). The argument _A_ must be unifiable with an atom, and the argument _L_ with the list of the characters of _A_.
  • atom_codes(? _A_,? _L_) [ISO] @anchor atom_codes The predicate holds when at least one of the arguments is ground (otherwise, an error message will be displayed). The argument _A_ will be unified with an atom and _L_ with the list of the ASCII codes for the characters of the external representation of _A_.
  • atom_concat(+ _As_,? _A_) @anchor atom_concat The predicate holds when the first argument is a list of atoms, and the second unifies with the atom obtained by concatenating all the atoms in the first list.
  • atomic_concat(+ _As_,? _A_) @anchor atomic_concat The predicate holds when the first argument is a list of atomic terms, and the second unifies with the atom obtained by concatenating all the atomic terms in the first list. The first argument thus may contain atoms or numbers.
  • atomic_list_concat(+ _As_,? _A_) @anchor atomic_list_concat The predicate holds when the first argument is a list of atomic terms, and the second unifies with the atom obtained by concatenating all the atomic terms in the first list. The first argument thus may contain atoms or numbers.
  • atomic_list_concat(? _As_,+ _Separator_,? _A_) Creates an atom just like [atomic_list_concat/2](@ref atomic_list_concat), but inserts _Separator_ between each pair of atoms. For example: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ?- atomic_list_concat([gnu, gnat], ', ', A). A = 'gnu, gnat' ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ YAP emulates the SWI-Prolog version of this predicate that can also be used to split atoms by instantiating _Separator_ and _Atom_ as shown below. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ?- atomic_list_concat(L, -, 'gnu-gnat'). L = [gnu, gnat] ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  • atom_length(+ _A_,? _I_) [ISO] @anchor atom_length The predicate holds when the first argument is an atom, and the second unifies with the number of characters forming that atom.
  • atom_concat(? _A1_,? _A2_,? _A12_) [ISO] The predicate holds when the third argument unifies with an atom, and the first and second unify with atoms such that their representations concatenated are the representation for _A12_. If _A1_ and _A2_ are unbound, the built-in will find all the atoms that concatenated give _A12_.
  • number_chars(? _I_,? _L_) [ISO] @anchor number_chars The predicate holds when at least one of the arguments is ground (otherwise, an error message will be displayed). The argument _I_ must be unifiable with a number, and the argument _L_ with the list of the characters of the external representation of _I_.
  • number_codes(? _A_,? _L_) [ISO] @anchor number_codes The predicate holds when at least one of the arguments is ground (otherwise, an error message will be displayed). The argument _A_ will be unified with a number and _L_ with the list of the ASCII codes for the characters of the external representation of _A_.
  • atom_number(? _Atom_,? _Number_) @anchor atom_number The predicate holds when at least one of the arguments is ground (otherwise, an error message will be displayed). If the argument _Atom_ is an atom, _Number_ must be the number corresponding to the characters in _Atom_, otherwise the characters in _Atom_ must encode a number _Number_.
  • number_atom(? _I_,? _L_) @anchor number_atom The predicate holds when at least one of the arguments is ground (otherwise, an error message will be displayed). The argument _I_ must be unifiable with a number, and the argument _L_ must be unifiable with an atom representing the number.
  • sub_atom(+ _A_,? _Bef_, ? _Size_, ? _After_, ? _At_out_) [ISO] @anchor sub_atom True when _A_ and _At_out_ are atoms such that the name of _At_out_ has size _Size_ and is a sub-string of the name of _A_, such that _Bef_ is the number of characters before and _After_ the number of characters afterwards. Note that _A_ must always be known, but _At_out_ can be unbound when calling this built-in. If all the arguments for [sub_atom/5](@ref sub_atom) but _A_ are unbound, the built-in will backtrack through all possible sub-strings of _A_.
@section Predicates_on_Characters Predicates on Characters The following predicates are used to manipulate characters:
  • char_code(? _A_,? _I_) [ISO] @anchor char_code The built-in succeeds with _A_ bound to character represented as an atom, and _I_ bound to the character code represented as an integer. At least, one of either _A_ or _I_ must be bound before the call.
  • char_type(? _Char_, ? _Type_) @anchor char_type Tests or generates alternative _Types_ or _Chars_. The character-types are inspired by the standard `C` `\` primitives.
    • alnum _Char_ is a letter (upper- or lowercase) or digit.
    • alpha _Char_ is a letter (upper- or lowercase).
    • csym _Char_ is a letter (upper- or lowercase), digit or the underscore (_). These are valid C- and Prolog symbol characters.
    • csymf _Char_ is a letter (upper- or lowercase) or the underscore (_). These are valid first characters for C- and Prolog symbols
    • ascii _Char_ is a 7-bits ASCII character (0..127).
    • white _Char_ is a space or tab. E.i. white space inside a line.
    • cntrl _Char_ is an ASCII control-character (0..31).
    • digit _Char_ is a digit.
    • digit( _Weight_) _Char_ is a digit with value _Weight_. I.e. `char_type(X, digit(6))` yields `X = '6'`. Useful for parsing numbers.
    • xdigit( _Weight_) _Char_ is a hexa-decimal digit with value _Weight_. I.e. char_type(a, xdigit(X) yields X = '10'. Useful for parsing numbers.
    • graph _Char_ produces a visible mark on a page when printed. Note that the space is not included!
    • lower _Char_ is a lower-case letter.
    • lower(Upper) _Char_ is a lower-case version of _Upper_. Only true if _Char_ is lowercase and _Upper_ uppercase.
    • to_lower(Upper) _Char_ is a lower-case version of Upper. For non-letters, or letter without case, _Char_ and Lower are the same. See also upcase_atom/2 and downcase_atom/2.
    • upper _Char_ is an upper-case letter.
    • upper(Lower) _Char_ is an upper-case version of Lower. Only true if _Char_ is uppercase and Lower lowercase.
    • to_upper(Lower) _Char_ is an upper-case version of Lower. For non-letters, or letter without case, _Char_ and Lower are the same. See also upcase_atom/2 and downcase_atom/2.
    • punct _Char_ is a punctuation character. This is a graph character that is not a letter or digit.
    • space _Char_ is some form of layout character (tab, vertical-tab, newline, etc.).
    • end_of_file _Char_ is -1.
    • end_of_line _Char_ ends a line (ASCII: 10..13).
    • newline _Char_ is a the newline character (10).
    • period _Char_ counts as the end of a sentence (.,!,?).
    • quote _Char_ is a quote-character (", ', `).
    • paren(Close) _Char_ is an open-parenthesis and Close is the corresponding close-parenthesis.
  • code_type(? _Code_, ? _Type_) @anchor code_type As [char_type/2](@ref char_type), but uses character-codes rather than one-character atoms. Please note that both predicates are as flexible as possible. They handle either representation if the argument is instantiated and only will instantiate with an integer code or one-character atom depending of the version used. See also the prolog-flag [double_quotes](@ref double_quotes) and the built-in predicates [atom_chars/2](@ref atom_chars) and [atom_codes/2](@ref atom_codes).
@section Comparing_Terms Comparing Terms The following predicates are used to compare and order terms, using the standard ordering:
  • variables come before numbers, numbers come before atoms which in turn come before compound terms, i.e.: variables @\< numbers @\< atoms @\< compound terms.
  • Variables are roughly ordered by "age" (the "oldest" variable is put first);
  • Floating point numbers are sorted in increasing order;
  • Rational numbers are sorted in increasing order;
  • Integers are sorted in increasing order;
  • Atoms are sorted in lexicographic order;
  • Compound terms are ordered first by arity of the main functor, then by the name of the main functor, and finally by their arguments in left-to-right order.
  • compare( _C_, _X_, _Y_) [ISO] @anchor compare As a result of comparing _X_ and _Y_, _C_ may take one of the following values:
    • `=` if _X_ and _Y_ are identical;
    • `\<` if _X_ precedes _Y_ in the defined order;
    • `\>` if _Y_ precedes _X_ in the defined order;
  • _X_ == _Y_ [ISO] @anchor qQqQ Succeeds if terms _X_ and _Y_ are strictly identical. The difference between this predicate and [=/2](@ref qQ) is that, if one of the arguments is a free variable, it only succeeds when they have already been unified. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ?- X == Y. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ fails, but, ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ?- X = Y, X == Y. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ succeeds. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ?- X == 2. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ fails, but, ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ?- X = 2, X == 2. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ succeeds.
  • _X_ \\== _Y_ [ISO] @anchor bQqQqQ Terms _X_ and _Y_ are not strictly identical.
  • _X_ @\< _Y_ [ISO] @anchor aAaAsS Term _X_ precedes term _Y_ in the standard order.
  • _X_ @=\< _Y_ [ISO] @anchor aAaAqQsS Term _X_ does not follow term _Y_ in the standard order.
  • _X_ @\> _Y_ [ISO] @anchor aAaAgG Term _X_ follows term _Y_ in the standard order.
  • _X_ @\>= _Y_ [ISO] @anchor aAaAgGqQ Term _X_ does not precede term _Y_ in the standard order.
  • sort(+ _L_,- _S_) [ISO] @anchor sort Unifies _S_ with the list obtained by sorting _L_ and merging identical (in the sense of `==`) elements.
  • keysort(+ _L_, _S_) [ISO] @anchor keysort Assuming L is a list of the form ` _Key_- _Value_`, `keysort(+ _L_, _S_)` unifies _S_ with the list obtained from _L_, by sorting its elements according to the value of _Key_. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ?- keysort([3-a,1-b,2-c,1-a,1-b],S). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ would return: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ S = [1-b,1-a,1-b,2-c,3-a] ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  • predsort(+ _Pred_, + _List_, - _Sorted_) @anchor predsort Sorts similar to sort/2, but determines the order of two terms by calling _Pred_(- _Delta_, + _E1_, + _E2_) . This call must unify _Delta_ with one of `\<`, `\>` or `=`. If built-in predicate compare/3 is used, the result is the same as sort/2.
  • length(? _L_,? _S_) @anchor length Unify the well-defined list _L_ with its length. The procedure can be used to find the length of a pre-defined list, or to build a list of length _S_.
@section Arithmetic Arithmetic @copydoc arithmetic * See @ref arithmetic_preds for the predicates that implement arithment * See @ref arithmetic_cmps for the arithmetic comparisons supported in YAP * See @ref arithmetic_operators for how to call arithmetic operations in YAP @section InputOutput Input/Output Predicates Some of the Input/Output predicates described below will in certain conditions provide error messages and abort only if the file_errors flag is set. If this flag is cleared the same predicates will just fail. Details on setting and clearing this flag are given under 7.7. @section Streams_and_Files Handling Streams and Files
  • open(+ _F_,+ _M_,- _S_) [ISO] @anchor open Opens the file with name _F_ in mode _M_ ('read', 'write' or 'append'), returning _S_ unified with the stream name. At most, there are 17 streams opened at the same time. Each stream is either an input or an output stream but not both. There are always 3 open streams: [user_input](@ref user_input) for reading, [user_output](@ref user_output) for writing and [user_error](@ref user_error) for writing. If there is no ambiguity, the atoms [user_input](@ref user_input) and [user_output](@ref user_output) may be referred to as `user`. The `file_errors` flag controls whether errors are reported when in mode 'read' or 'append' the file _F_ does not exist or is not readable, and whether in mode 'write' or 'append' the file is not writable.
  • open(+ _F_,+ _M_,- _S_,+ _Opts_) [ISO] Opens the file with name _F_ in mode _M_ ('read', 'write' or 'append'), returning _S_ unified with the stream name, and following these options:
    • type(+ _T_) [ISO] Specify whether the stream is a `text` stream (default), or a `binary` stream.
    • reposition(+ _Bool_) [ISO] Specify whether it is possible to reposition the stream (`true`), or not (`false`). By default, YAP enables repositioning for all files, except terminal files and sockets.
    • eof_action(+ _Action_) [ISO] Specify the action to take if attempting to input characters from a stream where we have previously found an `end_of_file`. The possible actions are `error`, that raises an error, `reset`, that tries to reset the stream and is used for `tty` type files, and `eof_code`, which generates a new `end_of_file` (default for non-tty files).
    • alias(+ _Name_) [ISO] Specify an alias to the stream. The alias Name must be an atom. The alias can be used instead of the stream descriptor for every operation concerning the stream. The operation will fail and give an error if the alias name is already in use. YAP allows several aliases for the same file, but only one is returned by [stream_property/2](@ref stream_property)
    • bom(+ _Bool_) If present and `true`, a BOM (Byte Order Mark) was detected while opening the file for reading or a BOM was written while opening the stream. See [BOM](@ref BOM) for details.
    • encoding(+ _Encoding_) Set the encoding used for text. See [Encoding](@ref Encoding) for an overview of wide character and encoding issues.
    • representation_errors(+ _Mode_) Change the behaviour when writing characters to the stream that cannot be represented by the encoding. The behaviour is one of `error` (throw and Input/Output error exception), `prolog` (write `\\u...\\` escape code or `xml` (write `\&#...;` XML character entity). The initial mode is `prolog` for the user streams and `error` for all other streams. See also [Encoding](@ref Encoding).
    • expand_filename(+ _Mode_) If _Mode_ is `true` then do filename expansion, then ask Prolog to do file name expansion before actually trying to opening the file: this includes processing `~` characters and processing `$` environment variables at the beginning of the file. Otherwise, just try to open the file using the given name. The default behavior is given by the Prolog flag [open_expands_filename](@ref open_expands_filename).
  • close(+ _S_) [ISO] @anchor close Closes the stream _S_. If _S_ does not stand for a stream currently opened an error is reported. The streams [user_input](@ref user_input), [user_output](@ref user_output), and [user_error](@ref user_error) can never be closed.
  • close(+ _S_,+ _O_) [ISO] Closes the stream _S_, following options _O_. The only valid options are `force(true)` and `force(false)`. YAP currently ignores these options.
  • time_file(+ _File_,- _Time_) @anchor time_file Unify the last modification time of _File_ with _Time_. _Time_ is a floating point number expressing the seconds elapsed since Jan 1, 1970.
  • access_file(+ _F_,+ _M_) @anchor access_file Is the file accessible?
  • file_base_name(+ _Name_,- _FileName_) @anchor file_base_name Give the path a full path _FullPath_ extract the _FileName_.
  • file_name_extension(? _Base_,? _Extension_, ? _Name_) @anchor file_name_extension This predicate is used to add, remove or test filename extensions. The main reason for its introduction is to deal with different filename properties in a portable manner. If the file system is case-insensitive, testing for an extension will be done case-insensitive too. _Extension_ may be specified with or without a leading dot (.). If an _Extension_ is generated, it will not have a leading dot.
  • current_stream( _F_, _M_, _S_) @anchor current_stream Defines the relation: The stream _S_ is opened on the file _F_ in mode _M_. It might be used to obtain all open streams (by backtracking) or to access the stream for a file _F_ in mode _M_, or to find properties for a stream _S_. Notice that some streams might not be associated to a file: in this case YAP tries to return the file number. If that is not available, YAP unifies _F_ with _S_.
  • is_stream( _S_) @anchor is_stream Succeeds if _S_ is a currently open stream.
  • flush_output [ISO] @anchor flush_output Send out all data in the output buffer of the current output stream.
  • flush_output(+ _S_) [ISO] Send all data in the output buffer for stream _S_.
  • set_input(+ _S_) [ISO] @anchor set_input Set stream _S_ as the current input stream. Predicates like [read/1](@ref read) and [get/1](@ref get) will start using stream _S_.
  • set_output(+ _S_) [ISO] @anchor set_output Set stream _S_ as the current output stream. Predicates like [write/1](@ref write) and [put/1](@ref put) will start using stream _S_.
  • stream_select(+ _STREAMS_,+ _TIMEOUT_,- _READSTREAMS_) @anchor stream_select Given a list of open _STREAMS_ opened in read mode and a _TIMEOUT_ return a list of streams who are now available for reading. If the _TIMEOUT_ is instantiated to `off`, [stream_select/3](@ref stream_select) will wait indefinitely for a stream to become open. Otherwise the timeout must be of the form `SECS:USECS` where `SECS` is an integer gives the number of seconds to wait for a timeout and `USECS` adds the number of micro-seconds. This built-in is only defined if the system call `select` is available in the system.
  • current_input(- _S_) [ISO] @anchor current_input Unify _S_ with the current input stream.
  • current_output(- _S_) [ISO] @anchor current_output Unify _S_ with the current output stream.
  • at_end_of_stream [ISO] @anchor at_end_of_stream Succeed if the current stream has stream position end-of-stream or past-end-of-stream.
  • at_end_of_stream(+ _S_) [ISO] Succeed if the stream _S_ has stream position end-of-stream or past-end-of-stream. Note that _S_ must be a readable stream.
  • set_stream_position(+ _S_, + _POS_) [ISO] @anchor set_stream_position Given a stream position _POS_ for a stream _S_, set the current stream position for _S_ to be _POS_.
  • stream_property(? _Stream_,? _Prop_) [ISO] @anchor stream_property Obtain the properties for the open streams. If the first argument is unbound, the procedure will backtrack through all open streams. Otherwise, the first argument must be a stream term (you may use `current_stream` to obtain a current stream given a file name). The following properties are recognized:
    • file_name( _P_) An atom giving the file name for the current stream. The file names are [user_input](@ref user_input), [user_output](@ref user_output), and [user_error](@ref user_error) for the standard streams.
    • mode( _P_) The mode used to open the file. It may be one of `append`, `read`, or `write`.
    • input The stream is readable.
    • output The stream is writable.
    • alias( _A_) ISO-Prolog primitive for stream aliases. YAP returns one of the existing aliases for the stream.
    • position( _P_) A term describing the position in the stream.
    • end_of_stream( _E_) Whether the stream is `at` the end of stream, or it has found the end of stream and is `past`, or whether it has `not` yet reached the end of stream.
    • eof_action( _A_) The action to take when trying to read after reaching the end of stream. The action may be one of `error`, generate an error, `eof_code`, return character code `-1`, or `reset` the stream.
    • reposition( _B_) Whether the stream can be repositioned or not, that is, whether it is seekable.
    • type( _T_) Whether the stream is a `text` stream or a `binary` stream.
    • bom(+ _Bool_) If present and `true`, a BOM (Byte Order Mark) was detected while opening the file for reading or a BOM was written while opening the stream. See [BOM](@ref BOM) for details.
    • encoding(+ _Encoding_) Query the encoding used for text. See [Encoding](@ref Encoding) for an overview of wide character and encoding issues in YAP.
    • representation_errors(+ _Mode_) Behaviour when writing characters to the stream that cannot be represented by the encoding. The behaviour is one of `error` (throw and Input/Output error exception), `prolog` (write `\\u...\\` escape code or `xml` (write `\&#...;` XML character entity). The initial mode is `prolog` for the user streams and `error` for all other streams. See also [Encoding](@ref Encoding) and `open/4`.
  • current_line_number(- _LineNumber_) @anchor current_line_number Unify _LineNumber_ with the line number for the current stream.
  • current_line_number(+ _Stream_,- _LineNumber_) Unify _LineNumber_ with the line number for the _Stream_.
  • line_count(+ _Stream_,- _LineNumber_) @anchor line_count Unify _LineNumber_ with the line number for the _Stream_.
  • character_count(+ _Stream_,- _CharacterCount_) @anchor character_count Unify _CharacterCount_ with the number of characters written to or read to _Stream_.
  • line_position(+ _Stream_,- _LinePosition_) @anchor line_position Unify _LinePosition_ with the position on current text stream _Stream_.
  • stream_position(+ _Stream_,- _StreamPosition_) @anchor stream_position Unify _StreamPosition_ with the packaged information of position on current stream _Stream_. Use [stream_position_data/3](@ref stream_position_data) to retrieve information on character or line count.
  • stream_position_data(+ _Field_,+ _StreamPosition_,- _Info_) @anchor stream_position_data Given the packaged stream position term _StreamPosition_, unify _Info_ with _Field_ `line_count`, `byte_count`, or `char_count`.
@section ChYProlog_File_Handling C-Prolog File Handling
  • tell(+ _S_) @anchor tell If _S_ is a currently opened stream for output, it becomes the current output stream. If _S_ is an atom it is taken to be a filename. If there is no output stream currently associated with it, then it is opened for output, and the new output stream created becomes the current output stream. If it is not possible to open the file, an error occurs. If there is a single opened output stream currently associated with the file, then it becomes the current output stream; if there are more than one in that condition, one of them is chosen. Whenever _S_ is a stream not currently opened for output, an error may be reported, depending on the state of the file_errors flag. The predicate just fails, if _S_ is neither a stream nor an atom.
  • telling(- _S_) @anchor telling The current output stream is unified with _S_.
  • told @anchor told Closes the current output stream, and the user's terminal becomes again the current output stream. It is important to remember to close streams after having finished using them, as the maximum number of simultaneously opened streams is 17.
  • see(+ _S_) @anchor see If _S_ is a currently opened input stream then it is assumed to be the current input stream. If _S_ is an atom it is taken as a filename. If there is no input stream currently associated with it, then it is opened for input, and the new input stream thus created becomes the current input stream. If it is not possible to open the file, an error occurs. If there is a single opened input stream currently associated with the file, it becomes the current input stream; if there are more than one in that condition, then one of them is chosen. When _S_ is a stream not currently opened for input, an error may be reported, depending on the state of the `file_errors` flag. If _S_ is neither a stream nor an atom the predicates just fails.
  • seeing(- _S_) @anchor seeing The current input stream is unified with _S_.
  • seen @anchor seen Closes the current input stream (see 6.7.).
@section InputOutput_of_Terms Handling Input/Output of Terms
  • read(- _T_) [ISO] @anchor read Reads the next term from the current input stream, and unifies it with _T_. The term must be followed by a dot ('.') and any blank-character as previously defined. The syntax of the term must match the current declarations for operators (see op). If the end-of-stream is reached, _T_ is unified with the atom `end_of_file`. Further reads from of the same stream may cause an error failure (see [open/3](@ref open)).
  • read_term(- _T_,+ _Options_) [ISO] @anchor read_term Reads term _T_ from the current input stream with execution controlled by the following options:
    • term_position(- _Position_) @anchor term_position Unify _Position_ with a term describing the position of the stream at the start of parse. Use [stream_position_data/3](@ref stream_position_data) to obtain extra information.
    • singletons(- _Names_) @anchor singletons Unify _Names_ with a list of the form _Name=Var_, where _Name_ is the name of a non-anonymous singleton variable in the original term, and `Var` is the variable's representation in YAP. The variables occur in left-to-right traversal order.
    • syntax_errors(+ _Val_) @anchor syntax_errors Control action to be taken after syntax errors. See [yap_flag/2](@ref yap_flag) for detailed information.
    • variable_names(- _Names_) @anchor variable_names Unify _Names_ with a list of the form _Name=Var_, where _Name_ is the name of a non-anonymous variable in the original term, and _Var_ is the variable's representation in YAP. The variables occur in left-to-right traversal order.
    • variables(- _Names_) @anchor variables Unify _Names_ with a list of the variables in term _T_. The variables occur in left-to-right traversal order.
  • char_conversion(+ _IN_,+ _OUT_) [ISO] @anchor char_conversion While reading terms convert unquoted occurrences of the character _IN_ to the character _OUT_. Both _IN_ and _OUT_ must be bound to single characters atoms. Character conversion only works if the flag `char_conversion` is on. This is default in the `iso` and `sicstus` language modes. As an example, character conversion can be used for instance to convert characters from the ISO-LATIN-1 character set to ASCII. If _IN_ is the same character as _OUT_, [char_conversion/2](@ref char_conversion) will remove this conversion from the table.
  • current_char_conversion(? _IN_,? _OUT_) [ISO] @anchor current_char_conversion If _IN_ is unbound give all current character translations. Otherwise, give the translation for _IN_, if one exists.
  • write( _T_) [ISO] @anchor write The term _T_ is written to the current output stream according to the operator declarations in force.
  • writeln( _T_) [ISO] @anchor writeln Same as [write/1](@ref write) followed by [nl/0](@ref nl).
  • display(+ _T_) @anchor display Displays term _T_ on the current output stream. All Prolog terms are written in standard parenthesized prefix notation.
  • write_canonical(+ _T_) [ISO] @anchor write_canonical Displays term _T_ on the current output stream. Atoms are quoted when necessary, and operators are ignored, that is, the term is written in standard parenthesized prefix notation.
  • write_term(+ _T_, + _Opts_) [ISO] @anchor write_term Displays term _T_ on the current output stream, according to the following options:
    • quoted(+ _Bool_) [ISO] If `true`, quote atoms if this would be necessary for the atom to be recognized as an atom by YAP's parser. The default value is `false`.
    • ignore_ops(+ _Bool_) [ISO] If `true`, ignore operator declarations when writing the term. The default value is `false`.
    • numbervars(+ _Bool_) [ISO] If `true`, output terms of the form `'$VAR'(N)`, where _N_ is an integer, as a sequence of capital letters. The default value is `false`.
    • portrayed(+ _Bool_) If `true`, use portray/1 to portray bound terms. The default value is `false`.
    • portray(+ _Bool_) If `true`, use portray/1 to portray bound terms. The default value is `false`.
    • max_depth(+ _Depth_) If `Depth` is a positive integer, use Depth as the maximum depth to portray a term. The default is `0`, that is, unlimited depth.
    • priority(+ _Piority_) If `Priority` is a positive integer smaller than `1200`, give the context priority. The default is `1200`.
    • cycles(+ _Bool_) Do not loop in rational trees (default).
  • writeq( _T_) [ISO] @anchor writeq Writes the term _T_, quoting names to make the result acceptable to the predicate 'read' whenever necessary.
  • print( _T_) @anchor print Prints the term _T_ to the current output stream using [write/1](@ref write) unless T is bound and a call to the user-defined predicate `portray/1` succeeds. To do pretty printing of terms the user should define suitable clauses for `portray/1` and use [print/1](@ref print).
  • format(+ _T_,+ _L_) @anchor format Print formatted output to the current output stream. The arguments in list _L_ are output according to the string or atom _T_. A control sequence is introduced by a `w`. The following control sequences are available in YAP:
    • '~~' Print a single tilde.
    • '~a' The next argument must be an atom, that will be printed as if by `write`.
    • '~Nc' The next argument must be an integer, that will be printed as a character code. The number _N_ is the number of times to print the character (default 1).
    • '~Ne'
    • '~NE'
    • '~Nf'
    • '~Ng'
    • '~NG' The next argument must be a floating point number. The float _F_, the number _N_ and the control code `c` will be passed to `printf` as: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ printf("%s.Nc", F) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ As an example: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ?- format("~8e, ~8E, ~8f, ~8g, ~8G~w", [3.14,3.14,3.14,3.14,3.14,3.14]). 3.140000e+00, 3.140000E+00, 3.140000, 3.14, 3.143.14 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
    • '~Nd' The next argument must be an integer, and _N_ is the number of digits after the decimal point. If _N_ is `0` no decimal points will be printed. The default is _N = 0_. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ?- format("~2d, ~d",[15000, 15000]). 150.00, 15000 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
    • '~ND' Identical to `'~Nd'`, except that commas are used to separate groups of three digits. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ?- format("~2D, ~D",[150000, 150000]). 1,500.00, 150,000 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
    • '~i' Ignore the next argument in the list of arguments: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ?- format('The ~i met the boregrove',[mimsy]). The met the boregrove ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
    • '~k' Print the next argument with `write_canonical`: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ?- format("Good night ~k",a+[1,2]). Good night +(a,[1,2]) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
    • '~Nn' Print _N_ newlines (where _N_ defaults to 1).
    • '~NN' Print _N_ newlines if at the beginning of the line (where _N_ defaults to 1).
    • '~Nr' The next argument must be an integer, and _N_ is interpreted as a radix, such that `2 \<= N \<= 36` (the default is 8). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ?- format("~2r, 0x~16r, ~r", [150000, 150000, 150000]). 100100100111110000, 0x249f0, 444760 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Note that the letters `a-z` denote digits larger than 9.
    • '~NR' Similar to '~NR'. The next argument must be an integer, and _N_ is interpreted as a radix, such that `2 \<= N \<= 36` (the default is 8). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ?- format("~2r, 0x~16r, ~r", [150000, 150000, 150000]). 100100100111110000, 0x249F0, 444760 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ The only difference is that letters `A-Z` denote digits larger than 9.
    • '~p' Print the next argument with [print/1](@ref print): ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ?- format("Good night ~p",a+[1,2]). Good night a+[1,2] ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
    • '~q' Print the next argument with [writeq/1](@ref writeq): ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ?- format("Good night ~q",'Hello'+[1,2]). Good night 'Hello'+[1,2] ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
    • '~Ns' The next argument must be a list of character codes. The system then outputs their representation as a string, where _N_ is the maximum number of characters for the string ( _N_ defaults to the length of the string). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ?- format("The ~s are ~4s",["woods","lovely"]). The woods are love ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
    • '~w' Print the next argument with [write/1](@ref write): ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ?- format("Good night ~w",'Hello'+[1,2]). Good night Hello+[1,2] ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
    The number of arguments, `N`, may be given as an integer, or it may be given as an extra argument. The next example shows a small procedure to write a variable number of `a` characters: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ write_many_as(N) :- format("~*c",[N,0'a]). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ The [format/2](@ref format) built-in also allows for formatted output. One can specify column boundaries and fill the intermediate space by a padding character:
    • '~N|' Set a column boundary at position _N_, where _N_ defaults to the current position.
    • '~N+' Set a column boundary at _N_ characters past the current position, where _N_ defaults to `8`.
    • '~Nt' Set padding for a column, where _N_ is the fill code (default is `SPC`).
    The next example shows how to align columns and padding. We first show left-alignment: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ?- format("~n*Hello~16+*~n",[]). *Hello * ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Note that we reserve 16 characters for the column. The following example shows how to do right-alignment: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ?- format("*~tHello~16+*~n",[]). * Hello* ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ The `~t` escape sequence forces filling before `Hello`. We next show how to do centering: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ?- format("*~tHello~t~16+*~n",[]). * Hello * ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ The two `~t` escape sequence force filling both before and after `Hello`. Space is then evenly divided between the right and the left sides.
  • format(+ _T_) Print formatted output to the current output stream.
  • format(+ _S_,+ _T_,+ _L_) Print formatted output to stream _S_.
  • with_output_to(+ _Ouput_,: _Goal_) @anchor with_output_to Run _Goal_ as [once/1](@ref once), while characters written to the current output are sent to _Output_. The predicate is SWI-Prolog specific. Applications should generally avoid creating atoms by breaking and concatenating other atoms as the creation of large numbers of intermediate atoms generally leads to poor performance, even more so in multi-threaded applications. This predicate supports creating difference-lists from character data efficiently. The example below defines the DCG rule `term/3` to insert a term in the output: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ term(Term, In, Tail) :- with_output_to(codes(In, Tail), write(Term)). ?- phrase(term(hello), X). X = [104, 101, 108, 108, 111] ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
    • A Stream handle or alias Temporary switch current output to the given stream. Redirection using with_output_to/2 guarantees the original output is restored, also if Goal fails or raises an exception. See also call_cleanup/2.
    • atom(- _Atom_) Create an atom from the emitted characters. Please note the remark above.
    • string(- _String_) Create a string-object (not supported in YAP).
    • codes(- _Codes_) Create a list of character codes from the emitted characters, similar to atom_codes/2.
    • codes(- _Codes_, - _Tail_) Create a list of character codes as a difference-list.
    • chars(- _Chars_) Create a list of one-character-atoms codes from the emitted characters, similar to atom_chars/2.
    • chars(- _Chars_, - _Tail_) Create a list of one-character-atoms as a difference-list.
@section InputOutput_of_Characters Handling Input/Output of Characters
  • put(+ _N_) @anchor put Outputs to the current output stream the character whose ASCII code is _N_. The character _N_ must be a legal ASCII character code, an expression yielding such a code, or a list in which case only the first element is used.
  • put_byte(+ _N_) [ISO] @anchor put_byte Outputs to the current output stream the character whose code is _N_. The current output stream must be a binary stream.
  • put_char(+ _N_) [ISO] @anchor put_char Outputs to the current output stream the character who is used to build the representation of atom `A`. The current output stream must be a text stream.
  • put_code(+ _N_) [ISO] @anchor put_code Outputs to the current output stream the character whose ASCII code is _N_. The current output stream must be a text stream. The character _N_ must be a legal ASCII character code, an expression yielding such a code, or a list in which case only the first element is used.
  • get(- _C_) @anchor get The next non-blank character from the current input stream is unified with _C_. Blank characters are the ones whose ASCII codes are not greater than 32. If there are no more non-blank characters in the stream, _C_ is unified with -1. If `end_of_stream` has already been reached in the previous reading, this call will give an error message.
  • get0(- _C_) @anchor get0 The next character from the current input stream is consumed, and then unified with _C_. There are no restrictions on the possible values of the ASCII code for the character, but the character will be internally converted by YAP.
  • get_byte(- _C_) [ISO] @anchor get_byte If _C_ is unbound, or is a character code, and the current stream is a binary stream, read the next byte from the current stream and unify its code with _C_.
  • get_char(- _C_) [ISO] @anchor get_char If _C_ is unbound, or is an atom representation of a character, and the current stream is a text stream, read the next character from the current stream and unify its atom representation with _C_.
  • get_code(- _C_) [ISO] @anchor get_code If _C_ is unbound, or is the code for a character, and the current stream is a text stream, read the next character from the current stream and unify its code with _C_.
  • peek_byte(- _C_) [ISO] @anchor peek_byte If _C_ is unbound, or is a character code, and the current stream is a binary stream, read the next byte from the current stream and unify its code with _C_, while leaving the current stream position unaltered.
  • peek_char(- _C_) [ISO] @anchor peek_char If _C_ is unbound, or is an atom representation of a character, and the current stream is a text stream, read the next character from the current stream and unify its atom representation with _C_, while leaving the current stream position unaltered.
  • peek_code(- _C_) [ISO] @anchor peek_code If _C_ is unbound, or is the code for a character, and the current stream is a text stream, read the next character from the current stream and unify its code with _C_, while leaving the current stream position unaltered.
  • skip(+ _N_) @anchor skip Skips input characters until the next occurrence of the character with ASCII code _N_. The argument to this predicate can take the same forms as those for `put` (see 6.11).
  • tab(+ _N_) @anchor tab Outputs _N_ spaces to the current output stream.
  • nl [ISO] @anchor nl Outputs a new line to the current output stream.
@section InputOutput_for_Streams Input/Output Predicates applied to Streams
  • read(+ _S_,- _T_) [ISO] Reads term _T_ from the stream _S_ instead of from the current input stream.
  • read_term(+ _S_,- _T_,+ _Options_) [ISO] Reads term _T_ from stream _S_ with execution controlled by the same options as [read_term/2](@ref read_term).
  • write(+ _S_, _T_) [ISO] Writes term _T_ to stream _S_ instead of to the current output stream.
  • write_canonical(+ _S_,+ _T_) [ISO] Displays term _T_ on the stream _S_. Atoms are quoted when necessary, and operators are ignored.
  • write_term(+ _S_, + _T_, + _Opts_) [ISO] Displays term _T_ on the current output stream, according to the same options used by `write_term/3`.
  • writeq(+ _S_, _T_) [ISO] As [writeq/1](@ref writeq), but the output is sent to the stream _S_.
  • display(+ _S_, _T_) Like [display/1](@ref display), but using stream _S_ to display the term.
  • print(+ _S_, _T_) Prints term _T_ to the stream _S_ instead of to the current output stream.
  • put(+ _S_,+ _N_) As `put(N)`, but to stream _S_.
  • put_byte(+ _S_,+ _N_) [ISO] As `put_byte(N)`, but to binary stream _S_.
  • put_char(+ _S_,+ _A_) [ISO] As `put_char(A)`, but to text stream _S_.
  • put_code(+ _S_,+ _N_) [ISO] As `put_code(N)`, but to text stream _S_.
  • get(+ _S_,- _C_) The same as `get(C)`, but from stream _S_.
  • get0(+ _S_,- _C_) The same as `get0(C)`, but from stream _S_.
  • get_byte(+ _S_,- _C_) [ISO] If _C_ is unbound, or is a character code, and the stream _S_ is a binary stream, read the next byte from that stream and unify its code with _C_.
  • get_char(+ _S_,- _C_) [ISO] If _C_ is unbound, or is an atom representation of a character, and the stream _S_ is a text stream, read the next character from that stream and unify its representation as an atom with _C_.
  • get_code(+ _S_,- _C_) [ISO] If _C_ is unbound, or is a character code, and the stream _S_ is a text stream, read the next character from that stream and unify its code with _C_.
  • peek_byte(+ _S_,- _C_) [ISO] If _C_ is unbound, or is a character code, and _S_ is a binary stream, read the next byte from the current stream and unify its code with _C_, while leaving the current stream position unaltered.
  • peek_char(+ _S_,- _C_) [ISO] If _C_ is unbound, or is an atom representation of a character, and the stream _S_ is a text stream, read the next character from that stream and unify its representation as an atom with _C_, while leaving the current stream position unaltered.
  • peek_code(+ _S_,- _C_) [ISO] If _C_ is unbound, or is an atom representation of a character, and the stream _S_ is a text stream, read the next character from that stream and unify its representation as an atom with _C_, while leaving the current stream position unaltered.
  • skip(+ _S_,- _C_) Like [skip/1](@ref skip), but using stream _S_ instead of the current input stream.
  • tab(+ _S_,+ _N_) The same as [tab/1](@ref tab), but using stream _S_.
  • nl(+ _S_) [ISO] Outputs a new line to stream _S_.
@section ChYProlog_to_Terminal Compatible C-Prolog predicates for Terminal Input/Output
  • ttyput(+ _N_) @anchor ttyput As `put(N)` but always to [user_output](@ref user_output).
  • ttyget(- _C_) @anchor ttyget The same as `get(C)`, but from stream [user_input](@ref user_input).
  • ttyget0(- _C_) @anchor ttyget0 The same as `get0(C)`, but from stream [user_input](@ref user_input).
  • ttyskip(- _C_) @anchor ttyskip Like [skip/1](@ref skip), but always using stream [user_input](@ref user_input). stream.
  • ttytab(+ _N_) @anchor ttytab The same as [tab/1](@ref tab), but using stream [user_output](@ref user_output).
  • ttynl @anchor ttynl Outputs a new line to stream [user_output](@ref user_output).
@section InputOutput_Control Controlling Input/Output
  • exists(+ _F_) @anchor exists Checks if file _F_ exists in the current directory.
  • nofileerrors @anchor nofileerrors Switches off the file_errors flag, so that the predicates [see/1](@ref see), [tell/1](@ref tell), [open/3](@ref open) and [close/1](@ref close) just fail, instead of producing an error message and aborting whenever the specified file cannot be opened or closed.
  • fileerrors @anchor fileerrors Switches on the file_errors flag so that in certain error conditions Input/Output predicates will produce an appropriated message and abort.
  • always_prompt_user @anchor always_prompt_user Force the system to prompt the user even if the [user_input](@ref user_input) stream is not a terminal. This command is useful if you want to obtain interactive control from a pipe or a socket.
@section Sockets Using Sockets From YAP YAP includes a SICStus Prolog compatible socket interface. In YAP-6.3 this uses the `clib` package to emulate the old low level interface that provides direct access to the major socket system calls. These calls can be used both to open a new connection in the network or connect to a networked server. Socket connections are described as read/write streams, and standard Input/Output built-ins can be used to write on or read from sockets. The following calls are available:
  • socket(+ _DOMAIN_,+ _TYPE_,+ _PROTOCOL_,- _SOCKET_) @anchor socket Corresponds to the BSD system call `socket`. Create a socket for domain _DOMAIN_ of type _TYPE_ and protocol _PROTOCOL_. Both _DOMAIN_ and _TYPE_ should be atoms, whereas _PROTOCOL_ must be an integer. The new socket object is accessible through a descriptor bound to the variable _SOCKET_. The current implementation of YAP accepts socket domains `'AF_INET'` and `'AF_UNIX'`. Socket types depend on the underlying operating system, but at least the following types are supported: `'SOCK_STREAM'` and `'SOCK_DGRAM'` (untested in 6.3).
  • socket(+ _DOMAIN_,- _SOCKET_) Call [socket/4](@ref socket) with _TYPE_ bound to `'SOCK_STREAM'` and _PROTOCOL_ bound to `0`.
  • socket_close(+ _SOCKET_) @anchor socket_close Close socket _SOCKET_. Note that sockets used in `socket_connect` (that is, client sockets) should not be closed with `socket_close`, as they will be automatically closed when the corresponding stream is closed with [close/1](@ref close) or `close/2`.
  • socket_bind(+ _SOCKET_, ? _PORT_) @anchor socket_bind Interface to system call `bind`, as used for servers: bind socket to a port. Port information depends on the domain:
    • 'AF_UNIX'(+ _FILENAME_) (unsupported)
    • 'AF_FILE'(+ _FILENAME_) use file name _FILENAME_ for UNIX or local sockets.
    • 'AF_INET'(? _HOST_,?PORT) If _HOST_ is bound to an atom, bind to host _HOST_, otherwise if unbound bind to local host ( _HOST_ remains unbound). If port _PORT_ is bound to an integer, try to bind to the corresponding port. If variable _PORT_ is unbound allow operating systems to choose a port number, which is unified with _PORT_.
  • socket_connect(+ _SOCKET_, + _PORT_, - _STREAM_) @anchor socket_connect Interface to system call `connect`, used for clients: connect socket _SOCKET_ to _PORT_. The connection results in the read/write stream _STREAM_. Port information depends on the domain:
    • 'AF_UNIX'(+ _FILENAME_)
    • 'AF_FILE'(+ _FILENAME_) connect to socket at file _FILENAME_.
    • 'AF_INET'(+ _HOST_,+ _PORT_) Connect to socket at host _HOST_ and port _PORT_.
  • socket_listen(+ _SOCKET_, + _LENGTH_) @anchor socket_listen Interface to system call `listen`, used for servers to indicate willingness to wait for connections at socket _SOCKET_. The integer _LENGTH_ gives the queue limit for incoming connections, and should be limited to `5` for portable applications. The socket must be of type `SOCK_STREAM` or `SOCK_SEQPACKET`.
  • socket_accept(+ _SOCKET_, - _CLIENT_, - _STREAM_) @anchor socket_accept Interface to system call `accept`, used for servers to wait for connections at socket _SOCKET_. The stream descriptor _STREAM_ represents the resulting connection. If the socket belongs to the domain `'AF_INET'`, _CLIENT_ unifies with an atom containing the IP address for the client in numbers and dots notation.
  • socket_accept(+ _SOCKET_, - _STREAM_) Accept a connection but do not return client information.
  • socket_buffering(+ _SOCKET_, - _MODE_, - _OLD_, + _NEW_) @anchor socket_buffering Set buffering for _SOCKET_ in `read` or `write` _MODE_. _OLD_ is unified with the previous status, and _NEW_ receives the new status which may be one of `unbuf` or `fullbuf`.
  • socket_select(+ _SOCKETS_, - _NEWSTREAMS_, + _TIMEOUT_, @anchor socket_select + _STREAMS_, - _READSTREAMS_) [unsupported in YAP-6.3] Interface to system call `select`, used for servers to wait for connection requests or for data at sockets. The variable _SOCKETS_ is a list of form _KEY-SOCKET_, where _KEY_ is an user-defined identifier and _SOCKET_ is a socket descriptor. The variable _TIMEOUT_ is either `off`, indicating execution will wait until something is available, or of the form _SEC-USEC_, where _SEC_ and _USEC_ give the seconds and microseconds before [socket_select/5](@ref socket_select) returns. The variable _SOCKETS_ is a list of form _KEY-STREAM_, where _KEY_ is an user-defined identifier and _STREAM_ is a stream descriptor Execution of [socket_select/5](@ref socket_select) unifies _READSTREAMS_ from _STREAMS_ with readable data, and _NEWSTREAMS_ with a list of the form _KEY-STREAM_, where _KEY_ was the key for a socket with pending data, and _STREAM_ the stream descriptor resulting from accepting the connection.
  • current_host(? _HOSTNAME_) @anchor current_host Unify _HOSTNAME_ with an atom representing the fully qualified hostname for the current host. Also succeeds if _HOSTNAME_ is bound to the unqualified hostname.
  • hostname_address(? _HOSTNAME_,? _IP_ADDRESS_) @anchor hostname_address _HOSTNAME_ is an host name and _IP_ADDRESS_ its IP address in number and dots notation.
@section Database Using the Clausal Data Base Predicates in YAP may be dynamic or static. By default, when consulting or reconsulting, predicates are assumed to be static: execution is faster and the code will probably use less space. Static predicates impose some restrictions: in general there can be no addition or removal of clauses for a procedure if it is being used in the current execution. Dynamic predicates allow programmers to change the Clausal Data Base with the same flexibility as in C-Prolog. With dynamic predicates it is always possible to add or remove clauses during execution and the semantics will be the same as for C-Prolog. But the programmer should be aware of the fact that asserting or retracting are still expensive operations, and therefore he should try to avoid them whenever possible.
  • dynamic + _P_ @anchor dynamic Declares predicate _P_ or list of predicates [ _P1_,..., _Pn_] as a dynamic predicate. _P_ must be written in form: _name/arity_. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ :- dynamic god/1. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ a more convenient form can be used: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ :- dynamic son/3, father/2, mother/2. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ or, equivalently, ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ :- dynamic [son/3, father/2, mother/2]. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Note: a predicate is assumed to be dynamic when asserted before being defined.
  • dynamic_predicate(+ _P_,+ _Semantics_) @anchor dynamic_predicate Declares predicate _P_ or list of predicates [ _P1_,..., _Pn_] as a dynamic predicate following either `logical` or `immediate` semantics.
  • compile_predicates(: _ListOfNameArity_) @anchor compile_predicates Compile a list of specified dynamic predicates (see [dynamic/1](@ref dynamic) and [assert/1](@ref assert) into normal static predicates. This call tells the Prolog environment the definition will not change anymore and further calls to [assert/1](@ref assert) or [retract/1](@ref retract) on the named predicates raise a permission error. This predicate is designed to deal with parts of the program that is generated at runtime but does not change during the remainder of the program execution.
@section Modifying_the_Database Modification of the Data Base These predicates can be used either for static or for dynamic predicates:
  • assert(+ _C_) @anchor assert Same as [assertz/1](@ref assertz). Adds clause _C_ to the program. If the predicate is undefined, declare it as dynamic. New code should use [assertz/1](@ref assertz) for better portability. Most Prolog systems only allow asserting clauses for dynamic predicates. This is also as specified in the ISO standard. YAP allows asserting clauses for static predicates, as long as the predicate is not in use and the language flag is cprolog. Note that this feature is deprecated, if you want to assert clauses for static procedures you should use [assert_static/1](@ref assert_static).
  • asserta(+ _C_) [ISO] @anchor asserta Adds clause _C_ to the beginning of the program. If the predicate is undefined, declare it as dynamic.
  • assertz(+ _C_) [ISO] @anchor assertz Adds clause _C_ to the end of the program. If the predicate is undefined, declare it as dynamic. Most Prolog systems only allow asserting clauses for dynamic predicates. This is also as specified in the ISO standard. YAP allows asserting clauses for static predicates. The current version of YAP supports this feature, but this feature is deprecated and support may go away in future versions.
  • abolish(+ _PredSpec_) [ISO] @anchor abolish Deletes the predicate given by _PredSpec_ from the database. If _PredSpec_ is an unbound variable, delete all predicates for the current module. The specification must include the name and arity, and it may include module information. Under iso language mode this built-in will only abolish dynamic procedures. Under other modes it will abolish any procedures.
  • abolish(+ _P_,+ _N_) Deletes the predicate with name _P_ and arity _N_. It will remove both static and dynamic predicates.
  • assert_static(: _C_) @anchor assert_static Adds clause _C_ to a static procedure. Asserting a static clause for a predicate while choice-points for the predicate are available has undefined results.
  • asserta_static(: _C_) @anchor asserta_static Adds clause _C_ to the beginning of a static procedure.
  • assertz_static(: _C_) @anchor assertz_static Adds clause _C_ to the end of a static procedure. Asserting a static clause for a predicate while choice-points for the predicate are available has undefined results.
The following predicates can be used for dynamic predicates and for static predicates, if source mode was on when they were compiled:
  • clause(+ _H_, _B_) [ISO] @anchor clause A clause whose head matches _H_ is searched for in the program. Its head and body are respectively unified with _H_ and _B_. If the clause is a unit clause, _B_ is unified with _true_. This predicate is applicable to static procedures compiled with `source` active, and to all dynamic procedures.
  • clause(+ _H_, _B_,- _R_) The same as [clause/2](@ref clause), plus _R_ is unified with the reference to the clause in the database. You can use [instance/2](@ref instance) to access the reference's value. Note that you may not use [erase/1](@ref erase) on the reference on static procedures.
  • nth_clause(+ _H_, _I_,- _R_) @anchor nth_clause Find the _I_th clause in the predicate defining _H_, and give a reference to the clause. Alternatively, if the reference _R_ is given the head _H_ is unified with a description of the predicate and _I_ is bound to its position.
The following predicates can only be used for dynamic predicates:
  • retract(+ _C_) [ISO] @anchor retract Erases the first clause in the program that matches _C_. This predicate may also be used for the static predicates that have been compiled when the source mode was `on`. For more information on [source/0](@ref source) ( (see [Setting the Compiler](@ref Setting_the_Compiler))).
  • retractall(+ _G_) [ISO] @anchor retractall Retract all the clauses whose head matches the goal _G_. Goal _G_ must be a call to a dynamic predicate.
@section Looking_at_the_Database Looking at the Data Base
  • listing @anchor listing Lists in the current output stream all the clauses for which source code is available (these include all clauses for dynamic predicates and clauses for static predicates compiled when source mode was `on`).
  • listing(+ _P_) Lists predicate _P_ if its source code is available.
  • portray_clause(+ _C_) @anchor portray_clause Write clause _C_ as if written by [listing/0](@ref listing).
  • portray_clause(+ _S_,+ _C_) Write clause _C_ on stream _S_ as if written by [listing/0](@ref listing).
  • current_atom( _A_) @anchor current_atom Checks whether _A_ is a currently defined atom. It is used to find all currently defined atoms by backtracking.
  • current_predicate( _F_) [ISO] @anchor current_predicate _F_ is the predicate indicator for a currently defined user or library predicate. _F_ is of the form _Na/Ar_, where the atom _Na_ is the name of the predicate, and _Ar_ its arity.
  • current_predicate( _A_, _P_) Defines the relation: _P_ is a currently defined predicate whose name is the atom _A_.
  • system_predicate( _A_, _P_) @anchor system_predicate Defines the relation: _P_ is a built-in predicate whose name is the atom _A_.
  • predicate_property( _P_, _Prop_) [ISO] @anchor predicate_property For the predicates obeying the specification _P_ unify _Prop_ with a property of _P_. These properties may be:
    • built_in @anchor built_in true for built-in predicates,
    • dynamic true if the predicate is dynamic
    • static @anchor static true if the predicate is static
    • meta_predicate( _M_) @anchor meta_predicate_flag true if the predicate has a meta_predicate declaration _M_.
    • multifile @anchor multifile_flag true if the predicate was declared to be multifile
    • imported_from( _Mod_) @anchor imported_from true if the predicate was imported from module _Mod_.
    • exported @anchor exported true if the predicate is exported in the current module.
    • public true if the predicate is public; note that all dynamic predicates are public.
    • tabled @anchor tabled true if the predicate is tabled; note that only static predicates can be tabled in YAP.
    • source (predicate_property flag) @anchor source_flag true if source for the predicate is available.
    • number_of_clauses( _ClauseCount_) @anchor number_of_clauses Number of clauses in the predicate definition. Always one if external or built-in.
  • predicate_statistics( _P_, _NCls_, _Sz_, _IndexSz_) @anchor predicate_statistics Given predicate _P_, _NCls_ is the number of clauses for _P_, _Sz_ is the amount of space taken to store those clauses (in bytes), and _IndexSz_ is the amount of space required to store indices to those clauses (in bytes).
  • predicate_erased_statistics( _P_, _NCls_, _Sz_, _IndexSz_) @anchor predicate_erased_statistics Given predicate _P_, _NCls_ is the number of erased clauses for _P_ that could not be discarded yet, _Sz_ is the amount of space taken to store those clauses (in bytes), and _IndexSz_ is the amount of space required to store indices to those clauses (in bytes).
@section Database_References Using Data Base References Data Base references are a fast way of accessing terms. The predicates [erase/1](@ref erase) and `instance/1` also apply to these references and may sometimes be used instead of [retract/1](@ref retract) and [clause/2](@ref clause).
  • assert(+ _C_,- _R_) The same as `assert(C)` ( (see [Modifying the Database](@ref Modifying_the_Database))) but unifies _R_ with the database reference that identifies the new clause, in a one-to-one way. Note that `asserta/2` only works for dynamic predicates. If the predicate is undefined, it will automatically be declared dynamic.
  • asserta(+ _C_,- _R_) The same as `asserta(C)` but unifying _R_ with the database reference that identifies the new clause, in a one-to-one way. Note that `asserta/2` only works for dynamic predicates. If the predicate is undefined, it will automatically be declared dynamic.
  • assertz(+ _C_,- _R_) The same as `assertz(C)` but unifying _R_ with the database reference that identifies the new clause, in a one-to-one way. Note that `asserta/2` only works for dynamic predicates. If the predicate is undefined, it will automatically be declared dynamic.
  • retract(+ _C_,- _R_) Erases from the program the clause _C_ whose database reference is _R_. The predicate must be dynamic.
@section Internal_Database Internal Data Base Some programs need global information for, e.g. counting or collecting data obtained by backtracking. As a rule, to keep this information, the internal data base should be used instead of asserting and retracting clauses (as most novice programmers do), . In YAP (as in some other Prolog systems) the internal data base (i.d.b. for short) is faster, needs less space and provides a better insulation of program and data than using asserted/retracted clauses. The i.d.b. is implemented as a set of terms, accessed by keys that unlikely what happens in (non-Prolog) data bases are not part of the term. Under each key a list of terms is kept. References are provided so that terms can be identified: each term in the i.d.b. has a unique reference (references are also available for clauses of dynamic predicates).
  • recorda(+ _K_, _T_,- _R_) @anchor recorda Makes term _T_ the first record under key _K_ and unifies _R_ with its reference.
  • recordz(+ _K_, _T_,- _R_) @anchor recordz Makes term _T_ the last record under key _K_ and unifies _R_ with its reference.
  • recorda_at(+ _R0_, _T_,- _R_) @anchor recorda_at Makes term _T_ the record preceding record with reference _R0_, and unifies _R_ with its reference.
  • recordz_at(+ _R0_, _T_,- _R_) @anchor recordz_at Makes term _T_ the record following record with reference _R0_, and unifies _R_ with its reference.
  • recordaifnot(+ _K_, _T_,- _R_) @anchor recordaifnot If a term equal to _T_ up to variable renaming is stored under key _K_ fail. Otherwise, make term _T_ the first record under key _K_ and unify _R_ with its reference.
  • recordzifnot(+ _K_, _T_,- _R_) @anchor recordzifnot If a term equal to _T_ up to variable renaming is stored under key _K_ fail. Otherwise, make term _T_ the first record under key _K_ and unify _R_ with its reference. This predicate is YAP specific.
  • recorded(+ _K_, _T_, _R_) @anchor recorded Searches in the internal database under the key _K_, a term that unifies with _T_ and whose reference matches _R_. This built-in may be used in one of two ways:
    • _K_ may be given, in this case the built-in will return all elements of the internal data-base that match the key.
    • _R_ may be given, if so returning the key and element that match the reference.
  • erase(+ _R_) @anchor erase The term referred to by _R_ is erased from the internal database. If reference _R_ does not exist in the database, `erase` just fails.
  • erased(+ _R_) @anchor erased Succeeds if the object whose database reference is _R_ has been erased.
  • instance(+ _R_,- _T_) @anchor instance If _R_ refers to a clause or a recorded term, _T_ is unified with its most general instance. If _R_ refers to an unit clause _C_, then _T_ is unified with ` _C_ :- true`. When _R_ is not a reference to an existing clause or to a recorded term, this goal fails.
  • eraseall(+ _K_) @anchor eraseall All terms belonging to the key `K` are erased from the internal database. The predicate always succeeds.
  • current_key(? _A_,? _K_) @anchor current_key Defines the relation: _K_ is a currently defined database key whose name is the atom _A_. It can be used to generate all the keys for the internal data-base.
  • nth_instance(? _Key_,? _Index_,? _R_) @anchor nth_instance Fetches the _Index_nth entry in the internal database under the key _Key_. Entries are numbered from one. If the key _Key_ or the _Index_ are bound, a reference is unified with _R_. Otherwise, the reference _R_ must be given, and YAP will find the matching key and index.
  • nth_instance(? _Key_,? _Index_, _T_,? _R_) Fetches the _Index_nth entry in the internal database under the key _Key_. Entries are numbered from one. If the key _Key_ or the _Index_ are bound, a reference is unified with _R_. Otherwise, the reference _R_ must be given, and YAP will find the matching key and index.
  • key_statistics(+ _K_,- _Entries_,- _Size_,- _IndexSize_) @anchor key_statistics Returns several statistics for a key _K_. Currently, it says how many entries we have for that key, _Entries_, what is the total size spent on entries, _Size_, and what is the amount of space spent in indices.
  • key_statistics(+ _K_,- _Entries_,- _TotalSize_) Returns several statistics for a key _K_. Currently, it says how many entries we have for that key, _Entries_, what is the total size spent on this key.
  • get_value(+ _A_,- _V_) @anchor get_value In YAP, atoms can be associated with constants. If one such association exists for atom _A_, unify the second argument with the constant. Otherwise, unify _V_ with `[]`. This predicate is YAP specific.
  • set_value(+ _A_,+ _C_) @anchor set_value Associate atom _A_ with constant _C_. The `set_value` and `get_value` built-ins give a fast alternative to the internal data-base. This is a simple form of implementing a global counter. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ read_and_increment_counter(Value) :- get_value(counter, Value), Value1 is Value+1, set_value(counter, Value1). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ This predicate is YAP specific.
There is a strong analogy between the i.d.b. and the way dynamic predicates are stored. In fact, the main i.d.b. predicates might be implemented using dynamic predicates: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ recorda(X,T,R) :- asserta(idb(X,T),R). recordz(X,T,R) :- assertz(idb(X,T),R). recorded(X,T,R) :- clause(idb(X,T),R). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ We can take advantage of this, the other way around, as it is quite easy to write a simple Prolog interpreter, using the i.d.b.: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ asserta(G) :- recorda(interpreter,G,_). assertz(G) :- recordz(interpreter,G,_). retract(G) :- recorded(interpreter,G,R), !, erase(R). call(V) :- var(V), !, fail. call((H :- B)) :- !, recorded(interpreter,(H :- B),_), call(B). call(G) :- recorded(interpreter,G,_). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ In YAP, much attention has been given to the implementation of the i.d.b., especially to the problem of accelerating the access to terms kept in a large list under the same key. Besides using the key, YAP uses an internal lookup function, transparent to the user, to find only the terms that might unify. For instance, in a data base containing the terms ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ b b(a) c(d) e(g) b(X) e(h) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ stored under the key k/1, when executing the query ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ :- recorded(k(_),c(_),R). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ `recorded` would proceed directly to the third term, spending almost the time as if `a(X)` or `b(X)` was being searched. The lookup function uses the functor of the term, and its first three arguments (when they exist). So, `recorded(k(_),e(h),_)` would go directly to the last term, while `recorded(k(_),e(_),_)` would find first the fourth term, and then, after backtracking, the last one. This mechanism may be useful to implement a sort of hierarchy, where the functors of the terms (and eventually the first arguments) work as secondary keys. In the YAP's i.d.b. an optimized representation is used for terms without free variables. This results in a faster retrieval of terms and better space usage. Whenever possible, avoid variables in terms in terms stored in the i.d.b. @section BlackBoard The Blackboard YAP implements a blackboard in the style of the SICStus Prolog blackboard. The blackboard uses the same underlying mechanism as the internal data-base but has several important differences:
  • It is module aware, in contrast to the internal data-base.
  • Keys can only be atoms or integers, and not compound terms.
  • A single term can be stored per key.
  • An atomic update operation is provided; this is useful for parallelism.
  • bb_put(+ _Key_,? _Term_) @anchor bb_put Store term table _Term_ in the blackboard under key _Key_. If a previous term was stored under key _Key_ it is simply forgotten.
  • bb_get(+ _Key_,? _Term_) @anchor bb_get Unify _Term_ with a term stored in the blackboard under key _Key_, or fail silently if no such term exists.
  • bb_delete(+ _Key_,? _Term_) @anchor bb_delete Delete any term stored in the blackboard under key _Key_ and unify it with _Term_. Fail silently if no such term exists.
  • bb_update(+ _Key_,? _Term_,? _New_) @anchor bb_update Atomically unify a term stored in the blackboard under key _Key_ with _Term_, and if the unification succeeds replace it by _New_. Fail silently if no such term exists or if unification fails.
@section Sets Collecting Solutions to a Goal When there are several solutions to a goal, if the user wants to collect all the solutions he may be led to use the data base, because backtracking will forget previous solutions. YAP allows the programmer to choose from several system predicates instead of writing his own routines. [findall/3](@ref findall) gives you the fastest, but crudest solution. The other built-in predicates post-process the result of the query in several different ways:
  • findall( _T_,+ _G_,- _L_) [ISO] @anchor findall Unifies _L_ with a list that contains all the instantiations of the term _T_ satisfying the goal _G_. With the following program: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ a(2,1). a(1,1). a(2,2). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ the answer to the query ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ findall(X,a(X,Y),L). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ would be: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ X = _32 Y = _33 L = [2,1,2]; no ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  • findall( _T_,+ _G_,+ _L_,- _L0_) Similar to [findall/3](@ref findall), but appends all answers to list _L0_.
  • all( _T_,+ _G_,- _L_) @anchor all Similar to `findall( _T_, _G_, _L_)` but eliminate repeated elements. Thus, assuming the same clauses as in the above example, the reply to the query ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ all(X,a(X,Y),L). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ would be: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ X = _32 Y = _33 L = [2,1]; no ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Note that [all/3](@ref all) will fail if no answers are found.
  • bagof( _T_,+ _G_,- _L_) [ISO] @anchor bagof For each set of possible instances of the free variables occurring in _G_ but not in _T_, generates the list _L_ of the instances of _T_ satisfying _G_. Again, assuming the same clauses as in the examples above, the reply to the query ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ bagof(X,a(X,Y),L). would be: X = _32 Y = 1 L = [2,1]; X = _32 Y = 2 L = [2]; no ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  • setof( _X_,+ _P_,- _B_) [ISO] @anchor setof Similar to `bagof( _T_, _G_, _L_)` but sorts list _L_ and keeping only one copy of each element. Again, assuming the same clauses as in the examples above, the reply to the query ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ setof(X,a(X,Y),L). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ would be: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ X = _32 Y = 1 L = [1,2]; X = _32 Y = 2 L = [2]; no ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
@section Grammars Grammar Rules Grammar rules in Prolog are both a convenient way to express definite clause grammars and an extension of the well known context-free grammars. A grammar rule is of the form: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ head --> body ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ where both \a head and \a body are sequences of one or more items linked by the standard conjunction operator ','. Items can be:
  • a non-terminal symbol may be either a complex term or an atom.
  • a terminal symbol may be any Prolog symbol. Terminals are written as Prolog lists.
  • an empty body is written as the empty list '[ ]'.
  • extra conditions may be inserted as Prolog procedure calls, by being written inside curly brackets '{' and '}'.
  • the left side of a rule consists of a nonterminal and an optional list of terminals.
  • alternatives may be stated in the right-hand side of the rule by using the disjunction operator ';'.
  • the cut and conditional symbol ('-\>') may be inserted in the right hand side of a grammar rule
Grammar related built-in predicates:
  • expand_term( _T_,- _X_) @anchor expand_term This predicate is used by YAP for preprocessing each top level term read when consulting a file and before asserting or executing it. It rewrites a term _T_ to a term _X_ according to the following rules: first try [term_expansion/2](@ref term_expansion) in the current module, and then try to use the user defined predicate `user:term_expansion/2`. If this call fails then the translating process for DCG rules is applied, together with the arithmetic optimizer whenever the compilation of arithmetic expressions is in progress.
  • _CurrentModule_:term_expansion( _T_,- _X_), user:term_expansion( _T_,- _X_) @anchor term_expansion This user-defined predicate is called by `expand_term/3` to preprocess all terms read when consulting a file. If it succeeds:
    • If _X_ is of the form `:- G` or `?- G`, it is processed as a directive.
    • If _X_ is of the form `'$source_location'( _File_, _Line_): _Clause_` it is processed as if from `File` and line `Line`.
    • If _X_ is a list, all terms of the list are asserted or processed as directives.
    • The term _X_ is asserted instead of _T_.
  • _CurrentModule_:goal_expansion(+ _G_,+ _M_,- _NG_), user:goal_expansion(+ _G_,+ _M_,- _NG_) @anchor goal_expansion YAP now supports [goal_expansion/3](@ref goal_expansion). This is an user-defined procedure that is called after term expansion when compiling or asserting goals for each sub-goal in a clause. The first argument is bound to the goal and the second to the module under which the goal _G_ will execute. If [goal_expansion/3](@ref goal_expansion) succeeds the new sub-goal _NG_ will replace _G_ and will be processed in the same way. If [goal_expansion/3](@ref goal_expansion) fails the system will use the default rules.
  • phrase(+ _P_, _L_, _R_) @anchor phrase This predicate succeeds when the difference list ` _L_- _R_` is a phrase of type _P_.
  • phrase(+ _P_, _L_) This predicate succeeds when _L_ is a phrase of type _P_. The same as `phrase(P,L,[])`. Both this predicate and the previous are used as a convenient way to start execution of grammar rules.
  • 'C'( _S1_, _T_, _S2_) @anchor C This predicate is used by the grammar rules compiler and is defined as `'C'([H|T],H,T)`.
@section OS Access to Operating System Functionality The following built-in predicates allow access to underlying Operating System functionality:
  • cd(+ _D_) @anchor cd Changes the current directory (on UNIX environments).
  • cd Changes the current directory (on UNIX environments) to the user's home directory.
  • environ(+ _E_,- _S_) @anchor environ Given an environment variable _E_ this predicate unifies the second argument _S_ with its value.
  • getcwd(- _D_) @anchor getcwd Unify the current directory, represented as an atom, with the argument _D_.
  • pwd @anchor pwd Prints the current directory.
  • ls @anchor ls Prints a list of all files in the current directory.
  • putenv(+ _E_,+ _S_) @anchor putenv Set environment variable _E_ to the value _S_. If the environment variable _E_ does not exist, create a new one. Both the environment variable and the value must be atoms.
  • rename(+ _F_,+ _G_) @anchor rename Renames file _F_ to _G_.
  • sh @anchor sh Creates a new shell interaction.
  • system(+ _S_) @anchor system Passes command _S_ to the Bourne shell (on UNIX environments) or the current command interpreter in WIN32 environments.
  • unix(+ _S_) @anchor unix Access to Unix-like functionality:
    • argv/1 Return a list of arguments to the program. These are the arguments that follow a `--`, as in the usual Unix convention.
    • cd/0 Change to home directory.
    • cd/1 Change to given directory. Acceptable directory names are strings or atoms.
    • environ/2 If the first argument is an atom, unify the second argument with the value of the corresponding environment variable.
    • getcwd/1 Unify the first argument with an atom representing the current directory.
    • putenv/2 Set environment variable _E_ to the value _S_. If the environment variable _E_ does not exist, create a new one. Both the environment variable and the value must be atoms.
    • shell/1 Execute command under current shell. Acceptable commands are strings or atoms.
    • system/1 Execute command with `/bin/sh`. Acceptable commands are strings or atoms.
    • shell/0 Execute a new shell.
  • working_directory(- _CurDir_,? _NextDir_) @anchor working_directory Fetch the current directory at _CurDir_. If _NextDir_ is bound to an atom, make its value the current working directory.
  • alarm(+ _Seconds_,+ _Callable_,+ _OldAlarm_) @anchor alarm Arranges for YAP to be interrupted in _Seconds_ seconds, or in [ _Seconds_| _MicroSeconds_]. When interrupted, YAP will execute _Callable_ and then return to the previous execution. If _Seconds_ is `0`, no new alarm is scheduled. In any event, any previously set alarm is canceled. The variable _OldAlarm_ unifies with the number of seconds remaining until any previously scheduled alarm was due to be delivered, or with `0` if there was no previously scheduled alarm. Note that execution of _Callable_ will wait if YAP is executing built-in predicates, such as Input/Output operations. The next example shows how _alarm/3_ can be used to implement a simple clock: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ loop :- loop. ticker :- write('.'), flush_output, get_value(tick, yes), alarm(1,ticker,_). :- set_value(tick, yes), alarm(1,ticker,_), loop. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ The clock, `ticker`, writes a dot and then checks the flag `tick` to see whether it can continue ticking. If so, it calls itself again. Note that there is no guarantee that the each dot corresponds a second: for instance, if the YAP is waiting for user input, `ticker` will wait until the user types the entry in. The next example shows how [alarm/3](@ref alarm) can be used to guarantee that a certain procedure does not take longer than a certain amount of time: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ loop :- loop. :- catch((alarm(10, throw(ball), _),loop), ball, format('Quota exhausted.~n',[])). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ In this case after `10` seconds our `loop` is interrupted, `ball` is thrown, and the handler writes `Quota exhausted`. Execution then continues from the handler. Note that in this case `loop/0` always executes until the alarm is sent. Often, the code you are executing succeeds or fails before the alarm is actually delivered. In this case, you probably want to disable the alarm when you leave the procedure. The next procedure does exactly so: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ once_with_alarm(Time,Goal,DoOnAlarm) :- catch(execute_once_with_alarm(Time, Goal), alarm, DoOnAlarm). execute_once_with_alarm(Time, Goal) :- alarm(Time, alarm, _), ( call(Goal) -> alarm(0, alarm, _) ; alarm(0, alarm, _), fail). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ The procedure `once_with_alarm/3` has three arguments: the _Time_ to wait before the alarm is sent; the _Goal_ to execute; and the goal _DoOnAlarm_ to execute if the alarm is sent. It uses [catch/3](@ref catch) to handle the case the `alarm` is sent. Then it starts the alarm, calls the goal _Goal_, and disables the alarm on success or failure.
  • on_signal(+ _Signal_,? _OldAction_,+ _Callable_) @anchor on_signal Set the interrupt handler for soft interrupt _Signal_ to be _Callable_. _OldAction_ is unified with the previous handler. Only a subset of the software interrupts (signals) can have their handlers manipulated through [on_signal/3](@ref on_signal). Their POSIX names, YAP names and default behavior is given below. The "YAP name" of the signal is the atom that is associated with each signal, and should be used as the first argument to [on_signal/3](@ref on_signal). It is chosen so that it matches the signal's POSIX name. [on_signal/3](@ref on_signal) succeeds, unless when called with an invalid signal name or one that is not supported on this platform. No checks are made on the handler provided by the user.
    • sig_up (Hangup) SIGHUP in Unix/Linux; Reconsult the initialization files ~/.yaprc, ~/.prologrc and ~/prolog.ini.
    • sig_usr1 and sig_usr2 (User signals) SIGUSR1 and SIGUSR2 in Unix/Linux; Print a message and halt.
    A special case is made, where if _Callable_ is bound to `default`, then the default handler is restored for that signal. A call in the form `on_signal( _S_, _H_, _H_)` can be used to retrieve a signal's current handler without changing it. It must be noted that although a signal can be received at all times, the handler is not executed while YAP is waiting for a query at the prompt. The signal will be, however, registered and dealt with as soon as the user makes a query. Please also note, that neither POSIX Operating Systems nor YAP guarantee that the order of delivery and handling is going to correspond with the order of dispatch.
@section Term_Modification Term Modification It is sometimes useful to change the value of instantiated variables. Although, this is against the spirit of logic programming, it is sometimes useful. As in other Prolog systems, YAP has several primitives that allow updating Prolog terms. Note that these primitives are also backtrackable. The `setarg/3` primitive allows updating any argument of a Prolog compound terms. The `mutable` family of predicates provides mutable variables. They should be used instead of `setarg/3`, as they allow the encapsulation of accesses to updatable variables. Their implementation can also be more efficient for long deterministic computations.
  • setarg(+ _I_,+ _S_,? _T_) @anchor setarg3n Set the value of the _I_th argument of term _S_ to term _T_.
  • create_mutable(+ _D_,- _M_) @anchor create_mutable Create new mutable variable _M_ with initial value _D_.
  • is_mutable(? _D_) @anchor is_mutable Holds if _D_ is a mutable term.
  • get_mutable(? _D_,+ _M_) @anchor get_mutable Unify the current value of mutable term _M_ with term _D_.
  • update_mutable(+ _D_,+ _M_) @anchor update_mutable Set the current value of mutable term _M_ to term _D_.
@section Global_Variables Global Variables Global variables are associations between names (atoms) and terms. They differ in various ways from storing information using [assert/1](@ref assert) or [recorda/3](@ref recorda).
  • The value lives on the Prolog (global) stack. This implies that lookup time is independent from the size of the term. This is particularly interesting for large data structures such as parsed XML documents or the CHR global constraint store.
  • They support both global assignment using [nb_setval/2](@ref nb_setval) and backtrackable assignment using [b_setval/2](@ref b_setval).
  • Only one value (which can be an arbitrary complex Prolog term) can be associated to a variable at a time.
  • Their value cannot be shared among threads. Each thread has its own namespace and values for global variables.
Currently global variables are scoped globally. We may consider module scoping in future versions. Both [b_setval/2](@ref b_setval) and [nb_setval/2](@ref nb_setval) implicitly create a variable if the referenced name does not already refer to a variable. Global variables may be initialised from directives to make them available during the program lifetime, but some considerations are necessary for saved-states and threads. Saved-states to not store global variables, which implies they have to be declared with [initialization/1](@ref initialization) to recreate them after loading the saved state. Each thread has its own set of global variables, starting with an empty set. Using `thread_initialization/1` to define a global variable it will be defined, restored after reloading a saved state and created in all threads that are created after the registration. Finally, global variables can be initialised using the exception hook called [exception/3](@ref exception). The latter technique is used by CHR.
  • b_setval(+ _Name_, + _Value_) @anchor b_setval Associate the term _Value_ with the atom _Name_ or replaces the currently associated value with _Value_. If _Name_ does not refer to an existing global variable a variable with initial value [] is created (the empty list). On backtracking the assignment is reversed.
  • b_getval(+ _Name_, - _Value_) @anchor b_getval Get the value associated with the global variable _Name_ and unify it with _Value_. Note that this unification may further instantiate the value of the global variable. If this is undesirable the normal precautions (double negation or [copy_term/2](@ref copy_term)) must be taken. The [b_getval/2](@ref b_getval) predicate generates errors if _Name_ is not an atom or the requested variable does not exist. Notice that for compatibility with other systems _Name_ must be already associated with a term: otherwise the system will generate an error.
  • nb_setval(+ _Name_, + _Value_) @anchor nb_setval Associates a copy of _Value_ created with [duplicate_term/2](@ref duplicate_term) with the atom _Name_. Note that this can be used to set an initial value other than `[]` prior to backtrackable assignment.
  • nb_getval(+ _Name_, - _Value_) @anchor nb_getval The [nb_getval/2](@ref nb_getval) predicate is a synonym for [b_getval/2](@ref b_getval), introduced for compatibility and symmetry. As most scenarios will use a particular global variable either using non-backtrackable or backtrackable assignment, using [nb_getval/2](@ref nb_getval) can be used to document that the variable is used non-backtrackable.
  • nb_linkval(+ _Name_, + _Value_) @anchor nb_linkval Associates the term _Value_ with the atom _Name_ without copying it. This is a fast special-purpose variation of [nb_setval/2](@ref nb_setval) intended for expert users only because the semantics on backtracking to a point before creating the link are poorly defined for compound terms. The principal term is always left untouched, but backtracking behaviour on arguments is undone if the original assignment was trailed and left alone otherwise, which implies that the history that created the term affects the behaviour on backtracking. Please consider the following example: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ demo_nb_linkval :- T = nice(N), ( N = world, nb_linkval(myvar, T), fail ; nb_getval(myvar, V), writeln(V) ). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  • nb_set_shared_val(+ _Name_, + _Value_) @anchor nb_set_shared_val Associates the term _Value_ with the atom _Name_, but sharing non-backtrackable terms. This may be useful if you want to rewrite a global variable so that the new copy will survive backtracking, but you want to share structure with the previous term. The next example shows the differences between the three built-ins: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ?- nb_setval(a,a(_)),nb_getval(a,A),nb_setval(b,t(C,A)),nb_getval(b,B). A = a(_A), B = t(_B,a(_C)) ? ?- nb_setval(a,a(_)),nb_getval(a,A),nb_set_shared_val(b,t(C,A)),nb_getval(b,B). ?- nb_setval(a,a(_)),nb_getval(a,A),nb_linkval(b,t(C,A)),nb_getval(b,B). A = a(_A), B = t(C,a(_A)) ? ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  • nb_setarg(+{Arg], + _Term_, + _Value_) @anchor nb_setarg Assigns the _Arg_-th argument of the compound term _Term_ with the given _Value_ as setarg/3, but on backtracking the assignment is not reversed. If _Term_ is not atomic, it is duplicated using duplicate_term/2. This predicate uses the same technique as [nb_setval/2](@ref nb_setval). We therefore refer to the description of [nb_setval/2](@ref nb_setval) for details on non-backtrackable assignment of terms. This predicate is compatible to GNU-Prolog `setarg(A,T,V,false)`, removing the type-restriction on _Value_. See also [nb_linkarg/3](@ref nb_linkarg). Below is an example for counting the number of solutions of a goal. Note that this implementation is thread-safe, reentrant and capable of handling exceptions. Realising these features with a traditional implementation based on assert/retract or flag/3 is much more complicated. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ succeeds_n_times(Goal, Times) :- Counter = counter(0), ( Goal, arg(1, Counter, N0), N is N0 + 1, nb_setarg(1, Counter, N), fail ; arg(1, Counter, Times) ). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  • nb_set_shared_arg(+ _Arg_, + _Term_, + _Value_) @anchor nb_set_shared_arg As [nb_setarg/3](@ref nb_setarg), but like [nb_linkval/2](@ref nb_linkval) it does not duplicate the global sub-terms in _Value_. Use with extreme care and consult the documentation of [nb_linkval/2](@ref nb_linkval) before use.
  • nb_linkarg(+ _Arg_, + _Term_, + _Value_) @anchor nb_linkarg As [nb_setarg/3](@ref nb_setarg), but like [nb_linkval/2](@ref nb_linkval) it does not duplicate _Value_. Use with extreme care and consult the documentation of [nb_linkval/2](@ref nb_linkval) before use.
  • nb_current(? _Name_, ? _Value_) @anchor nb_current Enumerate all defined variables with their value. The order of enumeration is undefined.
  • nb_delete(+ _Name_) @anchor nb_delete Delete the named global variable.
Global variables have been introduced by various Prolog implementations recently. We follow the implementation of them in SWI-Prolog, itself based on hProlog by Bart Demoen. GNU-Prolog provides a rich set of global variables, including arrays. Arrays can be implemented easily in YAP and SWI-Prolog using [functor/3](@ref functor) and `setarg/3` due to the unrestricted arity of compound terms. @section Profiling Profiling Prolog Programs YAP includes two profilers. The count profiler keeps information on the number of times a predicate was called. This information can be used to detect what are the most commonly called predicates in the program. The count profiler can be compiled by setting YAP's flag [profiling](@ref profiling) to `on`. The time-profiler is a `gprof` profiler, and counts how many ticks are being spent on specific predicates, or on other system functions such as internal data-base accesses or garbage collects. The YAP profiling sub-system is currently under development. Functionality for this sub-system will increase with newer implementation. @section The_Count_Profiler The Count Profiler *Notes:* The count profiler works by incrementing counters at procedure entry or backtracking. It provides exact information:
  • Profiling works for both static and dynamic predicates.
  • Currently only information on entries and retries to a predicate are maintained. This may change in the future.
  • As an example, the following user-level program gives a list of the most often called procedures in a program. The procedure `list_profile` shows all procedures, irrespective of module, and the procedure `list_profile/1` shows the procedures being used in a specific module. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ list_profile :- % get number of calls for each profiled procedure setof(D-[M:P|D1],(current_module(M),profile_data(M:P,calls,D),profile_data(M:P,retries,D1)),LP), % output so that the most often called % predicates will come last: write_profile_data(LP). list_profile(Module) :- % get number of calls for each profiled procedure setof(D-[Module:P|D1],(profile_data(Module:P,calls,D),profile_data(Module:P,retries,D1)),LP), % output so that the most often called % predicates will come last: write_profile_data(LP). write_profile_data([]). write_profile_data([D-[M:P|R]|SLP]) :- % swap the two calls if you want the most often % called predicates first. format('~a:~w: ~32+~t~d~12+~t~d~12+~n', [M,P,D,R]), write_profile_data(SLP). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
These are the current predicates to access and clear profiling data:
  • profile_data(? _Na/Ar_, ? _Parameter_, - _Data_) @anchor profile_data Give current profile data on _Parameter_ for a predicate described by the predicate indicator _Na/Ar_. If any of _Na/Ar_ or _Parameter_ are unbound, backtrack through all profiled predicates or stored parameters. Current parameters are:
    • calls Number of times a procedure was called.
    • retries Number of times a call to the procedure was backtracked to and retried.
  • profile_reset @anchor profiled_reset Reset all profiling information.
@section Tick_Profiler Tick Profiler The tick profiler works by interrupting the Prolog code every so often and checking at each point the code was. The profiler must be able to retrace the state of the abstract machine at every moment. The major advantage of this approach is that it gives the actual amount of time being spent per procedure, or whether garbage collection dominates execution time. The major drawback is that tracking down the state of the abstract machine may take significant time, and in the worst case may slow down the whole execution. The following procedures are available:
  • profinit @anchor profinit Initialise the data-structures for the profiler. Unnecessary for dynamic profiler.
  • profon @anchor profon Start profiling.
  • profoff @anchor profoff Stop profiling.
  • showprofres @anchor showprofres Show profiling info.
  • showprofres( _N_) Show profiling info for the top-most _N_ predicates.
The [showprofres/0](@ref showprofres) and `showprofres/1` predicates call a user-defined multifile hook predicate, `user:prolog_predicate_name/2`, that can be used for converting a possibly explicitly-qualified callable term into an atom that will used when printing the profiling information. @section Call_Counting Counting Calls Predicates compiled with YAP's flag [call_counting](@ref call_counting) set to `on` update counters on the numbers of calls and of retries. Counters are actually decreasing counters, so that they can be used as timers. Three counters are available:
  • `calls`: number of predicate calls since execution started or since system was reset;
  • `retries`: number of retries for predicates called since execution started or since counters were reset;
  • `calls_and_retries`: count both on predicate calls and retries.
These counters can be used to find out how many calls a certain goal takes to execute. They can also be used as timers. The code for the call counters piggybacks on the profiling code. Therefore, activating the call counters also activates the profiling counters. These are the predicates that access and manipulate the call counters:
  • call_count_data(- _Calls_, - _Retries_, - _CallsAndRetries_) @anchor call_count_data Give current call count data. The first argument gives the current value for the _Calls_ counter, next the _Retries_ counter, and last the _CallsAndRetries_ counter.
  • call_count_reset @anchor call_count_reset Reset call count counters. All timers are also reset.
  • call_count(? _CallsMax_, ? _RetriesMax_, ? _CallsAndRetriesMax_) @anchor call_count Set call count counter as timers. YAP will generate an exception if one of the instantiated call counters decreases to 0. YAP will ignore unbound arguments:
    • _CallsMax_: throw the exception `call_counter` when the counter `calls` reaches 0;
    • _RetriesMax_: throw the exception `retry_counter` when the counter `retries` reaches 0;
    • _CallsAndRetriesMax_: throw the exception `call_and_retry_counter` when the counter `calls_and_retries` reaches 0.
Next, we show a simple example of how to use call counters: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ?- yap_flag(call_counting,on), [-user]. l :- l. end_of_file. yap_flag(call_counting,off). yes yes ?- catch((call_count(10000,_,_),l),call_counter,format("limit_exceeded.~n",[])). limit_exceeded. yes ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Notice that we first compile the looping predicate `l/0` with [call_counting](@ref call_counting) `on`. Next, we [catch/3](@ref catch) to handle an exception when `l/0` performs more than 10000 reductions. @section Arrays Arrays The YAP system includes experimental support for arrays. The support is enabled with the option `YAP_ARRAYS`. There are two very distinct forms of arrays in YAP. The dynamic arrays are a different way to access compound terms created during the execution. Like any other terms, any bindings to these terms and eventually the terms themselves will be destroyed during backtracking. Our goal in supporting dynamic arrays is twofold. First, they provide an alternative to the standard [arg/3](@ref arg) built-in. Second, because dynamic arrays may have name that are globally visible, a dynamic array can be visible from any point in the program. In more detail, the clause ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ g(X) :- array_element(a,2,X). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ will succeed as long as the programmer has used the built-in array/2 to create an array term with at least 3 elements in the current environment, and the array was associated with the name `a`. The element `X` is a Prolog term, so one can bind it and any such bindings will be undone when backtracking. Note that dynamic arrays do not have a type: each element may be any Prolog term. The static arrays are an extension of the database. They provide a compact way for manipulating data-structures formed by characters, integers, or floats imperatively. They can also be used to provide two-way communication between YAP and external programs through shared memory. In order to efficiently manage space elements in a static array must have a type. Currently, elements of static arrays in YAP should have one of the following predefined types:
  • `byte`: an 8-bit signed character.
  • `unsigned_byte`: an 8-bit unsigned character.
  • `int`: Prolog integers. Size would be the natural size for the machine's architecture.
  • `float`: Prolog floating point number. Size would be equivalent to a double in `C`.
  • `atom`: a Prolog atom.
  • `dbref`: an internal database reference.
  • `term`: a generic Prolog term. Note that this will term will not be stored in the array itself, but instead will be stored in the Prolog internal database.
Arrays may be named or anonymous. Most arrays will be named, that is associated with an atom that will be used to find the array. Anonymous arrays do not have a name, and they are only of interest if the `TERM_EXTENSIONS` compilation flag is enabled. In this case, the unification and parser are extended to replace occurrences of Prolog terms of the form `X[I]` by run-time calls to [array_element/3](@ref array_element), so that one can use array references instead of extra calls to [arg/3](@ref arg). As an example: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ g(X,Y,Z,I,J) :- X[I] is Y[J]+Z[I]. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ should give the same results as: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ G(X,Y,Z,I,J) :- array_element(X,I,E1), array_element(Y,J,E2), array_element(Z,I,E3), E1 is E2+E3. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Note that the only limitation on array size are the stack size for dynamic arrays; and, the heap size for static (not memory mapped) arrays. Memory mapped arrays are limited by available space in the file system and in the virtual memory space. The following predicates manipulate arrays:
  • array(+ _Name_, + _Size_) @anchor array Creates a new dynamic array. The _Size_ must evaluate to an integer. The _Name_ may be either an atom (named array) or an unbound variable (anonymous array). Dynamic arrays work as standard compound terms, hence space for the array is recovered automatically on backtracking.
  • static_array(+ _Name_, + _Size_, + _Type_) @anchor static_array Create a new static array with name _Name_. Note that the _Name_ must be an atom (named array). The _Size_ must evaluate to an integer. The _Type_ must be bound to one of types mentioned previously.
  • reset_static_array(+ _Name_) @anchor reset_static_array Reset static array with name _Name_ to its initial value.
  • static_array_location(+ _Name_, - _Ptr_) @anchor static_array_location Give the location for a static array with name _Name_.
  • static_array_properties(? _Name_, ? _Size_, ? _Type_) @anchor static_array_properties Show the properties size and type of a static array with name _Name_. Can also be used to enumerate all current static arrays. This built-in will silently fail if the there is no static array with that name.
  • static_array_to_term(? _Name_, ? _Term_) @anchor static_array_to_term Convert a static array with name _Name_ to a compound term of name _Name_. This built-in will silently fail if the there is no static array with that name.
  • mmapped_array(+ _Name_, + _Size_, + _Type_, + _File_) @anchor mmapped_array Similar to [static_array/3](@ref static_array), but the array is memory mapped to file _File_. This means that the array is initialized from the file, and that any changes to the array will also be stored in the file. This built-in is only available in operating systems that support the system call `mmap`. Moreover, mmapped arrays do not store generic terms (type `term`).
  • close_static_array(+ _Name_) @anchor close_static_array Close an existing static array of name _Name_. The _Name_ must be an atom (named array). Space for the array will be recovered and further accesses to the array will return an error.
  • resize_static_array(+ _Name_, - _OldSize_, + _NewSize_) @anchor resize_static_array Expand or reduce a static array, The _Size_ must evaluate to an integer. The _Name_ must be an atom (named array). The _Type_ must be bound to one of `int`, `dbref`, `float` or `atom`. Note that if the array is a mmapped array the size of the mmapped file will be actually adjusted to correspond to the size of the array.
  • array_element(+ _Name_, + _Index_, ? _Element_) @anchor array_element Unify _Element_ with _Name_[ _Index_]. It works for both static and dynamic arrays, but it is read-only for static arrays, while it can be used to unify with an element of a dynamic array.
  • update_array(+ _Name_, + _Index_, ? _Value_) @anchor update_array Attribute value _Value_ to _Name_[ _Index_]. Type restrictions must be respected for static arrays. This operation is available for dynamic arrays if `MULTI_ASSIGNMENT_VARIABLES` is enabled (true by default). Backtracking undoes _update_array/3_ for dynamic arrays, but not for static arrays. Note that [update_array/3](@ref update_array) actually uses `setarg/3` to update elements of dynamic arrays, and `setarg/3` spends an extra cell for every update. For intensive operations we suggest it may be less expensive to unify each element of the array with a mutable terms and to use the operations on mutable terms.
  • add_to_array_element(+ _Name_, + _Index_, , + _Number_, ? _NewValue_) @anchor add_to_array_element Add _Number_ _Name_[ _Index_] and unify _NewValue_ with the incremented value. Observe that _Name_[ _Index_] must be an number. If _Name_ is a static array the type of the array must be `int` or `float`. If the type of the array is `int` you only may add integers, if it is `float` you may add integers or floats. If _Name_ corresponds to a dynamic array the array element must have been previously bound to a number and `Number` can be any kind of number. The `add_to_array_element/3` built-in actually uses `setarg/3` to update elements of dynamic arrays. For intensive operations we suggest it may be less expensive to unify each element of the array with a mutable terms and to use the operations on mutable terms.
@section Preds Predicate Information Built-ins that return information on the current predicates and modules:
  • current_module( _M_) @anchor current_module Succeeds if _M_ are defined modules. A module is defined as soon as some predicate defined in the module is loaded, as soon as a goal in the module is called, or as soon as it becomes the current type-in module.
  • current_module( _M_, _F_) Succeeds if _M_ are current modules associated to the file _F_.
@section Misc Miscellaneous
  • statistics/0 @anchor statistics Send to the current user error stream general information on space used and time spent by the system. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ?- statistics. memory (total) 4784124 bytes program space 3055616 bytes: 1392224 in use, 1663392 free 2228132 max stack space 1531904 bytes: 464 in use, 1531440 free global stack: 96 in use, 616684 max local stack: 368 in use, 546208 max trail stack 196604 bytes: 8 in use, 196596 free 0.010 sec. for 5 code, 2 stack, and 1 trail space overflows 0.130 sec. for 3 garbage collections which collected 421000 bytes 0.000 sec. for 0 atom garbage collections which collected 0 bytes 0.880 sec. runtime 1.020 sec. cputime 25.055 sec. elapsed time ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ The example shows how much memory the system spends. Memory is divided into Program Space, Stack Space and Trail. In the example we have 3MB allocated for program spaces, with less than half being actually used. YAP also shows the maximum amount of heap space having been used which was over 2MB. The stack space is divided into two stacks which grow against each other. We are in the top level so very little stack is being used. On the other hand, the system did use a lot of global and local stack during the previous execution (we refer the reader to a WAM tutorial in order to understand what are the global and local stacks). YAP also shows information on how many memory overflows and garbage collections the system executed, and statistics on total execution time. Cputime includes all running time, runtime excludes garbage collection and stack overflow time.
  • statistics(? _Param_,- _Info_) Gives statistical information on the system parameter given by first argument:
    • atoms @anchor atoms `[ _NumberOfAtoms_, _SpaceUsedBy Atoms_]` This gives the total number of atoms `NumberOfAtoms` and how much space they require in bytes, _SpaceUsedBy Atoms_.
    • cputime @anchor cputime `[ _Time since Boot_, _Time From Last Call to Cputime_]` This gives the total cputime in milliseconds spent executing Prolog code, garbage collection and stack shifts time included.
    • dynamic_code @anchor dynamic_code `[ _Clause Size_, _Index Size_, _Tree Index Size_, _Choice Point Instructions Size_, _Expansion Nodes Size_, _Index Switch Size_]` Size of static code in YAP in bytes: _Clause Size_, the number of bytes allocated for clauses, plus _Index Size_, the number of bytes spent in the indexing code. The indexing code is divided into main tree, _Tree Index Size_, tables that implement choice-point manipulation, _Choice xsPoint Instructions Size_, tables that cache clauses for future expansion of the index tree, _Expansion Nodes Size_, and tables such as hash tables that select according to value, _Index Switch Size_.
    • garbage_collection @anchor garbage_collection `[ _Number of GCs_, _Total Global Recovered_, _Total Time Spent_]` Number of garbage collections, amount of space recovered in kbytes, and total time spent doing garbage collection in milliseconds. More detailed information is available using `yap_flag(gc_trace,verbose)`.
    • global_stack @anchor global_stack `[ _Global Stack Used_, _Execution Stack Free_]` Space in kbytes currently used in the global stack, and space available for expansion by the local and global stacks.
    • local_stack @anchor local_stack `[ _Local Stack Used_, _Execution Stack Free_]` Space in kbytes currently used in the local stack, and space available for expansion by the local and global stacks.
    • heap @anchor heap `[ _Heap Used_, _Heap Free_]` Total space in kbytes not recoverable in backtracking. It includes the program code, internal data base, and, atom symbol table.
    • program @anchor program `[ _Program Space Used_, _Program Space Free_]` Equivalent to [heap](@ref heap).
    • runtime @anchor runtime `[ _Time since Boot_, _Time From Last Call to Runtime_]` This gives the total cputime in milliseconds spent executing Prolog code, not including garbage collections and stack shifts. Note that until YAP4.1.2 the [runtime](@ref runtime) statistics would return time spent on garbage collection and stack shifting.
    • stack_shifts @anchor stack_shifts `[ _Number of Heap Shifts_, _Number of Stack Shifts_, _Number of Trail Shifts_]` Number of times YAP had to expand the heap, the stacks, or the trail. More detailed information is available using `yap_flag(gc_trace,verbose)`.
    • static_code @anchor static_code `[ _Clause Size_, _Index Size_, _Tree Index Size_, _Expansion Nodes Size_, _Index Switch Size_]` Size of static code in YAP in bytes: _Clause Size_, the number of bytes allocated for clauses, plus _Index Size_, the number of bytes spent in the indexing code. The indexing code is divided into a main tree, _Tree Index Size_, table that cache clauses for future expansion of the index tree, _Expansion Nodes Size_, and and tables such as hash tables that select according to value, _Index Switch Size_.
    • trail @anchor trail `[ _Trail Used_, _Trail Free_]` Space in kbytes currently being used and still available for the trail.
    • walltime @anchor walltime `[ _Time since Boot_, _Time From Last Call to Walltime_]` This gives the clock time in milliseconds since starting Prolog.
  • time(: _Goal_) @anchor time Prints the CPU time and the wall time for the execution of _Goal_. Possible choice-points of _Goal_ are removed. Based on the SWI-Prolog definition (minus reporting the number of inferences, which YAP currently does not support).
  • yap_flag(? _Param_,? _Value_) @anchor yap_flag Set or read system properties for _Param_:
    • argv @anchor argv Read-only flag. It unifies with a list of atoms that gives the arguments to YAP after `--`.
    • agc_margin @anchor agc_margin An integer: if this amount of atoms has been created since the last atom-garbage collection, perform atom garbage collection at the first opportunity. Initial value is 10,000. May be changed. A value of 0 (zero) disables atom garbage collection.
    • associate @anchor associate Read-write flag telling a suffix for files associated to Prolog sources. It is `yap` by default.
    • bounded [ISO] @anchor bounded Read-only flag telling whether integers are bounded. The value depends on whether YAP uses the GMP library or not.
    • profiling @anchor call_counting If `off` (default) do not compile call counting information for procedures. If `on` compile predicates so that they calls and retries to the predicate may be counted. Profiling data can be read through the [call_count_data/3](@ref call_count_data) built-in.
    • char_conversion [ISO] Writable flag telling whether a character conversion table is used when reading terms. The default value for this flag is `off` except in `sicstus` and `iso` language modes, where it is `on`.
    • character_escapes [ISO] @anchor character_escapes Writable flag telling whether a character escapes are enables, `true`, or disabled, `false`. The default value for this flag is `on`.
    • debug [ISO] @anchor debug If _Value_ is unbound, tell whether debugging is `true` or `false`. If _Value_ is bound to `true` enable debugging, and if it is bound to `false` disable debugging.
    • debugger_print_options @anchor debugger_print_options If bound, set the argument to the `write_term/3` options the debugger uses to write terms. If unbound, show the current options.
    • dialect @anchor dialect Read-only flag that always returns `yap`.
    • discontiguous_warnings @anchor discontiguous_warnings If _Value_ is unbound, tell whether warnings for discontiguous predicates are `on` or `off`. If _Value_ is bound to `on` enable these warnings, and if it is bound to `off` disable them. The default for YAP is `off`, unless we are in `sicstus` or `iso` mode.
    • dollar_as_lower_case @anchor dollar_as_lower_case If `off` (default) consider the character '$' a control character, if `on` consider '$' a lower case character.
    • double_quotes [ISO] @anchor double_quotes If _Value_ is unbound, tell whether a double quoted list of characters token is converted to a list of atoms, `chars`, to a list of integers, `codes`, or to a single atom, `atom`. If _Value_ is bound, set to the corresponding behavior. The default value is `codes`.
    • executable @anchor executable Read-only flag. It unifies with an atom that gives the original program path.
    • fast @anchor fast If `on` allow fast machine code, if `off` (default) disable it. Only available in experimental implementations.
    • fileerrors If `on` `fileerrors` is `on`, if `off` (default) `fileerrors` is disabled.
    • float_format @anchor float_format C-library `printf()` format specification used by [write/1](@ref write) and friends to determine how floating point numbers are printed. The default is `%.15g`. The specified value is passed to `printf()` without further checking. For example, if you want less digits printed, `%g` will print all floats using 6 digits instead of the default 15.
    • gc If `on` allow garbage collection (default), if `off` disable it.
    • gc_margin @anchor gc_margin Set or show the minimum free stack before starting garbage collection. The default depends on total stack size.
    • gc_trace @anchor gc_trace If `off` (default) do not show information on garbage collection and stack shifts, if `on` inform when a garbage collection or stack shift happened, if [verbose](@ref verbose) give detailed information on garbage collection and stack shifts. Last, if `very_verbose` give detailed information on data-structures found during the garbage collection process, namely, on choice-points.
    • generate_debugging_info @anchor generate_debugging_info If `true` (default) generate debugging information for procedures, including source mode. If `false` predicates no information is generated, although debugging is still possible, and source mode is disabled.
    • host_type @anchor host_type Return `configure` system information, including the machine-id for which YAP was compiled and Operating System information.
    • index @anchor index_yap_flag If `on` allow indexing (default), if `off` disable it, if `single` allow on first argument only.
    • index_sub_term_search_depth @anchor index_sub_term_yap_flag Maximum bound on searching sub-terms for indexing, if `0` (default) no bound.
    • informational_messages @anchor informational_messages If `on` allow printing of informational messages, such as the ones that are printed when consulting. If `off` disable printing these messages. It is `on` by default except if YAP is booted with the `-L` flag.
    • integer_rounding_function [ISO] @anchor integer_rounding_function Read-only flag telling the rounding function used for integers. Takes the value `toward_zero` for the current version of YAP.
    • language @anchor language Choose whether YAP is closer to C-Prolog, `cprolog`, iso-prolog, `iso` or SICStus Prolog, `sicstus`. The current default is `cprolog`. This flag affects update semantics, leashing mode, style checking, handling calls to undefined procedures, how directives are interpreted, when to use dynamic, character escapes, and how files are consulted.
    • max_arity [ISO] @anchor max_arity Read-only flag telling the maximum arity of a functor. Takes the value `unbounded` for the current version of YAP.
    • max_integer [ISO] @anchor max_integer Read-only flag telling the maximum integer in the implementation. Depends on machine and Operating System architecture, and on whether YAP uses the `GMP` multi-precision library. If [bounded](@ref bounded) is false, requests for [max_integer](@ref max_integer) will fail.
    • max_tagged_integer @anchor max_tagged_integer Read-only flag telling the maximum integer we can store as a single word. Depends on machine and Operating System architecture. It can be used to find the word size of the current machine.
    • min_integer [ISO] @anchor min_integer Read-only flag telling the minimum integer in the implementation. Depends on machine and Operating System architecture, and on whether YAP uses the `GMP` multi-precision library. If [bounded](@ref bounded) is false, requests for [min_integer](@ref min_integer) will fail.
    • min_tagged_integer @anchor min_tagged_integer Read-only flag telling the minimum integer we can store as a single word. Depends on machine and Operating System architecture.
    • n_of_integer_keys_in_bb @anchor n_of_integer_keys_in_bb Read or set the size of the hash table that is used for looking up the blackboard when the key is an integer.
    • occurs_check @anchor occurs_check Current read-only and set to `false`.
    • n_of_integer_keys_in_db @anchor n_of_integer_keys_in_db Read or set the size of the hash table that is used for looking up the internal data-base when the key is an integer.
    • open_expands_filename @anchor open_expands_filename If `true` the [open/3](@ref open) builtin performs filename-expansion before opening a file (SICStus Prolog like). If `false` it does not (SWI-Prolog like).
    • open_shared_object @anchor open_shared_object If true, `open_shared_object/2` and friends are implemented, providing access to shared libraries (`.so` files) or to dynamic link libraries (`.DLL` files).
    • profiling @anchor profiling If `off` (default) do not compile profiling information for procedures. If `on` compile predicates so that they will output profiling information. Profiling data can be read through the [profile_data/3](@ref profile_data) built-in.
    • prompt_alternatives_on(atom, changeable) @anchor prompt_alternatives_on SWI-Compatible option, determines prompting for alternatives in the Prolog toplevel. Default is groundness, YAP prompts for alternatives if and only if the query contains variables. The alternative, default in SWI-Prolog is determinism which implies the system prompts for alternatives if the goal succeeded while leaving choicepoints.
    • redefine_warnings @anchor redefine_warnings If _Value_ is unbound, tell whether warnings for procedures defined in several different files are `on` or `off`. If _Value_ is bound to `on` enable these warnings, and if it is bound to `off` disable them. The default for YAP is `off`, unless we are in `sicstus` or `iso` mode.
    • shared_object_search_path @anchor shared_object_search_path Name of the environment variable used by the system to search for shared objects.
    • shared_object_extension @anchor shared_object_extension Suffix associated with loadable code.
    • single_var_warnings @anchor single_var_warnings If _Value_ is unbound, tell whether warnings for singleton variables are `on` or `off`. If _Value_ is bound to `on` enable these warnings, and if it is bound to `off` disable them. The default for YAP is `off`, unless we are in `sicstus` or `iso` mode.
    • strict_iso @anchor strict_iso If _Value_ is unbound, tell whether strict ISO compatibility mode is `on` or `off`. If _Value_ is bound to `on` set language mode to `iso` and enable strict mode. If _Value_ is bound to `off` disable strict mode, and keep the current language mode. The default for YAP is `off`. Under strict ISO Prolog mode all calls to non-ISO built-ins generate an error. Compilation of clauses that would call non-ISO built-ins will also generate errors. Pre-processing for grammar rules is also disabled. Module expansion is still performed. Arguably, ISO Prolog does not provide all the functionality required from a modern Prolog system. Moreover, because most Prolog implementations do not fully implement the standard and because the standard itself gives the implementor latitude in a few important questions, such as the unification algorithm and maximum size for numbers there is no guarantee that programs compliant with this mode will work the same way in every Prolog and in every platform. We thus believe this mode is mostly useful when investigating how a program depends on a Prolog's platform specific features.
    • stack_dump_on_error @anchor stack_dump_on_error If `on` show a stack dump when YAP finds an error. The default is `off`.
    • syntax_errors Control action to be taken after syntax errors while executing [read/1](@ref read), `read/2`, or `read_term/3`:
      • dec10 Report the syntax error and retry reading the term.
      • fail Report the syntax error and fail (default).
      • error Report the syntax error and generate an error.
      • quiet Just fail
    • system_options @anchor system_options This read only flag tells which options were used to compile YAP. Currently it informs whether the system supports `big_numbers`, `coroutining`, `depth_limit`, `low_level_tracer`, `or-parallelism`, `rational_trees`, `readline`, `tabling`, `threads`, or the `wam_profiler`.
    • tabling_mode Sets or reads the tabling mode for all tabled predicates. Please (see [Tabling](@ref Tabling)) for the list of options.
    • to_chars_mode @anchor to_chars_modes Define whether YAP should follow `quintus`-like semantics for the `atom_chars/1` or `number_chars/1` built-in, or whether it should follow the ISO standard (`iso` option).
    • toplevel_hook @anchor toplevel_hook +If bound, set the argument to a goal to be executed before entering the top-level. If unbound show the current goal or `true` if none is presented. Only the first solution is considered and the goal is not backtracked into.
    • toplevel_print_options @anchor toplevel_print_options +If bound, set the argument to the `write_term/3` options used to write terms from the top-level. If unbound, show the current options.
    • typein_module @anchor typein_module If bound, set the current working or type-in module to the argument, which must be an atom. If unbound, unify the argument with the current working module.
    • unix Read-only Boolean flag that unifies with `true` if YAP is running on an Unix system. Defined if the C-compiler used to compile this version of YAP either defines `__unix__` or `unix`.
    • unknown [ISO] Corresponds to calling the [unknown/2](@ref unknown) built-in. Possible values are `error`, `fail`, and `warning`.
    • update_semantics @anchor update_semantics Define whether YAP should follow `immediate` update semantics, as in C-Prolog (default), `logical` update semantics, as in Quintus Prolog, SICStus Prolog, or in the ISO standard. There is also an intermediate mode, `logical_assert`, where dynamic procedures follow logical semantics but the internal data base still follows immediate semantics.
    • user_error @anchor user_error If the second argument is bound to a stream, set [user_error](@ref user_error) to this stream. If the second argument is unbound, unify the argument with the current [user_error](@ref user_error) stream. By default, the [user_error](@ref user_error) stream is set to a stream corresponding to the Unix `stderr` stream. The next example shows how to use this flag: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ?- open( '/dev/null', append, Error, [alias(mauri_tripa)] ). Error = '$stream'(3) ? ; no ?- set_prolog_flag(user_error, mauri_tripa). close(mauri_tripa). yes ?- ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ We execute three commands. First, we open a stream in write mode and give it an alias, in this case `mauri_tripa`. Next, we set [user_error](@ref user_error) to the stream via the alias. Note that after we did so prompts from the system were redirected to the stream `mauri_tripa`. Last, we close the stream. At this point, YAP automatically redirects the [user_error](@ref user_error) alias to the original `stderr`.
    • user_flags @anchor user_flags Define the behaviour of [set_prolog_flag/2](@ref set_prolog_flag) if the flag is not known. Values are `silent`, `warning` and `error`. The first two create the flag on-the-fly, with `warning` printing a message. The value `error` is consistent with ISO: it raises an existence error and does not create the flag. See also `create_prolog_flag/3`. The default is`error`, and developers are encouraged to use `create_prolog_flag/3` to create flags for their library.
    • user_input @anchor user_input If the second argument is bound to a stream, set [user_input](@ref user_input) to this stream. If the second argument is unbound, unify the argument with the current [user_input](@ref user_input) stream. By default, the [user_input](@ref user_input) stream is set to a stream corresponding to the Unix `stdin` stream.
    • user_output @anchor user_output If the second argument is bound to a stream, set [user_output](@ref user_output) to this stream. If the second argument is unbound, unify the argument with the current [user_output](@ref user_output) stream. By default, the [user_output](@ref user_output) stream is set to a stream corresponding to the Unix `stdout` stream.
    • verbose @anchor verbose If `normal` allow printing of informational and banner messages, such as the ones that are printed when consulting. If `silent` disable printing these messages. It is `normal` by default except if YAP is booted with the `-q` or `-L` flag.
    • verbose_load @anchor verbose_load If `true` allow printing of informational messages when consulting files. If `false` disable printing these messages. It is `normal` by default except if YAP is booted with the `-L` flag.
    • version @anchor version Read-only flag that returns an atom with the current version of YAP.
    • version_data @anchor version_data Read-only flag that reads a term of the form `yap`( _Major_, _Minor_, _Patch_, _Undefined_), where _Major_ is the major version, _Minor_ is the minor version, and _Patch_ is the patch number.
    • windows @anchor windoes Read-only boolean flag that unifies with tr `true` if YAP is running on an Windows machine.
    • write_strings @anchor write_strings Writable flag telling whether the system should write lists of integers that are writable character codes using the list notation. It is `on` if enables or `off` if disabled. The default value for this flag is `off`.
    • max_workers @anchor max_workers Read-only flag telling the maximum number of parallel processes.
    • max_threads @anchor max_threads Read-only flag telling the maximum number of Prolog threads that can be created.
  • current_prolog_flag(? _Flag_,- _Value_) [ISO] @anchor current_prolog_flag Obtain the value for a YAP Prolog flag. Equivalent to calling [yap_flag/2](@ref yap_flag) with the second argument unbound, and unifying the returned second argument with _Value_.
  • prolog_flag(? _Flag_,- _OldValue_,+ _NewValue_) @anchor prolog_flag Obtain the value for a YAP Prolog flag and then set it to a new value. Equivalent to first calling [current_prolog_flag/2](@ref current_prolog_flag) with the second argument _OldValue_ unbound and then calling [set_prolog_flag/2](@ref set_prolog_flag) with the third argument _NewValue_.
  • set_prolog_flag(+ _Flag_,+ _Value_) [ISO] @anchor set_prolog_flag Set the value for YAP Prolog flag `Flag`. Equivalent to calling [yap_flag/2](@ref yap_flag) with both arguments bound.
  • create_prolog_flag(+ _Flag_,+ _Value_,+ _Options_) @anchor create_prolog_flag Create a new YAP Prolog flag. _Options_ include `type(+Type)` and `access(+Access)` with _Access_ one of `read_only` or `read_write` and _Type_ one of `boolean`, `integer`, `float`, `atom` and `term` (that is, no type).
  • op(+ _P_,+ _T_,+ _A_) [ISO] @anchor op Defines the operator _A_ or the list of operators _A_ with type _T_ (which must be one of `xfx`, `xfy`,`yfx`, `xf`, `yf`, `fx` or `fy`) and precedence _P_ (see appendix iv for a list of predefined operators). Note that if there is a preexisting operator with the same name and type, this operator will be discarded. Also, `','` may not be defined as an operator, and it is not allowed to have the same for an infix and a postfix operator.
  • current_op( _P_, _T_, _F_) [ISO] @anchor current_op Defines the relation: _P_ is a currently defined operator of type _T_ and precedence _P_.
  • prompt(- _A_,+ _B_) @anchor prompt Changes YAP input prompt from _A_ to _B_.
  • initialization Execute the goals defined by initialization/1. Only the first answer is considered.
  • prolog_initialization( _G_) @anchor prolog_initialization Add a goal to be executed on system initialization. This is compatible with SICStus Prolog's [initialization/1](@ref initialization).
  • version Write YAP's boot message.
  • version(- _Message_) Add a message to be written when yap boots or after aborting. It is not possible to remove messages.
  • prolog_load_context(? _Key_, ? _Value_) @anchor prolog_load_context Obtain information on what is going on in the compilation process. The following keys are available:
    • directory @anchor directory_prolog_load_context Full name for the directory where YAP is currently consulting the file.
    • file @anchor file_prolog_load_context Full name for the file currently being consulted. Notice that included filed are ignored.
    • module @anchor module_prolog_load_context Current source module.
    • source (prolog_load_context/2 option) @anchor source_prolog_load_context Full name for the file currently being read in, which may be consulted, reconsulted, or included.
    • stream @anchor stream_prolog_load_context Stream currently being read in.
    • term_position @anchor term_position_prolog_load_context Stream position at the stream currently being read in. For SWI compatibility, it is a term of the form `'$stream_position'(0,Line,0,0,0)`.
  • source_location(? _FileName_, ? _Line_) @anchor source_location SWI-compatible predicate. If the last term has been read from a physical file (i.e., not from the file user or a string), unify File with an absolute path to the file and Line with the line-number in the file. Please use [prolog_load_context/2](@ref prolog_load_context).
  • source_file(? _File_) @anchor source_file SWI-compatible predicate. True if _File_ is a loaded Prolog source file.
  • source_file(? _ModuleAndPred_,? _File_) SWI-compatible predicate. True if the predicate specified by _ModuleAndPred_ was loaded from file _File_, where _File_ is an absolute path name (see `absolute_file_name/2`).
@page Library Library Predicates Library files reside in the library_directory path (set by the `LIBDIR` variable in the Makefile for YAP). Currently, most files in the library are from the Edinburgh Prolog library. @section Aggregate Aggregate This is the SWI-Prolog library based on the Quintus and SICStus 4 library. @c To be done - Analysing the aggregation template This library provides aggregating operators over the solutions of a predicate. The operations are a generalisation of the [bagof/3](@ref bagof), [setof/3](@ref setof) and [findall/3](@ref findall) built-in predicates. The defined aggregation operations are counting, computing the sum, minimum, maximum, a bag of solutions and a set of solutions. We first give a simple example, computing the country with the smallest area: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~{.prolog} smallest_country(Name, Area) :- aggregate(min(A, N), country(N, A), min(Area, Name)). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ There are four aggregation predicates, distinguished on two properties.
  • aggregate vs. aggregate_all The aggregate predicates use setof/3 (aggregate/4) or bagof/3 (aggregate/3), dealing with existential qualified variables ( _Var_/\\ _Goal_) and providing multiple solutions for the remaining free variables in _Goal_. The aggregate_all/3 predicate uses findall/3, implicitly qualifying all free variables and providing exactly one solution, while aggregate_all/4 uses sort/2 over solutions and Distinguish (see below) generated using findall/3.
  • The _Distinguish_ argument The versions with 4 arguments provide a _Distinguish_ argument that allow for keeping duplicate bindings of a variable in the result. For example, if we wish to compute the total population of all countries we do not want to lose results because two countries have the same population. Therefore we use: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~{.prolog} aggregate(sum(P), Name, country(Name, P), Total) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
All aggregation predicates support the following operator below in _Template_. In addition, they allow for an arbitrary named compound term where each of the arguments is a term from the list below. I.e. the term `r(min(X), max(X))` computes both the minimum and maximum binding for _X_.
  • count Count number of solutions. Same as `sum(1)`.
  • sum( _Expr_) Sum of _Expr_ for all solutions.
  • min( _Expr_) Minimum of _Expr_ for all solutions.
  • min( _Expr_, _Witness_) A term min( _Min_, _Witness_), where _Min_ is the minimal version of _Expr_ over all Solution and _Witness_ is any other template applied to Solution that produced _Min_. If multiple solutions provide the same minimum, _Witness_ corresponds to the first solution.
  • max( _Expr_) Maximum of _Expr_ for all solutions.
  • max( _Expr_, _Witness_) As min( _Expr_, _Witness_), but producing the maximum result.
  • set( _X_) An ordered set with all solutions for _X_.
  • bag( _X_) A list of all solutions for _X_.
The predicates are:
  • [nondet]aggregate(+ _Template_, : _Goal_, - _Result_) @anchor aggregate Aggregate bindings in _Goal_ according to _Template_. The aggregate/3 version performs bagof/3 on _Goal_.
  • [nondet]aggregate(+ _Template_, + _Discriminator_, : _Goal_, - _Result_) Aggregate bindings in _Goal_ according to _Template_. The aggregate/3 version performs setof/3 on _Goal_.
  • [semidet]aggregate_all(+ _Template_, : _Goal_, - _Result_) @anchor aggregate_all Aggregate bindings in _Goal_ according to _Template_. The aggregate_all/3 version performs findall/3 on _Goal_.
  • [semidet]aggregate_all(+ _Template_, + _Discriminator_, : _Goal_, - _Result_) Aggregate bindings in _Goal_ according to _Template_. The aggregate_all/3 version performs findall/3 followed by sort/2 on _Goal_.
  • foreach(:Generator, : _Goal_) @anchor foreach True if the conjunction of instances of _Goal_ using the bindings from Generator is true. Unlike forall/2, which runs a failure-driven loop that proves _Goal_ for each solution of Generator, foreach creates a conjunction. Each member of the conjunction is a copy of _Goal_, where the variables it shares with Generator are filled with the values from the corresponding solution. The implementation executes forall/2 if _Goal_ does not contain any variables that are not shared with Generator. Here is an example: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~{.prolog} ?- foreach(between(1,4,X), dif(X,Y)), Y = 5. Y = 5 ?- foreach(between(1,4,X), dif(X,Y)), Y = 3. No ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Notice that _Goal_ is copied repeatedly, which may cause problems if attributed variables are involved.
  • [det]free_variables(:Generator, + _Template_, +VarList0, -VarList) @anchor free_variables In order to handle variables properly, we have to find all the universally quantified variables in the Generator. All variables as yet unbound are universally quantified, unless
    1. they occur in the template
    2. they are bound by X/\\P, setof, or bagof
    `free_variables(Generator, Template, OldList, NewList)` finds this set, using OldList as an accumulator.
The original author of this code was Richard O'Keefe. Jan Wielemaker made some SWI-Prolog enhancements, sponsored by SecuritEase, http://www.securitease.com. The code is public domain (from DEC10 library). @section Apply Apply Macros This library provides a SWI-compatible set of utilities for applying a predicate to all elements of a list. The library just forwards definitions from the `maplist` library. @section Association_Lists Association Lists The following association list manipulation predicates are available once included with the `use_module(library(assoc))` command. The original library used Richard O'Keefe's implementation, on top of unbalanced binary trees. The current code utilises code from the red-black trees library and emulates the SICStus Prolog interface.
  • assoc_to_list(+ _Assoc_,? _List_) @anchor assoc_to_list Given an association list _Assoc_ unify _List_ with a list of the form _Key-Val_, where the elements _Key_ are in ascending order.
  • del_assoc(+ _Key_, + _Assoc_, ? _Val_, ? _NewAssoc_) @anchor del_assoc Succeeds if _NewAssoc_ is an association list, obtained by removing the element with _Key_ and _Val_ from the list _Assoc_.
  • del_max_assoc(+ _Assoc_, ? _Key_, ? _Val_, ? _NewAssoc_) @anchor del_max_assoc Succeeds if _NewAssoc_ is an association list, obtained by removing the largest element of the list, with _Key_ and _Val_ from the list _Assoc_.
  • del_min_assoc(+ _Assoc_, ? _Key_, ? _Val_, ? _NewAssoc_) @anchor del_min_assoc Succeeds if _NewAssoc_ is an association list, obtained by removing the smallest element of the list, with _Key_ and _Val_ from the list _Assoc_.
  • empty_assoc(+ _Assoc_) @anchor empty_assoc Succeeds if association list _Assoc_ is empty.
  • gen_assoc(+ _Assoc_,? _Key_,? _Value_) @anchor gen_assoc Given the association list _Assoc_, unify _Key_ and _Value_ with two associated elements. It can be used to enumerate all elements in the association list.
  • get_assoc(+ _Key_,+ _Assoc_,? _Value_) @anchor get_next_assoc If _Key_ is one of the elements in the association list _Assoc_, return the associated value.
  • get_assoc(+ _Key_,+ _Assoc_,? _Value_,+ _NAssoc_,? _NValue_) @anchor get_assoc If _Key_ is one of the elements in the association list _Assoc_, return the associated value _Value_ and a new association list _NAssoc_ where _Key_ is associated with _NValue_.
  • get_prev_assoc(+ _Key_,+ _Assoc_,? _Next_,? _Value_) @anchor get_prev_assoc If _Key_ is one of the elements in the association list _Assoc_, return the previous key, _Next_, and its value, _Value_.
  • get_next_assoc(+ _Key_,+ _Assoc_,? _Next_,? _Value_) If _Key_ is one of the elements in the association list _Assoc_, return the next key, _Next_, and its value, _Value_.
  • is_assoc(+ _Assoc_) @anchor is_assoc Succeeds if _Assoc_ is an association list, that is, if it is a red-black tree.
  • list_to_assoc(+ _List_,? _Assoc_) @anchor list_to_assoc Given a list _List_ such that each element of _List_ is of the form _Key-Val_, and all the _Keys_ are unique, _Assoc_ is the corresponding association list.
  • map_assoc(+ _Pred_,+ _Assoc_) @anchor map_assoc Succeeds if the unary predicate name _Pred_( _Val_) holds for every element in the association list.
  • map_assoc(+ _Pred_,+ _Assoc_,? _New_) Given the binary predicate name _Pred_ and the association list _Assoc_, _New_ in an association list with keys in _Assoc_, and such that if _Key-Val_ is in _Assoc_, and _Key-Ans_ is in _New_, then _Pred_( _Val_, _Ans_) holds.
  • max_assoc(+ _Assoc_,- _Key_,? _Value_) @anchor max_assoc Given the association list _Assoc_, _Key_ in the largest key in the list, and _Value_ the associated value.
  • min_assoc(+ _Assoc_,- _Key_,? _Value_) @anchor min_assoc Given the association list _Assoc_, _Key_ in the smallest key in the list, and _Value_ the associated value.
  • ord_list_to_assoc(+ _List_,? _Assoc_) @anchor ord_list_to_assoc Given an ordered list _List_ such that each element of _List_ is of the form _Key-Val_, and all the _Keys_ are unique, _Assoc_ is the corresponding association list.
  • put_assoc(+ _Key_,+ _Assoc_,+ _Val_,+ _New_) @anchor put_assoc The association list _New_ includes and element of association _key_ with _Val_, and all elements of _Assoc_ that did not have key _Key_.
@section AVL_Trees AVL Trees AVL trees are balanced search binary trees. They are named after their inventors, Adelson-Velskii and Landis, and they were the first dynamically balanced trees to be proposed. The YAP AVL tree manipulation predicates library uses code originally written by Martin van Emdem and published in the Logic Programming Newsletter, Autumn 1981. A bug in this code was fixed by Philip Vasey, in the Logic Programming Newsletter, Summer 1982. The library currently only includes routines to insert and lookup elements in the tree. Please try red-black trees if you need deletion.
  • avl_new(+ _T_) @anchor avl_new Create a new tree.
  • avl_insert(+ _Key_,? _Value_,+ _T0_,- _TF_) @anchor avl_insert Add an element with key _Key_ and _Value_ to the AVL tree _T0_ creating a new AVL tree _TF_. Duplicated elements are allowed.
  • avl_lookup(+ _Key_,- _Value_,+ _T_) @anchor avl_lookup Lookup an element with key _Key_ in the AVL tree _T_, returning the value _Value_.
@section Exo_Intervals Exo Intervals This package assumes you use exo-compilation, that is, that you loaded the pedicate using the `exo` option to [load_files/2](@ref load_files), In this case, YAP includes a package for improved search on intervals of integers. The package is activated by `udi` declarations that state what is the argument of interest: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~{.prolog} :- udi(diagnoses(exo_interval,?,?)). :- load_files(db, [consult(exo)]). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ It is designed to optimise the following type of queries: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~{.prolog} ?- max(X, diagnoses(X, 9, Y), X). ?- min(X, diagnoses(X, 9, 36211117), X). ?- X #< Y, min(X, diagnoses(X, 9, 36211117), X ), diagnoses(Y, 9, _). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ The first argument gives the time, the second the patient, and the third the condition code. The first query should find the last time the patient 9 had any code reported, the second looks for the first report of code 36211117, and the last searches for reports after this one. All queries run in constant or log(n) time. @section Gecode Gecode Interface The gecode library intreface was designed and implemented by Denis Duchier, with recent work by Vítor Santos Costa to port it to version 4 of gecode and to have an higher level interface, @subsection The_Gecode_Interface The Gecode Interface This text is due to Denys Duchier. The gecode interface requires ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~{.prolog} :- use_module(library(gecode)). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Several example programs are available with the distribution.
  • CREATING A SPACE A space is gecodes data representation for a store of constraints: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~{.prolog} Space := space ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  • CREATING VARIABLES Unlike in Gecode, variable objects are not bound to a specific Space. Each one actually contains an index with which it is possible to access a Space-bound Gecode variable. Variables can be created using the following expressions: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~{.prolog} IVar := intvar(Space,SPEC...) BVar := boolvar(Space) SVar := setvar(Space,SPEC...) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ where SPEC... is the same as in Gecode. For creating lists of variables use the following variants: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~{.prolog} IVars := intvars(Space,N,SPEC...) BVars := boolvars(Space,N,SPEC...) SVars := setvars(Space,N,SPEC...) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ where N is the number of variables to create (just like for XXXVarArray in Gecode). Sometimes an IntSet is necessary: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~{.prolog} ISet := intset([SPEC...]) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ where each SPEC is either an integer or a pair (I,J) of integers. An IntSet describes a set of ints by providing either intervals, or integers (which stand for an interval of themselves). It might be tempting to simply represent an IntSet as a list of specs, but this would be ambiguous with IntArgs which, here, are represented as lists of ints. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~{.prolog} Space += keep(Var) Space += keep(Vars) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Variables can be marked as "kept". In this case, only such variables will be explicitly copied during search. This could bring substantial benefits in memory usage. Of course, in a solution, you can then only look at variables that have been "kept". If no variable is marked as "kept", then they are all kept. Thus marking variables as "kept" is purely an optimization.
  • CONSTRAINTS AND BRANCHINGS all constraint and branching posting functions are available just like in Gecode. Wherever a XXXArgs or YYYSharedArray is expected, simply use a list. At present, there is no support for minimodel-like constraint posting. Constraints and branchings are added to a space using: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~{.prolog} Space += CONSTRAINT Space += BRANCHING ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ For example: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~{.prolog} Space += rel(X,'IRT_EQ',Y) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ arrays of variables are represented by lists of variables, and constants are represented by atoms with the same name as the Gecode constant (e.g. 'INT_VAR_SIZE_MIN').
  • SEARCHING FOR SOLUTIONS ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~{.prolog} SolSpace := search(Space) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ This is a backtrackable predicate that enumerates all solution spaces (SolSpace). It may also take options: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~{.prolog} SolSpace := search(Space,Options) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Options is a list whose elements maybe:
    • restart to select the Restart search engine
    • threads=N to activate the parallel search engine and control the number of workers (see Gecode doc)
    • c_d=N to set the commit distance for recomputation
    • a_d=N to set the adaptive distance for recomputation
  • EXTRACTING INFO FROM A SOLUTION An advantage of non Space-bound variables, is that you can use them both to post constraints in the original space AND to consult their values in solutions. Below are methods for looking up information about variables. Each of these methods can either take a variable as argument, or a list of variables, and returns resp. either a value, or a list of values: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~{.prolog} Val := assigned(Space,X) Val := min(Space,X) Val := max(Space,X) Val := med(Space,X) Val := val(Space,X) Val := size(Space,X) Val := width(Space,X) Val := regret_min(Space,X) Val := regret_max(Space,X) Val := glbSize(Space,V) Val := lubSize(Space,V) Val := unknownSize(Space,V) Val := cardMin(Space,V) Val := cardMax(Space,V) Val := lubMin(Space,V) Val := lubMax(Space,V) Val := glbMin(Space,V) Val := glbMax(Space,V) Val := glb_ranges(Space,V) Val := lub_ranges(Space,V) Val := unknown_ranges(Space,V) Val := glb_values(Space,V) Val := lub_values(Space,V) Val := unknown_values(Space,V) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  • DISJUNCTORS Disjunctors provide support for disjunctions of clauses, where each clause is a conjunction of constraints: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~{.prolog} C1 or C2 or ... or Cn ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Each clause is executed "speculatively": this means it does not affect the main space. When a clause becomes failed, it is discarded. When only one clause remains, it is committed: this means that it now affects the main space. Example: Consider the problem where either X=Y=0 or X=Y+(1 or 2) for variable X and Y that take values in 0..3. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~{.prolog} Space := space, [X,Y] := intvars(Space,2,0,3), ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ First, we must create a disjunctor as a manager for our 2 clauses: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~{.prolog} Disj := disjunctor(Space), ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ We can now create our first clause: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~{.prolog} C1 := clause(Disj), ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ This clause wants to constrain X and Y to 0. However, since it must be executed "speculatively", it must operate on new variables X1 and Y1 that shadow X and Y: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~{.prolog} [X1,Y1] := intvars(C1,2,0,3), C1 += forward([X,Y],[X1,Y1]), ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ The forward(...) stipulation indicates which global variable is shadowed by which clause-local variable. Now we can post the speculative clause-local constraints for X=Y=0: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~{.prolog} C1 += rel(X1,'IRT_EQ',0), C1 += rel(Y1,'IRT_EQ',0), ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ We now create the second clause which uses X2 and Y2 to shadow X and Y: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~{.prolog} C2 := clause(Disj), [X2,Y2] := intvars(C2,2,0,3), C2 += forward([X,Y],[X2,Y2]), ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ However, this clause also needs a clause-local variable Z2 taking values 1 or 2 in order to post the clause-local constraint X2=Y2+Z2: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~{.prolog} Z2 := intvar(C2,1,2), C2 += linear([-1,1,1],[X2,Y2,Z2],'IRT_EQ',0), ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Finally, we can branch and search: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~{.prolog} Space += branch([X,Y],'INT_VAR_SIZE_MIN','INT_VAL_MIN'), SolSpace := search(Space), ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ and lookup values of variables in each solution: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~{.prolog} [X_,Y_] := val(SolSpace,[X,Y]). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
@subsection Gecode_and_ClPbBFDbC Programming Finite Domain Constraints in YAP/Gecode The gecode/clp(fd) interface is designed to use the GECODE functionality in a more CLP like style. It requires ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~{.prolog} :- use_module(library(gecode/clpfd)). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Several example programs are available with the distribution. Integer variables are declared as:
  • _V_ in _A_.. _B_ declares an integer variable _V_ with range _A_ to _B_.
  • _Vs_ ins _A_.. _B_ declares a set of integer variabless _Vs_ with range _A_ to _B_.
  • boolvar( _V_) declares a boolean variable.
  • boolvars( _Vs_) declares a set of boolean variable.
Constraints supported are:
  • _X_ #= _Y_ equality
  • _X_ #\\= _Y_ disequality
  • _X_ #\> _Y_ larger
  • _X_ #\>= _Y_ larger or equal
  • _X_ #=\< _Y_ smaller
  • _X_ #\< _Y_ smaller or equal Arguments to this constraint may be an arithmetic expression with +, -, \\\*, integer division /, min, max, sum, count, and abs. Boolean variables support conjunction (/\\), disjunction (\\/), implication (=\>), equivalence (\<=\>), and xor. The sum constraint allows a two argument version using the `where` conditional, in Zinc style. The send more money equation may be written as: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~{.prolog} 1000*S + 100*E + 10*N + D + 1000*M + 100*O + 10*R + E #= 10000*M + 1000*O + 100*N + 10*E + Y, ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ This example uses `where` to select from column _I_ the elements that have value under _M_: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~{.prolog} OutFlow[I] #= sum(J in 1..N where D[J,I]count constraint counts the number of elements that match a certain constant or variable (integer sets are not available).
  • all_different( _Vs_ )
  • all_distinct( _Vs_)
  • all_different( _Cs_, _Vs_)
  • all_distinct( _Cs_, _Vs_) verifies whether all elements of a list are different. In the second case, tests if all the sums between a list of constants and a list of variables are different. This is a formulation of the queens problem that uses both versions of `all_different`: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~{.prolog} queens(N, Queens) :- length(Queens, N), Queens ins 1..N, all_distinct(Queens), foldl(inc, Queens, Inc, 0, _), % [0, 1, 2, .... ] foldl(dec, Queens, Dec, 0, _), % [0, -1, -2, ... ] all_distinct(Inc,Queens), all_distinct(Dec,Queens), labeling([], Queens). inc(_, I0, I0, I) :- I is I0+1. dec(_, I0, I0, I) :- I is I0-1. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ The next example uses `all_different/1` and the functionality of the matrix package to verify that all squares in sudoku have a different value: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~{.prolog} foreach( [I,J] ins 0..2 , all_different(M[I*3+(0..2),J*3+(0..2)]) ), ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  • scalar_product(+ _Cs_, + _Vs_, + _Rel_, ? _V_ ) The product of constant _Cs_ by _Vs_ must be in relation _Rel_ with _V_ .
  • _X_ #= all elements of _X_ must take the same value
  • _X_ #\\= not all elements of _X_ take the same value
  • _X_ #\> elements of _X_ must be increasing
  • _X_ #\>= elements of _X_ must be increasinga or equal
  • _X_ #=\< elements of _X_ must be decreasing
  • _X_ #\< elements of _X_ must be decreasing or equal
  • _X_ #\<==\> _B_ reified equivalence
  • _X_ #==\> _B_ reified implication
  • _X_ #\< _B_ reified implication As an example. consider finding out the people who wanted to sit next to a friend and that are are actually sitting together: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~{.prolog} preference_satisfied(X-Y, B) :- abs(X - Y) #= 1 #<==> B. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Note that not all constraints may be reifiable.
  • element( _X_, _Vs_ ) _X_ is an element of list _Vs_
  • clause( _Type_, _Ps_ , _Ns_, _V_ ) If _Type_ is `and` it is the conjunction of boolean variables _Ps_ and the negation of boolean variables _Ns_ and must have result _V_. If _Type_ is `or` it is a disjunction.
  • DFA the interface allows creating and manipulation deterministic finite automata. A DFA has a set of states, represented as integers and is initialised with an initial state, a set of transitions from the first to the last argument emitting the middle argument, and a final state. The swedish-drinkers protocol is represented as follows: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~{.prolog} A = [X,Y,Z], dfa( 0, [t(0,0,0),t(0,1,1),t(1,0,0),t(-1,0,0)], [0], C), in_dfa( A, C ), ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ This code will enumeratae the valid tuples of three emissions.
  • extensional constraints Constraints can also be represented as lists of tuples. The previous example would be written as: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~{.prolog} extensional_constraint([[0,0,0],[0,1,0],[1,0,0]], C), in_relation( A, C ), ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  • minimum( _X_, _Vs_)
  • min( _X_, _Vs_) First Argument is the least element of a list.
  • maximum( _X_, _Vs_)
  • max( _X_, _Vs_) First Argument is the greatest element of a list.
  • lex_order( _Vs_) All elements must be ordered.
The following predicates control search:
  • labeling( _Opts_, _Xs_) performs labeling, several variable and value selection options are available. The defaults are `min` and `min_step`. Variable selection options are as follows:
    • leftmost choose the first variable
    • min choose one of the variables with smallest minimum value
    • max choose one of the variables with greatest maximum value
    • ff choose one of the most constrained variables, that is, with the smallest domain.
    Given that we selected a variable, the values chosen for branching may be:
    • min_step smallest value
    • max_step largest value
    • bisect median
    • enum all value starting from the minimum.
  • maximize( _V_) maximise variable _V_
  • minimize(V) minimise variable _V_
@section Heaps Heaps A heap is a labelled binary tree where the key of each node is less than or equal to the keys of its sons. The point of a heap is that we can keep on adding new elements to the heap and we can keep on taking out the minimum element. If there are N elements total, the total time is O(NlgN). If you know all the elements in advance, you are better off doing a merge-sort, but this file is for when you want to do say a best-first search, and have no idea when you start how many elements there will be, let alone what they are. The following heap manipulation routines are available once included with the `use_module(library(heaps))` command.
  • add_to_heap(+ _Heap_,+ _key_,+ _Datum_,- _NewHeap_) @anchor add_to_heap Inserts the new _Key-Datum_ pair into the heap. The insertion is not stable, that is, if you insert several pairs with the same _Key_ it is not defined which of them will come out first, and it is possible for any of them to come out first depending on the history of the heap.
  • empty_heap(? _Heap_) @anchor empty_heap Succeeds if _Heap_ is an empty heap.
  • get_from_heap(+ _Heap_,- _key_,- _Datum_,- _Heap_) @anchor get_from_heap Returns the _Key-Datum_ pair in _OldHeap_ with the smallest _Key_, and also a _Heap_ which is the _OldHeap_ with that pair deleted.
  • heap_size(+ _Heap_, - _Size_) @anchor heap_size Reports the number of elements currently in the heap.
  • heap_to_list(+ _Heap_, - _List_) @anchor heap_to_list Returns the current set of _Key-Datum_ pairs in the _Heap_ as a _List_, sorted into ascending order of _Keys_.
  • list_to_heap(+ _List_, - _Heap_) @anchor list_to_heap Takes a list of _Key-Datum_ pairs (such as keysort could be used to sort) and forms them into a heap.
  • min_of_heap(+ _Heap_, - _Key_, - _Datum_) @anchor min_of_heap Returns the Key-Datum pair at the top of the heap (which is of course the pair with the smallest Key), but does not remove it from the heap.
  • min_of_heap(+ _Heap_, - _Key1_, - _Datum1_, - _Key2_, - _Datum2_) Returns the smallest (Key1) and second smallest (Key2) pairs in the heap, without deleting them.
@section Lists List Manipulation The following list manipulation routines are available once included with the `use_module(library(lists))` command.
  • append(? _Prefix_,? _Suffix_,? _Combined_) @anchor append True when all three arguments are lists, and the members of _Combined_ are the members of _Prefix_ followed by the members of _Suffix_. It may be used to form _Combined_ from a given _Prefix_, _Suffix_ or to take a given _Combined_ apart.
  • append(? _Lists_,? _Combined_) Holds if the lists of _Lists_ can be concatenated as a _Combined_ list.
  • delete(+ _List_, ? _Element_, ? _Residue_) @anchor delete True when _List_ is a list, in which _Element_ may or may not occur, and _Residue_ is a copy of _List_ with all elements identical to _Element_ deleted.
  • flatten(+ _List_, ? _FlattenedList_) @anchor flatten Flatten a list of lists _List_ into a single list _FlattenedList_. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~{.prolog} ?- flatten([[1],[2,3],[4,[5,6],7,8]],L). L = [1,2,3,4,5,6,7,8] ? ; no ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  • last(+ _List_,? _Last_) @anchor last True when _List_ is a list and _Last_ is identical to its last element.
  • list_concat(+ _Lists_,? _List_) @anchor list_concat True when _Lists_ is a list of lists and _List_ is the concatenation of _Lists_.
  • member(? _Element_, ? _Set_) @anchor member True when _Set_ is a list, and _Element_ occurs in it. It may be used to test for an element or to enumerate all the elements by backtracking.
  • memberchk(+ _Element_, + _Set_) @anchor memberchk As [member/2](@ref member), but may only be used to test whether a known _Element_ occurs in a known Set. In return for this limited use, it is more efficient when it is applicable.
  • nth0(? _N_, ? _List_, ? _Elem_) @anchor nth0 True when _Elem_ is the Nth member of _List_, counting the first as element 0. (That is, throw away the first N elements and unify _Elem_ with the next.) It can only be used to select a particular element given the list and index. For that task it is more efficient than [member/2](@ref member)
  • nth1(? _N_, ? _List_, ? _Elem_) @anchor nth1 The same as [nth0/3](@ref nth0), except that it counts from 1, that is `nth(1, [H|_], H)`.
  • nth(? _N_, ? _List_, ? _Elem_) @anchor nth The same as [nth1/3](@ref nth1).
  • nth0(? _N_, ? _List_, ? _Elem_, ? _Rest_) Unifies _Elem_ with the Nth element of _List_, counting from 0, and _Rest_ with the other elements. It can be used to select the Nth element of _List_ (yielding _Elem_ and _Rest_), or to insert _Elem_ before the Nth (counting from 1) element of _Rest_, when it yields _List_, e.g. `nth0(2, List, c, [a,b,d,e])` unifies List with `[a,b,c,d,e]`. `nth/4` is the same except that it counts from 1. `nth0/4` can be used to insert _Elem_ after the Nth element of _Rest_.
  • nth1(? _N_, ? _List_, ? _Elem_, ? _Rest_) Unifies _Elem_ with the Nth element of _List_, counting from 1, and _Rest_ with the other elements. It can be used to select the Nth element of _List_ (yielding _Elem_ and _Rest_), or to insert _Elem_ before the Nth (counting from 1) element of _Rest_, when it yields _List_, e.g. `nth(3, List, c, [a,b,d,e])` unifies List with `[a,b,c,d,e]`. `nth/4` can be used to insert _Elem_ after the Nth element of _Rest_.
  • nth(? _N_, ? _List_, ? _Elem_, ? _Rest_) Same as `nth1/4`.
  • permutation(+ _List_,? _Perm_) @anchor permutation True when _List_ and _Perm_ are permutations of each other.
  • remove_duplicates(+ _List_, ? _Pruned_) @anchor remove_duplicates Removes duplicated elements from _List_. Beware: if the _List_ has non-ground elements, the result may surprise you.
  • reverse(+ _List_, ? _Reversed_) @anchor reverse True when _List_ and _Reversed_ are lists with the same elements but in opposite orders.
  • same_length(? _List1_, ? _List2_) @anchor same_length True when _List1_ and _List2_ are both lists and have the same number of elements. No relation between the values of their elements is implied. Modes `same_length(-,+)` and `same_length(+,-)` generate either list given the other; mode `same_length(-,-)` generates two lists of the same length, in which case the arguments will be bound to lists of length 0, 1, 2, ...
  • select(? _Element_, ? _List_, ? _Residue_) @anchor select True when _Set_ is a list, _Element_ occurs in _List_, and _Residue_ is everything in _List_ except _Element_ (things stay in the same order).
  • selectchk(? _Element_, ? _List_, ? _Residue_) @anchor selectchk Semi-deterministic selection from a list. Steadfast: defines as ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~{.prolog} selectchk(Elem, List, Residue) :- select(Elem, List, Rest0), !, Rest = Rest0. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  • sublist(? _Sublist_, ? _List_) @anchor sublist True when both `append(_,Sublist,S)` and `append(S,_,List)` hold.
  • suffix(? _Suffix_, ? _List_) @anchor suffix Holds when `append(_,Suffix,List)` holds.
  • sum_list(? _Numbers_, ? _Total_) @anchor sum_list True when _Numbers_ is a list of numbers, and _Total_ is their sum.
  • sum_list(? _Numbers_, + _SoFar_, ? _Total_) True when _Numbers_ is a list of numbers, and _Total_ is the sum of their total plus _SoFar_.
  • sumlist(? _Numbers_, ? _Total_) @anchor sumlist True when _Numbers_ is a list of integers, and _Total_ is their sum. The same as [sum_list/2](@ref sum_list), please do use [sum_list/2](@ref sum_list) instead.
  • max_list(? _Numbers_, ? _Max_) @anchor max_list True when _Numbers_ is a list of numbers, and _Max_ is the maximum.
  • min_list(? _Numbers_, ? _Min_) @anchor min_list True when _Numbers_ is a list of numbers, and _Min_ is the minimum.
  • numlist(+ _Low_, + _High_, + _List_) @anchor numlist If _Low_ and _High_ are integers with _Low_ =\< _High_, unify _List_ to a list `[Low, Low+1, ...High]`. See also [between/3](@ref between).
  • intersection(+ _Set1_, + _Set2_, + _Set3_) @anchor intersection Succeeds if _Set3_ unifies with the intersection of _Set1_ and _Set2_. _Set1_ and _Set2_ are lists without duplicates. They need not be ordered.
  • subtract(+ _Set_, + _Delete_, ? _Result_) @anchor subtract Delete all elements from _Set_ that occur in _Delete_ (a set) and unify the result with _Result_. Deletion is based on unification using [memberchk/2](@ref memberchk). The complexity is `|Delete|\*|Set|`. See [ord_subtract/3](@ref ord_subtract).
@section LineUtilities Line Manipulation Utilities This package provides a set of useful predicates to manipulate sequences of characters codes, usually first read in as a line. It is available by loading the library `library(lineutils)`.
  • search_for(+ _Char_,+ _Line_) @anchor search_for Search for a character _Char_ in the list of codes _Line_.
  • search_for(+ _Char_,+ _Line_,- _RestOfine_) Search for a character _Char_ in the list of codes _Line_, _RestOfLine_ has the line to the right.
  • scan_natural(? _Nat_,+ _Line_,+ _RestOfLine_) @anchor scan_natural Scan the list of codes _Line_ for a natural number _Nat_, zero or a positive integer, and unify _RestOfLine_ with the remainder of the line.
  • scan_integer(? _Int_,+ _Line_,+ _RestOfLine_) @anchor scan_integer Scan the list of codes _Line_ for an integer _Nat_, either a positive, zero, or negative integer, and unify _RestOfLine_ with the remainder of the line.
  • split(+ _Line_,+ _Separators_,- _Split_) @anchor split Unify _Words_ with a set of strings obtained from _Line_ by using the character codes in _Separators_ as separators. As an example, consider: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~{.prolog} ?- split("Hello * I am free"," *",S). S = ["Hello","I","am","free"] ? no ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  • split(+ _Line_,- _Split_) Unify _Words_ with a set of strings obtained from _Line_ by using the blank characters as separators.
  • fields(+ _Line_,+ _Separators_,- _Split_) @anchor fields Unify _Words_ with a set of strings obtained from _Line_ by using the character codes in _Separators_ as separators for fields. If two separators occur in a row, the field is considered empty. As an example, consider: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~{.prolog} ?- fields("Hello I am free"," *",S). S = ["Hello","","I","am","","free"] ? ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  • fields(+ _Line_,- _Split_) Unify _Words_ with a set of strings obtained from _Line_ by using the blank characters as field separators.
  • glue(+ _Words_,+ _Separator_,- _Line_) @anchor glue Unify _Line_ with string obtained by glueing _Words_ with the character code _Separator_.
  • copy_line(+ _StreamInput_,+ _StreamOutput_) @anchor copy_line Copy a line from _StreamInput_ to _StreamOutput_.
  • process(+ _StreamInp_, + _Goal_) @anchor process For every line _LineIn_ in stream _StreamInp_, call `call(Goal,LineIn)`.
  • filter(+ _StreamInp_, + _StreamOut_, + _Goal_) @anchor filter For every line _LineIn_ in stream _StreamInp_, execute `call(Goal,LineIn,LineOut)`, and output _LineOut_ to stream _StreamOut_.
  • file_filter(+ _FileIn_, + _FileOut_, + _Goal_) @anchor file_filter For every line _LineIn_ in file _FileIn_, execute `call(Goal,LineIn,LineOut)`, and output _LineOut_ to file _FileOut_.
  • file_filter(+ _FileIn_, + _FileOut_, + _Goal_, @anchor file_filter_with_init + _FormatCommand_, + _Arguments_) Same as [file_filter/3](@ref file_filter), but before starting the filter execute `format/3` on the output stream, using _FormatCommand_ and _Arguments_.
@section matrix Matrix Library This package provides a fast implementation of multi-dimensional matrices of integers and floats. In contrast to dynamic arrays, these matrices are multi-dimensional and compact. In contrast to static arrays. these arrays are allocated in the stack. Matrices are available by loading the library `library(matrix)`. They are multimensional objects of type:
  • terms: Prolog terms
  • ints: bounded integers, represented as an opaque term. The maximum integer depends on hardware, but should be obtained from the natural size of the machine.
  • floats: floating-poiny numbers, represented as an opaque term.
Matrix elements can be accessed through the `matrix_get/2` predicate or through an R-inspired access notation (that uses the ciao style extension to `[]`. Examples include:
  • _E_ \<== _X_[2,3] Access the second row, third column of matrix X. Indices start from `0`,
  • _L_ \<== _X_[2,_] Access all the second row, the output is a list ofe elements.
  • _L_ \<== _X_[2..4,_] Access all the second, thrd and fourth rows, the output is a list of elements.
  • _L_ \<== _X_[2..4+3,_] Access all the fifth, sixth and eight rows, the output is a list of elements.
The matrix library also supports a B-Prolog/ECliPSe inspired `foreach` ITerator to iterate over elements of a matrix:
  • foreach(I in 0..N1, X[I] \<== Y[I]) Copies a vector, element by element.
  • foreach([I in 0..N1, J in I..N1], Z[I,J] \<== X[I,J] - X[I,J]) The lower-triangular matrix _Z_ is the difference between the lower-triangular and upper-triangular parts of _X_.
  • foreach([I in 0..N1, J in 0..N1], plus(X[I,J]), 0, Sum) Add all elements of a matrix by using _Sum_ as an accumulator.
Notice that the library does not support all known matrix operations. Please contact the YAP maintainers if you require extra functionality.
  • _X_ = array[ _Dim1_,..., _Dimn_] of _Objects_ @anchor of The [of/2](@ref of) operator can be used to create a new array of _Objects_. The objects supported are:
    • Unbound Variable create an array of free variables
    • ints create an array of integers
    • floats create an array of floating-point numbers
    • _I_: _J_ create an array with integers from _I_ to _J_
    • [..] create an array from the values in a list
    The dimensions can be given as an integer, and the matrix will be indexed `C`-style from `0..( _Max_-1)`, or can be given as an interval ` _Base_.. _Limit_`. In the latter case, matrices of integers and of floating-point numbers should have the same _Base_ on every dimension.
  • ? _LHS_ \<== _RHS_ @anchor sSqQqQ General matrix assignment operation. It evaluates the right-hand side and then acts different according to the left-hand side and to the matrix:
    • if _LHS_ is part of an integer or floating-point matrix, perform non-backtrackable assignment.
    • other unify left-hand side and right-hand size.
    The right-hand side supports the following operators:
    • []/2 written as _M_[ _Offset_]: obtain an element or list of elements of matrix _M_ at offset _Offset_.
    • matrix/1 create a vector from a list
    • matrix/2 create a matrix from a list. Oprions are:
      • dim= a list of dimensiona
      • type= integers, floating-point or terms
      • base= a list of base offsets per dimension (all must be the same for arrays of integers and floating-points
    • matrix/3 create matrix giving two options
    • dim/1 list with matrix dimensions
    • nrow/1 number of rows in bi-dimensional matrix
    • ncol/1 number of columns in bi-dimensional matrix
    • length/1 size of a matrix
    • size/1 size of a matrix
    • max/1 maximum element of a numeric matrix
    • maxarg/1 argument of maximum element of a numeric matrix
    • min/1 minimum element of a numeric matrix
    • minarg/1 argument of minimum element of a numeric matrix
    • list/1 represent matrix as a list
    • lists/2 represent matrix as list of embedded lists
    • ../2 _I_.. _J_ generates a list with all integers from _I_ to _J_, included.
    • +/2 add two numbers, add two matrices element-by-element, or add a number to all elements of a matrix or list
    • -/2 subtract two numbers, subtract two matrices or lists element-by-element, or subtract a number from all elements of a matrix or list
    • \* /2 multiply two numbers, multiply two matrices or lists element-by-element, or multiply a number from all elements of a matrix or list
    • log/1 natural logarithm of a number, matrix or list
    • exp/1 natural exponentiation of a number, matrix or list
  • foreach( _Sequence_, _Goal_) @anchor foreach_matrix Deterministic iterator. The ranges are given by _Sequence_ that is either ` _I_ in _M_.. _N_`, or of the form `[ _I_, _J_] ins _M_.. _N_`, or a list of the above conditions. Variables in the goal are assumed to be global, ie, share a single value in the execution. The exceptions are the iteration indices. Moreover, if the goal is of the form ` _Locals_^ _G_` all variables occurring in _Locals_ are marked as local. As an example: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~{.prolog} foreach([I,J] ins 1..N, A^(A <==M[I,J], N[I] <== N[I] + A*A) ) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ the variables _I_, _J_ and _A_ are duplicated for every call (local), whereas the matrices _M_ and _N_ are shared throughout the execution (global).
  • foreach( _Sequence_, _Goal_, _Acc0_, _AccF_) Deterministic iterator with accumulator style arguments.
  • matrix_new(+ _Type_,+ _Dims_,- _Matrix_) @anchor matrix_new Create a new matrix _Matrix_ of type _Type_, which may be one of `ints` or `floats`, and with a list of dimensions _Dims_. The matrix will be initialised to zeros. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ?- matrix_new(ints,[2,3],Matrix). Matrix = {..} ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Notice that currently YAP will always write a matrix of numbers as `{..}`.
  • matrix_new(+ _Type_,+ _Dims_,+ _List_,- _Matrix_) Create a new matrix _Matrix_ of type _Type_, which may be one of `ints` or `floats`, with dimensions _Dims_, and initialised from list _List_.
  • matrix_new_set(? _Dims_,+ _OldMatrix_,+ _Value_,- _NewMatrix_) @anchor matrix_new_set Create a new matrix _NewMatrix_ of type _Type_, with dimensions _Dims_. The elements of _NewMatrix_ are set to _Value_.
  • matrix_dims(+ _Matrix_,- _Dims_) @anchor matrix_dims Unify _Dims_ with a list of dimensions for _Matrix_.
  • matrix_ndims(+ _Matrix_,- _Dims_) @anchor matrix_ndims Unify _NDims_ with the number of dimensions for _Matrix_.
  • matrix_size(+ _Matrix_,- _NElems_) @anchor matrix_size Unify _NElems_ with the number of elements for _Matrix_.
  • matrix_type(+ _Matrix_,- _Type_) @anchor matrix_type Unify _NElems_ with the type of the elements in _Matrix_.
  • matrix_to_list(+ _Matrix_,- _Elems_) @anchor matrix_to_list Unify _Elems_ with the list including all the elements in _Matrix_.
  • matrix_get(+ _Matrix_,+ _Position_,- _Elem_) @anchor matrix_get Unify _Elem_ with the element of _Matrix_ at position _Position_.
  • matrix_get(+ _Matrix_[+ _Position_],- _Elem_) Unify _Elem_ with the element _Matrix_[ _Position_].
  • matrix_set(+ _Matrix_,+ _Position_,+ _Elem_) @anchor matrix_set Set the element of _Matrix_ at position _Position_ to _Elem_.
  • matrix_set(+ _Matrix_[+ _Position_],+ _Elem_) Set the element of _Matrix_[ _Position_] to _Elem_.
  • matrix_set_all(+ _Matrix_,+ _Elem_) @anchor matrix_set_all Set all element of _Matrix_ to _Elem_.
  • matrix_add(+ _Matrix_,+ _Position_,+ _Operand_) @anchor matrix_add Add _Operand_ to the element of _Matrix_ at position _Position_.
  • matrix_inc(+ _Matrix_,+ _Position_) @anchor matrix_inc Increment the element of _Matrix_ at position _Position_.
  • matrix_inc(+ _Matrix_,+ _Position_,- _Element_) Increment the element of _Matrix_ at position _Position_ and unify with _Element_.
  • matrix_dec(+ _Matrix_,+ _Position_) @anchor matrix_dec Decrement the element of _Matrix_ at position _Position_.
  • matrix_dec(+ _Matrix_,+ _Position_,- _Element_) Decrement the element of _Matrix_ at position _Position_ and unify with _Element_.
  • matrix_arg_to_offset(+ _Matrix_,+ _Position_,- _Offset_) @anchor matrix_arg_to_offset Given matrix _Matrix_ return what is the numerical _Offset_ of the element at _Position_.
  • matrix_offset_to_arg(+ _Matrix_,- _Offset_,+ _Position_) @anchor matrix_offset_to_arg Given a position _Position _ for matrix _Matrix_ return the corresponding numerical _Offset_ from the beginning of the matrix.
  • matrix_max(+ _Matrix_,+ _Max_) @anchor matrix_max Unify _Max_ with the maximum in matrix _Matrix_.
  • matrix_maxarg(+ _Matrix_,+ _Maxarg_) @anchor matrix_maxarg Unify _Max_ with the position of the maximum in matrix _Matrix_.
  • matrix_min(+ _Matrix_,+ _Min_) @anchor matrix_min Unify _Min_ with the minimum in matrix _Matrix_.
  • matrix_minarg(+ _Matrix_,+ _Minarg_) @anchor matrix_minarg Unify _Min_ with the position of the minimum in matrix _Matrix_.
  • matrix_sum(+ _Matrix_,+ _Sum_) @anchor matrix_sum Unify _Sum_ with the sum of all elements in matrix _Matrix_.
  • matrix_agg_lines(+ _Matrix_,+ _Aggregate_) @anchor matrix_agg_lines If _Matrix_ is a n-dimensional matrix, unify _Aggregate_ with the n-1 dimensional matrix where each element is obtained by adding all Matrix elements with same last n-1 index.
  • matrix_agg_cols(+ _Matrix_,+ _Aggregate_) @anchor matrix_agg_cols If _Matrix_ is a n-dimensional matrix, unify _Aggregate_ with the one dimensional matrix where each element is obtained by adding all Matrix elements with same first index.
  • matrix_op(+ _Matrix1_,+ _Matrix2_,+ _Op_,- _Result_) @anchor matrix_op _Result_ is the result of applying _Op_ to matrix _Matrix1_ and _Matrix2_. Currently, only addition (`+`) is supported.
  • matrix_op_to_all(+ _Matrix1_,+ _Op_,+ _Operand_,- _Result_) @anchor matrix_op_to_all _Result_ is the result of applying _Op_ to all elements of _Matrix1_, with _Operand_ as the second argument. Currently, only addition (`+`), multiplication (`\*`), and division (`/`) are supported.
  • matrix_op_to_lines(+ _Matrix1_,+ _Lines_,+ _Op_,- _Result_) @anchor matrix_op_to_lines _Result_ is the result of applying _Op_ to all elements of _Matrix1_, with the corresponding element in _Lines_ as the second argument. Currently, only division (`/`) is supported.
  • matrix_op_to_cols(+ _Matrix1_,+ _Cols_,+ _Op_,- _Result_) @anchor matrix_op_to_cols _Result_ is the result of applying _Op_ to all elements of _Matrix1_, with the corresponding element in _Cols_ as the second argument. Currently, only addition (`+`) is supported. Notice that _Cols_ will have n-1 dimensions.
  • matrix_shuffle(+ _Matrix_,+ _NewOrder_,- _Shuffle_) @anchor matrix_shuffle Shuffle the dimensions of matrix _Matrix_ according to _NewOrder_. The list _NewOrder_ must have all the dimensions of _Matrix_, starting from 0.
  • matrix_transpose(+ _Matrix_,- _Transpose_) @anchor matrix_reorder Transpose matrix _Matrix_ to _Transpose_. Equivalent to: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ matrix_transpose(Matrix,Transpose) :- matrix_shuffle(Matrix,[1,0],Transpose). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  • matrix_expand(+ _Matrix_,+ _NewDimensions_,- _New_) @anchor matrix_expand Expand _Matrix_ to occupy new dimensions. The elements in _NewDimensions_ are either 0, for an existing dimension, or a positive integer with the size of the new dimension.
  • matrix_select(+ _Matrix_,+ _Dimension_,+ _Index_,- _New_) @anchor matrix_select Select from _Matrix_ the elements who have _Index_ at _Dimension_.
  • matrix_row(+ _Matrix_,+ _Column_,- _NewMatrix_) @anchor matrix_row Select from _Matrix_ the row matching _Column_ as new matrix _NewMatrix_. _Column_ must have one less dimension than the original matrix. _Dimension_.
@section MATLAB MATLAB Package Interface The MathWorks MATLAB is a widely used package for array processing. YAP now includes a straightforward interface to MATLAB. To actually use it, you need to install YAP calling `configure` with the `--with-matlab=DIR` option, and you need to call `use_module(library(lists))` command. Accessing the matlab dynamic libraries can be complicated. In Linux machines, to use this interface, you may have to set the environment variable LD_LIBRARY_PATH. Next, follows an example using bash in a 64-bit Linux PC: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ export LD_LIBRARY_PATH=''$MATLAB_HOME"/sys/os/glnxa64:''$MATLAB_HOME"/bin/glnxa64:''$LD_LIBRARY_PATH" ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ where `MATLAB_HOME` is the directory where matlab is installed at. Please replace `ax64` for `x86` on a 32-bit PC.
  • start_matlab(+ _Options_) @anchor start_matlab Start a matlab session. The argument _Options_ may either be the empty string/atom or the command to call matlab. The command may fail.
  • close_matlab @anchor close_matlab Stop the current matlab session.
  • matlab_on @anchor matlab_on Holds if a matlab session is on.
  • matlab_eval_string(+ _Command_) @anchor matlab_eval_string Holds if matlab evaluated successfully the command _Command_.
  • matlab_eval_string(+ _Command_, - _Answer_) MATLAB will evaluate the command _Command_ and unify _Answer_ with a string reporting the result.
  • matlab_cells(+ _Size_, ? _Array_) @anchor matlab_cells MATLAB will create an empty vector of cells of size _Size_, and if _Array_ is bound to an atom, store the array in the matlab variable with name _Array_. Corresponds to the MATLAB command `cells`.
  • matlab_cells(+ _SizeX_, + _SizeY_, ? _Array_) MATLAB will create an empty array of cells of size _SizeX_ and _SizeY_, and if _Array_ is bound to an atom, store the array in the matlab variable with name _Array_. Corresponds to the MATLAB command `cells`.
  • matlab_initialized_cells(+ _SizeX_, + _SizeY_, + _List_, ? _Array_) @anchor matlab_initialized_cells MATLAB will create an array of cells of size _SizeX_ and _SizeY_, initialized from the list _List_, and if _Array_ is bound to an atom, store the array in the matlab variable with name _Array_.
  • matlab_matrix(+ _SizeX_, + _SizeY_, + _List_, ? _Array_) @anchor matlab_matrix MATLAB will create an array of floats of size _SizeX_ and _SizeY_, initialized from the list _List_, and if _Array_ is bound to an atom, store the array in the matlab variable with name _Array_.
  • matlab_set(+ _MatVar_, + _X_, + _Y_, + _Value_) @anchor matlab_set Call MATLAB to set element _MatVar_( _X_, _Y_) to _Value_. Notice that this command uses the MATLAB array access convention.
  • matlab_get_variable(+ _MatVar_, - _List_) @anchor matlab_get_variable Unify MATLAB variable _MatVar_ with the List _List_.
  • matlab_item(+ _MatVar_, + _X_, ? _Val_) @anchor matlab_item Read or set MATLAB _MatVar_( _X_) from/to _Val_. Use `C` notation for matrix access (ie, starting from 0).
  • matlab_item(+ _MatVar_, + _X_, + _Y_, ? _Val_) Read or set MATLAB _MatVar_( _X_, _Y_) from/to _Val_. Use `C` notation for matrix access (ie, starting from 0).
  • matlab_item1(+ _MatVar_, + _X_, ? _Val_) @anchor matlab_item1 Read or set MATLAB _MatVar_( _X_) from/to _Val_. Use MATLAB notation for matrix access (ie, starting from 1).
  • matlab_item1(+ _MatVar_, + _X_, + _Y_, ? _Val_) Read or set MATLAB _MatVar_( _X_, _Y_) from/to _Val_. Use MATLAB notation for matrix access (ie, starting from 1).
  • matlab_sequence(+ _Min_, + _Max_, ? _Array_) @anchor matlab_sequence MATLAB will create a sequence going from _Min_ to _Max_, and if _Array_ is bound to an atom, store the sequence in the matlab variable with name _Array_.
  • matlab_vector(+ _Size_, + _List_, ? _Array_) @anchor matlab_vector MATLAB will create a vector of floats of size _Size_, initialized from the list _List_, and if _Array_ is bound to an atom, store the array in the matlab variable with name _Array_.
  • matlab_zeros(+ _Size_, ? _Array_) @anchor matlab_zeros MATLAB will create a vector of zeros of size _Size_, and if _Array_ is bound to an atom, store the array in the matlab variable with name _Array_. Corresponds to the MATLAB command `zeros`.
  • matlab_zeros(+ _SizeX_, + _SizeY_, ? _Array_) MATLAB will create an array of zeros of size _SizeX_ and _SizeY_, and if _Array_ is bound to an atom, store the array in the matlab variable with name _Array_. Corresponds to the MATLAB command `zeros`.
  • matlab_zeros(+ _SizeX_, + _SizeY_, + _SizeZ_, ? _Array_) MATLAB will create an array of zeros of size _SizeX_, _SizeY_, and _SizeZ_. If _Array_ is bound to an atom, store the array in the matlab variable with name _Array_. Corresponds to the MATLAB command `zeros`.
@section NonhYBacktrackable_Data_Structures Non-Backtrackable Data Structures The following routines implement well-known data-structures using global non-backtrackable variables (implemented on the Prolog stack). The data-structures currently supported are Queues, Heaps, and Beam for Beam search. They are allowed through `library(nb)`.
  • nb_queue(- _Queue_) @anchor nb_queue Create a _Queue_.
  • nb_queue_close(+ _Queue_, - _Head_, ? _Tail_) @anchor nb_queue_close Unify the queue _Queue_ with a difference list _Head_- _Tail_. The queue will now be empty and no further elements can be added.
  • nb_queue_enqueue(+ _Queue_, + _Element_) @anchor nb_queue_enqueue Add _Element_ to the front of the queue _Queue_.
  • nb_queue_dequeue(+ _Queue_, - _Element_) @anchor nb_queue_dequeue Remove _Element_ from the front of the queue _Queue_. Fail if the queue is empty.
  • nb_queue_peek(+ _Queue_, - _Element_) @anchor nb_queue_peek _Element_ is the front of the queue _Queue_. Fail if the queue is empty.
  • nb_queue_size(+ _Queue_, - _Size_) @anchor nb_queue_size Unify _Size_ with the number of elements in the queue _Queue_.
  • nb_queue_empty(+ _Queue_) @anchor nb_queue_empty Succeeds if _Queue_ is empty.
  • nb_heap(+ _DefaultSize_,- _Heap_) @anchor nb_heap Create a _Heap_ with default size _DefaultSize_. Note that size will expand as needed.
  • nb_heap_close(+ _Heap_) @anchor nb_heap_close Close the heap _Heap_: no further elements can be added.
  • nb_heap_add(+ _Heap_, + _Key_, + _Value_) @anchor nb_heap_add Add _Key_- _Value_ to the heap _Heap_. The key is sorted on _Key_ only.
  • nb_heap_del(+ _Heap_, - _Key_, - _Value_) @anchor nb_heap_del Remove element _Key_- _Value_ with smallest _Value_ in heap _Heap_. Fail if the heap is empty.
  • nb_heap_peek(+ _Heap_, - _Key_, - _Value_)) @anchor nb_heap_peek _Key_- _Value_ is the element with smallest _Key_ in the heap _Heap_. Fail if the heap is empty.
  • nb_heap_size(+ _Heap_, - _Size_) @anchor nb_heap_size Unify _Size_ with the number of elements in the heap _Heap_.
  • nb_heap_empty(+ _Heap_) @anchor nb_heap_empty Succeeds if _Heap_ is empty.
  • nb_beam(+ _DefaultSize_,- _Beam_) @anchor nb_beam Create a _Beam_ with default size _DefaultSize_. Note that size is fixed throughout.
  • nb_beam_close(+ _Beam_) @anchor nb_beam_close Close the beam _Beam_: no further elements can be added.
  • nb_beam_add(+ _Beam_, + _Key_, + _Value_) @anchor nb_beam_add Add _Key_- _Value_ to the beam _Beam_. The key is sorted on _Key_ only.
  • nb_beam_del(+ _Beam_, - _Key_, - _Value_) @anchor nb_beam_del Remove element _Key_- _Value_ with smallest _Value_ in beam _Beam_. Fail if the beam is empty.
  • nb_beam_peek(+ _Beam_, - _Key_, - _Value_)) @anchor nb_beam_peek _Key_- _Value_ is the element with smallest _Key_ in the beam _Beam_. Fail if the beam is empty.
  • nb_beam_size(+ _Beam_, - _Size_) @anchor nb_beam_size Unify _Size_ with the number of elements in the beam _Beam_.
  • nb_beam_empty(+ _Beam_) @anchor nb_beam_empty Succeeds if _Beam_ is empty.
@section Ordered_Sets Ordered Sets The following ordered set manipulation routines are available once included with the `use_module(library(ordsets))` command. An ordered set is represented by a list having unique and ordered elements. Output arguments are guaranteed to be ordered sets, if the relevant inputs are. This is a slightly patched version of Richard O'Keefe's original library.
  • list_to_ord_set(+ _List_, ? _Set_) @anchor list_to_ord_set Holds when _Set_ is the ordered representation of the set represented by the unordered representation _List_.
  • merge(+ _List1_, + _List2_, - _Merged_) @anchor merge Holds when _Merged_ is the stable merge of the two given lists. Notice that [merge/3](@ref merge) will not remove duplicates, so merging ordered sets will not necessarily result in an ordered set. Use `ord_union/3` instead.
  • ord_add_element(+ _Set1_, + _Element_, ? _Set2_) @anchor ord_add_element Inserting _Element_ in _Set1_ returns _Set2_. It should give exactly the same result as `merge(Set1, [Element], Set2)`, but a bit faster, and certainly more clearly. The same as [ord_insert/3](@ref ord_insert).
  • ord_del_element(+ _Set1_, + _Element_, ? _Set2_) @anchor ord_del_element Removing _Element_ from _Set1_ returns _Set2_.
  • ord_disjoint(+ _Set1_, + _Set2_) @anchor ord_disjoint Holds when the two ordered sets have no element in common.
  • ord_member(+ _Element_, + _Set_) @anchor ord_member Holds when _Element_ is a member of _Set_.
  • ord_insert(+ _Set1_, + _Element_, ? _Set2_) @anchor ord_insert Inserting _Element_ in _Set1_ returns _Set2_. It should give exactly the same result as `merge(Set1, [Element], Set2)`, but a bit faster, and certainly more clearly. The same as [ord_add_element/3](@ref ord_add_element).
  • ord_intersect(+ _Set1_, + _Set2_) @anchor ord_intersect Holds when the two ordered sets have at least one element in common.
  • ord_intersection(+ _Set1_, + _Set2_, ? _Intersection_) Holds when Intersection is the ordered representation of _Set1_ and _Set2_.
  • ord_intersection(+ _Set1_, + _Set2_, ? _Intersection_, ? _Diff_) Holds when Intersection is the ordered representation of _Set1_ and _Set2_. _Diff_ is the difference between _Set2_ and _Set1_.
  • ord_seteq(+ _Set1_, + _Set2_) @anchor ord_seteq Holds when the two arguments represent the same set.
  • ord_setproduct(+ _Set1_, + _Set2_, - _Set_) @anchor ord_setproduct If Set1 and Set2 are ordered sets, Product will be an ordered set of x1-x2 pairs.
  • ord_subset(+ _Set1_, + _Set2_) @anchor ordsubset Holds when every element of the ordered set _Set1_ appears in the ordered set _Set2_.
  • ord_subtract(+ _Set1_, + _Set2_, ? _Difference_) @anchor ord_subtract Holds when _Difference_ contains all and only the elements of _Set1_ which are not also in _Set2_.
  • ord_symdiff(+ _Set1_, + _Set2_, ? _Difference_) @anchor ord_symdiff Holds when _Difference_ is the symmetric difference of _Set1_ and _Set2_.
  • ord_union(+ _Sets_, ? _Union_) @anchor ord_union Holds when _Union_ is the union of the lists _Sets_.
  • ord_union(+ _Set1_, + _Set2_, ? _Union_) Holds when _Union_ is the union of _Set1_ and _Set2_.
  • ord_union(+ _Set1_, + _Set2_, ? _Union_, ? _Diff_) Holds when _Union_ is the union of _Set1_ and _Set2_ and _Diff_ is the difference.
@section Pseudo_Random Pseudo Random Number Integer Generator The following routines produce random non-negative integers in the range 0 .. 2^(w-1) -1, where w is the word size available for integers, e.g. 32 for Intel machines and 64 for Alpha machines. Note that the numbers generated by this random number generator are repeatable. This generator was originally written by Allen Van Gelder and is based on Knuth Vol 2.
  • rannum(- _I_) @anchor rannum Produces a random non-negative integer _I_ whose low bits are not all that random, so it should be scaled to a smaller range in general. The integer _I_ is in the range 0 .. 2^(w-1) - 1. You can use: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ rannum(X) :- yap_flag(max_integer,MI), rannum(R), X is R/MI. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ to obtain a floating point number uniformly distributed between 0 and 1.
  • ranstart @anchor ranstart Initialize the random number generator using a built-in seed. The [ranstart/0](@ref ranstart) built-in is always called by the system when loading the package.
  • ranstart(+ _Seed_) Initialize the random number generator with user-defined _Seed_. The same _Seed_ always produces the same sequence of numbers.
  • ranunif(+ _Range_,- _I_) @anchor ranunif [ranunif/2](@ref ranunif) produces a uniformly distributed non-negative random integer _I_ over a caller-specified range _R_. If range is _R_, the result is in 0 .. _R_-1.
@section Queues Queues The following queue manipulation routines are available once included with the `use_module(library(queues))` command. Queues are implemented with difference lists.
  • make_queue(+ _Queue_) @anchor make_queue Creates a new empty queue. It should only be used to create a new queue.
  • join_queue(+ _Element_, + _OldQueue_, - _NewQueue_) @anchor join_queue Adds the new element at the end of the queue.
  • list_join_queue(+ _List_, + _OldQueue_, - _NewQueue_) @anchor list_join_queue Ads the new elements at the end of the queue.
  • jump_queue(+ _Element_, + _OldQueue_, - _NewQueue_) @anchor jump_queue Adds the new element at the front of the list.
  • list_jump_queue(+ _List_, + _OldQueue_, + _NewQueue_) @anchor list_jump_queue Adds all the elements of _List_ at the front of the queue.
  • head_queue(+ _Queue_, ? _Head_) @anchor head_queue Unifies Head with the first element of the queue.
  • serve_queue(+ _OldQueue_, + _Head_, - _NewQueue_) @anchor serve_queue Removes the first element of the queue for service.
  • empty_queue(+ _Queue_) @anchor empty_queue Tests whether the queue is empty.
  • length_queue(+ _Queue_, - _Length_) @anchor length_queue Counts the number of elements currently in the queue.
  • list_to_queue(+ _List_, - _Queue_) @anchor list_to_queue Creates a new queue with the same elements as _List._
  • queue_to_list(+ _Queue_, - _List_) @anchor queue_to_list Creates a new list with the same elements as _Queue_.
@section Random Random Number Generator The following random number operations are included with the `use_module(library(random))` command. Since YAP-4.3.19 YAP uses the O'Keefe public-domain algorithm, based on the "Applied Statistics" algorithm AS183.
  • getrand(- _Key_) @anchor getrand Unify _Key_ with a term of the form `rand(X,Y,Z)` describing the current state of the random number generator.
  • random(- _Number_) @anchor random Unify _Number_ with a floating-point number in the range `[0...1)`.
  • random(+ _LOW_, + _HIGH_, - _NUMBER_) Unify _Number_ with a number in the range `[LOW...HIGH)`. If both _LOW_ and _HIGH_ are integers then _NUMBER_ will also be an integer, otherwise _NUMBER_ will be a floating-point number.
  • randseq(+ _LENGTH_, + _MAX_, - _Numbers_) @anchor randseq Unify _Numbers_ with a list of _LENGTH_ unique random integers in the range `[1... _MAX_)`.
  • randset(+ _LENGTH_, + _MAX_, - _Numbers_) @anchor randset Unify _Numbers_ with an ordered list of _LENGTH_ unique random integers in the range `[1... _MAX_)`.
  • setrand(+ _Key_) @anchor setrand Use a term of the form `rand(X,Y,Z)` to set a new state for the random number generator. The integer `X` must be in the range `[1...30269)`, the integer `Y` must be in the range `[1...30307)`, and the integer `Z` must be in the range `[1...30323)`.
@section Read_Utilities Read Utilities The `readutil` library contains primitives to read lines, files, multiple terms, etc.
  • read_line_to_codes(+ _Stream_, - _Codes_) @anchor read_line_to_codes Read the next line of input from _Stream_ and unify the result with _Codes_ after the line has been read. A line is ended by a newline character or end-of-file. Unlike `read_line_to_codes/3`, this predicate removes trailing newline character. On end-of-file the atom `end_of_file` is returned. See also `at_end_of_stream/[0,1]`.
  • read_line_to_codes(+ _Stream_, - _Codes_, ? _Tail_) Difference-list version to read an input line to a list of character codes. Reading stops at the newline or end-of-file character, but unlike [read_line_to_codes/2](@ref read_line_to_codes), the newline is retained in the output. This predicate is especially useful for reading a block of lines upto some delimiter. The following example reads an HTTP header ended by a blank line: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ read_header_data(Stream, Header) :- read_line_to_codes(Stream, Header, Tail), read_header_data(Header, Stream, Tail). read_header_data("\r\n", _, _) :- !. read_header_data("\n", _, _) :- !. read_header_data("", _, _) :- !. read_header_data(_, Stream, Tail) :- read_line_to_codes(Stream, Tail, NewTail), read_header_data(Tail, Stream, NewTail). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  • read_stream_to_codes(+ _Stream_, - _Codes_) @anchor read_stream_to_codes Read all input until end-of-file and unify the result to _Codes_.
  • read_stream_to_codes(+ _Stream_, - _Codes_, ? _Tail_) Difference-list version of [read_stream_to_codes/2](@ref read_stream_to_codes).
  • read_file_to_codes(+ _Spec_, - _Codes_, + _Options_) @anchor read_file_to_codes Read a file to a list of character codes. Currently ignores _Options_.
  • read_file_to_terms(+ _Spec_, - _Terms_, + _Options_) @anchor read_file_to_terms Read a file to a list of Prolog terms (see read/1). @c _Spec_ is a
@section RedhYBlack_Trees Red-Black Trees Red-Black trees are balanced search binary trees. They are named because nodes can be classified as either red or black. The code we include is based on "Introduction to Algorithms", second edition, by Cormen, Leiserson, Rivest and Stein. The library includes routines to insert, lookup and delete elements in the tree.
  • rb_new(? _T_) @anchor rb_new Create a new tree.
  • rb_empty(? _T_) @anchor rb_empty Succeeds if tree _T_ is empty.
  • is_rbtree(+ _T_) @anchor is_rbtree Check whether _T_ is a valid red-black tree.
  • rb_insert(+ _T0_,+ _Key_,? _Value_,+ _TF_) @anchor rb_insert Add an element with key _Key_ and _Value_ to the tree _T0_ creating a new red-black tree _TF_. Duplicated elements are not allowed. Add a new element with key _Key_ and _Value_ to the tree _T0_ creating a new red-black tree _TF_. Fails is an element with _Key_ exists in the tree.
  • rb_lookup(+ _Key_,- _Value_,+ _T_) @anchor rb_lookup Backtrack through all elements with key _Key_ in the red-black tree _T_, returning for each the value _Value_.
  • rb_lookupall(+ _Key_,- _Value_,+ _T_) @anchor rb_lookupall Lookup all elements with key _Key_ in the red-black tree _T_, returning the value _Value_.
  • rb_delete(+ _T_,+ _Key_,- _TN_) @anchor rb_delete Delete element with key _Key_ from the tree _T_, returning a new tree _TN_.
  • rb_delete(+ _T_,+ _Key_,- _Val_,- _TN_) Delete element with key _Key_ from the tree _T_, returning the value _Val_ associated with the key and a new tree _TN_.
  • rb_del_min(+ _T_,- _Key_,- _Val_,- _TN_) @anchor rb_del_min Delete the least element from the tree _T_, returning the key _Key_, the value _Val_ associated with the key and a new tree _TN_.
  • rb_del_max(+ _T_,- _Key_,- _Val_,- _TN_) @anchor rb_del_max Delete the largest element from the tree _T_, returning the key _Key_, the value _Val_ associated with the key and a new tree _TN_.
  • rb_update(+ _T_,+ _Key_,+ _NewVal_,- _TN_) @anchor rb_update Tree _TN_ is tree _T_, but with value for _Key_ associated with _NewVal_. Fails if it cannot find _Key_ in _T_.
  • rb_apply(+ _T_,+ _Key_,+ _G_,- _TN_) @anchor rb_apply If the value associated with key _Key_ is _Val0_ in _T_, and if `call(G,Val0,ValF)` holds, then _TN_ differs from _T_ only in that _Key_ is associated with value _ValF_ in tree _TN_. Fails if it cannot find _Key_ in _T_, or if `call(G,Val0,ValF)` is not satisfiable.
  • rb_visit(+ _T_,- _Pairs_) @anchor rb_visit _Pairs_ is an infix visit of tree _T_, where each element of _Pairs_ is of the form _K_- _Val_.
  • rb_size(+ _T_,- _Size_) @anchor rb_size _Size_ is the number of elements in _T_.
  • rb_keys(+ _T_,+ _Keys_) @anchor rb_keys _Keys_ is an infix visit with all keys in tree _T_. Keys will be sorted, but may be duplicate.
  • rb_map(+ _T_,+ _G_,- _TN_) @anchor rb_map For all nodes _Key_ in the tree _T_, if the value associated with key _Key_ is _Val0_ in tree _T_, and if `call(G,Val0,ValF)` holds, then the value associated with _Key_ in _TN_ is _ValF_. Fails if or if `call(G,Val0,ValF)` is not satisfiable for all _Var0_.
  • rb_partial_map(+ _T_,+ _Keys_,+ _G_,- _TN_) @anchor rb_partial_map For all nodes _Key_ in _Keys_, if the value associated with key _Key_ is _Val0_ in tree _T_, and if `call(G,Val0,ValF)` holds, then the value associated with _Key_ in _TN_ is _ValF_. Fails if or if `call(G,Val0,ValF)` is not satisfiable for all _Var0_. Assumes keys are not repeated.
  • rb_fold(+ _T_,+ _G_,+ _Acc0_, - _AccF_) @anchor rb_fold For all nodes _Key_ in the tree _T_, if the value associated with key _Key_ is _V_ in tree _T_, if `call(G,V,Acc1,Acc2)` holds, then if _VL_ is value of the previous node in inorder, `call(G,VL,_,Acc0)` must hold, and if _VR_ is the value of the next node in inorder, `call(G,VR,Acc1,_)` must hold.
  • rb_key_fold(+ _T_,+ _G_,+ _Acc0_, - _AccF_) @anchor rb_key_fold For all nodes _Key_ in the tree _T_, if the value associated with key _Key_ is _V_ in tree _T_, if `call(G,Key,V,Acc1,Acc2)` holds, then if _VL_ is value of the previous node in inorder, `call(G,KeyL,VL,_,Acc0)` must hold, and if _VR_ is the value of the next node in inorder, `call(G,KeyR,VR,Acc1,_)` must hold.
  • rb_clone(+ _T_,+ _NT_,+ _Nodes_) @anchor rb_clone ``Clone'' the red-back tree into a new tree with the same keys as the original but with all values set to unbound values. Nodes is a list containing all new nodes as pairs _K-V_.
  • rb_min(+ _T_,- _Key_,- _Value_) @anchor rb_min _Key_ is the minimum key in _T_, and is associated with _Val_.
  • rb_max(+ _T_,- _Key_,- _Value_) @anchor rb_max _Key_ is the maximal key in _T_, and is associated with _Val_.
  • rb_next(+ _T_, + _Key_,- _Next_,- _Value_) @anchor rb_next _Next_ is the next element after _Key_ in _T_, and is associated with _Val_.
  • rb_previous(+ _T_, + _Key_,- _Previous_,- _Value_) @anchor rb_previous _Previous_ is the previous element after _Key_ in _T_, and is associated with _Val_.
  • ord_list_to_rbtree(+ _L_, - _T_) @anchor list_to_rbtree _T_ is the red-black tree corresponding to the mapping in ordered list _L_.
@section RegExp Regular Expressions This library includes routines to determine whether a regular expression matches part or all of a string. The routines can also return which parts parts of the string matched the expression or subexpressions of it. This library relies on Henry Spencer's `C`-package and is only available in operating systems that support dynamic loading. The `C`-code has been obtained from the sources of FreeBSD-4.0 and is protected by copyright from Henry Spencer and from the Regents of the University of California (see the file library/regex/COPYRIGHT for further details). Much of the description of regular expressions below is copied verbatim from Henry Spencer's manual page. A regular expression is zero or more branches, separated by ``|''. It matches anything that matches one of the branches. A branch is zero or more pieces, concatenated. It matches a match for the first, followed by a match for the second, etc. A piece is an atom possibly followed by ``\*'', ``+'', or ``?''. An atom followed by ``\*'' matches a sequence of 0 or more matches of the atom. An atom followed by ``+'' matches a sequence of 1 or more matches of the atom. An atom followed by ``?'' matches a match of the atom, or the null string. An atom is a regular expression in parentheses (matching a match for the regular expression), a range (see below), ``.'' (matching any single character), ``^'' (matching the null string at the beginning of the input string), ``$'' (matching the null string at the end of the input string), a ``\\'' followed by a single character (matching that character), or a single character with no other significance (matching that character). A range is a sequence of characters enclosed in ``[]''. It normally matches any single character from the sequence. If the sequence begins with ``^'', it matches any single character not from the rest of the sequence. If two characters in the sequence are separated by ``-'', this is shorthand for the full list of ASCII characters between them (e.g. ``[0-9]'' matches any decimal digit). To include a literal ``]'' in the sequence, make it the first character (following a possible ``^''). To include a literal ``-'', make it the first or last character.
  • regexp(+ _RegExp_,+ _String_,+ _Opts_) @anchor regexp Match regular expression _RegExp_ to input string _String_ according to options _Opts_. The options may be:
    • `nocase`: Causes upper-case characters in _String_ to be treated as lower case during the matching process.
  • regexp(+ _RegExp_,+ _String_,+ _Opts_,? _SubMatchVars_) Match regular expression _RegExp_ to input string _String_ according to options _Opts_. The variable _SubMatchVars_ should be originally unbound or a list of unbound variables all will contain a sequence of matches, that is, the head of _SubMatchVars_ will contain the characters in _String_ that matched the leftmost parenthesized subexpression within _RegExp_, the next head of list will contain the characters that matched the next parenthesized subexpression to the right in _RegExp_, and so on. The options may be:
    • `nocase`: Causes upper-case characters in _String_ to be treated as lower case during the matching process.
    • `indices`: Changes what is stored in _SubMatchVars_. Instead of storing the matching characters from _String_, each variable will contain a term of the form _IO-IF_ giving the indices in _String_ of the first and last characters in the matching range of characters.
    In general there may be more than one way to match a regular expression to an input string. For example, consider the command ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ regexp("(a*)b*","aabaaabb", [], [X,Y]) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Considering only the rules given so far, _X_ and _Y_ could end up with the values `"aabb"` and `"aa"`, `"aaab"` and `"aaa"`, `"ab"` and `"a"`, or any of several other combinations. To resolve this potential ambiguity `regexp` chooses among alternatives using the rule ``first then longest''. In other words, it considers the possible matches in order working from left to right across the input string and the pattern, and it attempts to match longer pieces of the input string before shorter ones. More specifically, the following rules apply in decreasing order of priority:
    1. If a regular expression could match two different parts of an input string then it will match the one that begins earliest.
    2. If a regular expression contains "|" operators then the leftmost matching sub-expression is chosen.
    3. In \*, +, and ? constructs, longer matches are chosen in preference to shorter ones.
    4. In sequences of expression components the components are considered from left to right.
    In the example from above, `"(a\*)b\*"` matches `"aab"`: the `"(a\*)"` portion of the pattern is matched first and it consumes the leading `"aa"`; then the `"b\*"` portion of the pattern consumes the next `"b"`. Or, consider the following example: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ regexp("(ab|a)(b*)c", "abc", [], [X,Y,Z]) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ After this command _X_ will be `"abc"`, _Y_ will be `"ab"`, and _Z_ will be an empty string. Rule 4 specifies that `"(ab|a)"` gets first shot at the input string and Rule 2 specifies that the `"ab"` sub-expression is checked before the `"a"` sub-expression. Thus the `"b"` has already been claimed before the `"(b\*)"` component is checked and `(b\*)` must match an empty string.
@section shlib SWI-Prolog's shlib library This section discusses the functionality of the (autoload) `library(shlib)`, providing an interface to manage shared libraries. One of the files provides a global function `install_mylib()` that initialises the module using calls to `PL_register_foreign()`. Here is a simple example file `mylib.c`, which creates a Windows MessageBox: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~{.c} #include #include static foreign_t pl_say_hello(term_t to) { char *a; if ( PL_get_atom_chars(to, &a) ) { MessageBox(NULL, a, "DLL test", MB_OK|MB_TASKMODAL); PL_succeed; } PL_fail; } install_t install_mylib() { PL_register_foreign("say_hello", 1, pl_say_hello, 0); } ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Now write a file mylib.pl: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ :- module(mylib, [ say_hello/1 ]). :- use_foreign_library(foreign(mylib)). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ The file mylib.pl can be loaded as a normal Prolog file and provides the predicate defined in C.
  • load_foreign_library(: _FileSpec_) is det @anchor load_foreign_library
  • load_foreign_library(: _FileSpec_, + _Entry_:atom) is det Load a shared object or DLL. After loading the _Entry_ function is called without arguments. The default entry function is composed from `install_`, followed by the file base-name. E.g., the load-call below calls the function `install_mylib()`. If the platform prefixes extern functions with `_`, this prefix is added before calling. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ... load_foreign_library(foreign(mylib)), ... ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ _FileSpec_ is a specification for [absolute_file_name/3](@ref absolute_file_name). If searching the file fails, the plain name is passed to the OS to try the default method of the OS for locating foreign objects. The default definition of [file_search_path/2](@ref file_search_path) searches \/lib/Yap. See also `use_foreign_library/1,2` are intended for use in directives.
  • [det] use_foreign_library(+ _FileSpec_), use_foreign_library(+ _FileSpec_, + _Entry_:atom) @anchor use_foreign_library Load and install a foreign library as [load_foreign_library/1](@ref load_foreign_library) and `load_foreign_library/2` and register the installation using `initialization/2` with the option now. This is similar to using: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ :- initialization(load_foreign_library(foreign(mylib))). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ but using the [initialization/1](@ref initialization) wrapper causes the library to be loaded after loading of the file in which it appears is completed, while [use_foreign_library/1](@ref use_foreign_library) loads the library immediately. I.e. the difference is only relevant if the remainder of the file uses functionality of the `C`-library.
  • [det]unload_foreign_library(+ _FileSpec_)
  • [det]unload_foreign_library(+ _FileSpec_, + _Exit_:atom) @anchor unload_foreign_library Unload a shared object or DLL. After calling the _Exit_ function, the shared object is removed from the process. The default exit function is composed from `uninstall_`, followed by the file base-name.
  • current_foreign_library(? _File_, ? _Public_) @anchor current_foreign_library Query currently loaded shared libraries.
@section Splay_Trees Splay Trees Splay trees are explained in the paper "Self-adjusting Binary Search Trees", by D.D. Sleator and R.E. Tarjan, JACM, vol. 32, No.3, July 1985, p. 668. They are designed to support fast insertions, deletions and removals in binary search trees without the complexity of traditional balanced trees. The key idea is to allow the tree to become unbalanced. To make up for this, whenever we find a node, we move it up to the top. We use code by Vijay Saraswat originally posted to the Prolog mailing-list.
  • splay_access(- _Return_,+ _Key_,? _Val_,+ _Tree_,- _NewTree_) @anchor splay_access If item _Key_ is in tree _Tree_, return its _Val_ and unify _Return_ with `true`. Otherwise unify _Return_ with `null`. The variable _NewTree_ unifies with the new tree.
  • splay_delete(+ _Key_,? _Val_,+ _Tree_,- _NewTree_) @anchor splay_delete Delete item _Key_ from tree _Tree_, assuming that it is present already. The variable _Val_ unifies with a value for key _Key_, and the variable _NewTree_ unifies with the new tree. The predicate will fail if _Key_ is not present.
  • splay_init(- _NewTree_) @anchor splay_init Initialize a new splay tree.
  • splay_insert(+ _Key_,? _Val_,+ _Tree_,- _NewTree_) @anchor splay_insert Insert item _Key_ in tree _Tree_, assuming that it is not there already. The variable _Val_ unifies with a value for key _Key_, and the variable _NewTree_ unifies with the new tree. In our implementation, _Key_ is not inserted if it is already there: rather it is unified with the item already in the tree.
  • splay_join(+ _LeftTree_,+ _RighTree_,- _NewTree_) @anchor splay_join Combine trees _LeftTree_ and _RighTree_ into a single tree _NewTree_ containing all items from both trees. This operation assumes that all items in _LeftTree_ are less than all those in _RighTree_ and destroys both _LeftTree_ and _RighTree_.
  • splay_split(+ _Key_,? _Val_,+ _Tree_,- _LeftTree_,- _RightTree_) @anchor splay_split Construct and return two trees _LeftTree_ and _RightTree_, where _LeftTree_ contains all items in _Tree_ less than _Key_, and _RightTree_ contains all items in _Tree_ greater than _Key_. This operations destroys _Tree_.
@section String_InputOutput Reading From and Writing To Strings From Version 4.3.2 onwards YAP implements SICStus Prolog compatible String Input/Output. The library allows users to read from and write to a memory buffer as if it was a file. The memory buffer is built from or converted to a string of character codes by the routines in library. Therefore, if one wants to read from a string the string must be fully instantiated before the library built-in opens the string for reading. These commands are available through the `use_module(library(charsio))` command.
  • format_to_chars(+ _Form_, + _Args_, - _Result_) @anchor format_to_chars Execute the built-in procedure [format/2](@ref format) with form _Form_ and arguments _Args_ outputting the result to the string of character codes _Result_.
  • format_to_chars(+ _Form_, + _Args_, - _Result_, - _Result0_) Execute the built-in procedure [format/2](@ref format) with form _Form_ and arguments _Args_ outputting the result to the difference list of character codes _Result-Result0_.
  • write_to_chars(+ _Term_, - _Result_) @anchor write_to_chars Execute the built-in procedure [write/1](@ref write) with argument _Term_ outputting the result to the string of character codes _Result_.
  • write_to_chars(+ _Term_, - _Result0_, - _Result_) Execute the built-in procedure [write/1](@ref write) with argument _Term_ outputting the result to the difference list of character codes _Result-Result0_.
  • atom_to_chars(+ _Atom_, - _Result_) @anchor atom_to_chars Convert the atom _Atom_ to the string of character codes _Result_.
  • atom_to_chars(+ _Atom_, - _Result0_, - _Result_) Convert the atom _Atom_ to the difference list of character codes _Result-Result0_.
  • number_to_chars(+ _Number_, - _Result_) @anchor number_to_chars Convert the number _Number_ to the string of character codes _Result_.
  • number_to_chars(+ _Number_, - _Result0_, - _Result_) Convert the atom _Number_ to the difference list of character codes _Result-Result0_.
  • atom_to_term(+ _Atom_, - _Term_, - _Bindings_) @anchor atom_to_term Use _Atom_ as input to [read_term/2](@ref read_term) using the option `variable_names` and return the read term in _Term_ and the variable bindings in _Bindings_. _Bindings_ is a list of `Name = Var` couples, thus providing access to the actual variable names. See also [read_term/2](@ref read_term). If Atom has no valid syntax, a syntax_error exception is raised.
  • term_to_atom(? _Term_, ? _Atom_) @anchor term_to_atom True if _Atom_ describes a term that unifies with _Term_. When _Atom_ is instantiated _Atom_ is converted and then unified with _Term_. If _Atom_ has no valid syntax, a syntax_error exception is raised. Otherwise _Term_ is ``written'' on _Atom_ using [write_term/2](@ref write_term) with the option quoted(true).
  • read_from_chars(+ _Chars_, - _Term_) @anchor read_from_chars Parse the list of character codes _Chars_ and return the result in the term _Term_. The character codes to be read must terminate with a dot character such that either (i) the dot character is followed by blank characters; or (ii) the dot character is the last character in the string.
  • open_chars_stream(+ _Chars_, - _Stream_) @anchor open_chars_stream Open the list of character codes _Chars_ as a stream _Stream_.
  • with_output_to_chars(? _Goal_, - _Chars_) @anchor with_output_to_chars Execute goal _Goal_ such that its standard output will be sent to a memory buffer. After successful execution the contents of the memory buffer will be converted to the list of character codes _Chars_.
  • with_output_to_chars(? _Goal_, ? _Chars0_, - _Chars_) Execute goal _Goal_ such that its standard output will be sent to a memory buffer. After successful execution the contents of the memory buffer will be converted to the difference list of character codes _Chars-Chars0_.
  • with_output_to_chars(? _Goal_, - _Stream_, ? _Chars0_, - _Chars_) Execute goal _Goal_ such that its standard output will be sent to a memory buffer. After successful execution the contents of the memory buffer will be converted to the difference list of character codes _Chars-Chars0_ and _Stream_ receives the stream corresponding to the memory buffer.
The implementation of the character IO operations relies on three YAP built-ins:
  • charsio:open_mem_read_stream(+ _String_, - _Stream_) Store a string in a memory buffer and output a stream that reads from this memory buffer.
  • charsio:open_mem_write_stream(- _Stream_) Create a new memory buffer and output a stream that writes to it.
  • charsio:peek_mem_write_stream(- _Stream_, L0, L) Convert the memory buffer associated with stream _Stream_ to the difference list of character codes _L-L0_.
These built-ins are initialized to belong to the module `charsio` in `init.yap`. Novel procedures for manipulating strings by explicitly importing these built-ins. YAP does not currently support opening a `charsio` stream in `append` mode, or seeking in such a stream. @section System Calling The Operating System from YAP YAP now provides a library of system utilities compatible with the SICStus Prolog system library. This library extends and to some point replaces the functionality of Operating System access routines. The library includes Unix/Linux and Win32 `C` code. They are available through the `use_module(library(system))` command.
  • datime(datime(- _Year_, - _Month_, - _DayOfTheMonth_, @anchor datime - _Hour_, - _Minute_, - _Second_) The [datime/1](@ref datime) procedure returns the current date and time, with information on _Year_, _Month_, _DayOfTheMonth_, _Hour_, _Minute_, and _Second_. The _Hour_ is returned on local time. This function uses the WIN32 `GetLocalTime` function or the Unix `localtime` function. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ?- datime(X). X = datime(2001,5,28,15,29,46) ? ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  • mktime(datime(+ _Year_, + _Month_, + _DayOfTheMonth_, @anchor mktime + _Hour_, + _Minute_, + _Second_), - _Seconds_) The `mktime/1` procedure returns the number of _Seconds_ elapsed since 00:00:00 on January 1, 1970, Coordinated Universal Time (UTC). The user provides information on _Year_, _Month_, _DayOfTheMonth_, _Hour_, _Minute_, and _Second_. The _Hour_ is given on local time. This function uses the WIN32 `GetLocalTime` function or the Unix `mktime` function. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ?- mktime(datime(2001,5,28,15,29,46),X). X = 991081786 ? ; ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  • delete_file(+ _File_) @anchor delete_file The [delete_file/1](@ref delete_file) procedure removes file _File_. If _File_ is a directory, remove the directory and all its subdirectories. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ?- delete_file(x). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  • delete_file(+ _File_,+ _Opts_) The `delete_file/2` procedure removes file _File_ according to options _Opts_. These options are `directory` if one should remove directories, `recursive` if one should remove directories recursively, and `ignore` if errors are not to be reported. This example is equivalent to using the [delete_file/1](@ref delete_file) predicate: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ?- delete_file(x, [recursive]). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  • directory_files(+ _Dir_,+ _List_) @anchor directory_files Given a directory _Dir_, [directory_files/2](@ref directory_files) procedures a listing of all files and directories in the directory: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ?- directory_files('.',L), writeq(L). ['Makefile.~1~','sys.so','Makefile','sys.o',x,..,'.'] ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ The predicates uses the `dirent` family of routines in Unix environments, and `findfirst` in WIN32.
  • file_exists(+ _File_) @anchor file_exists The atom _File_ corresponds to an existing file.
  • file_exists(+ _File_,+ _Permissions_) The atom _File_ corresponds to an existing file with permissions compatible with _Permissions_. YAP currently only accepts for permissions to be described as a number. The actual meaning of this number is Operating System dependent.
  • file_property(+ _File_,? _Property_) @anchor file_property The atom _File_ corresponds to an existing file, and _Property_ will be unified with a property of this file. The properties are of the form `type( _Type_)`, which gives whether the file is a regular file, a directory, a fifo file, or of unknown type; `size( _Size_)`, with gives the size for a file, and `mod_time( _Time_)`, which gives the last time a file was modified according to some Operating System dependent timestamp; `mode( _mode_)`, gives the permission flags for the file, and `linkto( _FileName_)`, gives the file pointed to by a symbolic link. Properties can be obtained through backtracking: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ?- file_property('Makefile',P). P = type(regular) ? ; P = size(2375) ? ; P = mod_time(990826911) ? ; no ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  • make_directory(+ _Dir_) @anchor make_directory Create a directory _Dir_. The name of the directory must be an atom.
  • rename_file(+ _OldFile_,+ _NewFile_) @anchor rename_file Create file _OldFile_ to _NewFile_. This predicate uses the `C` built-in function `rename`.
  • environ(? _EnvVar_,+ _EnvValue_) @anchor sys_environ Unify environment variable _EnvVar_ with its value _EnvValue_, if there is one. This predicate is backtrackable in Unix systems, but not currently in Win32 configurations. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ?- environ('HOME',X). X = 'C:\\cygwin\\home\\administrator' ? ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  • host_id(- _Id_) @anchor host_id Unify _Id_ with an identifier of the current host. YAP uses the `hostid` function when available,
  • host_name(- _Name_) @anchor host_name Unify _Name_ with a name for the current host. YAP uses the `hostname` function in Unix systems when available, and the `GetComputerName` function in WIN32 systems.
  • kill( _Id_,+ _SIGNAL_) @anchor kill Send signal _SIGNAL_ to process _Id_. In Unix this predicate is a direct interface to `kill` so one can send signals to groups of processes. In WIN32 the predicate is an interface to `TerminateProcess`, so it kills _Id_ independently of _SIGNAL_.
  • mktemp( _Spec_,- _File_) @anchor mktemp Direct interface to `mktemp`: given a _Spec_, that is a file name with six _X_ to it, create a file name _File_. Use [tmpnam/1](@ref tmpnam) instead.
  • pid(- _Id_) @anchor pid Unify _Id_ with the process identifier for the current process. An interface to the getpid function.
  • tmpnam(- _File_) @anchor tmpnam Interface with _tmpnam_: obtain a new, unique file name _File_.
  • tmp_file(- _File_) @anchor tmp_file Create a name for a temporary file. _Base_ is an user provided identifier for the category of file. The _TmpName_ is guaranteed to be unique. If the system halts, it will automatically remove all created temporary files.
  • exec(+ _Command_,[+ _InputStream_,+ _OutputStream_,+ _ErrorStream_],- _PID_) @anchor exec Execute command _Command_ with its streams connected to _InputStream_, _OutputStream_, and _ErrorStream_. The process that executes the command is returned as _PID_. The command is executed by the default shell `bin/sh -c` in Unix. The following example demonstrates the use of [exec/3](@ref exec) to send a command and process its output: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ exec(ls,[std,pipe(S),null],P),repeat, get0(S,C), (C = -1, close(S) ! ; put(C)). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ The streams may be one of standard stream, `std`, null stream, `null`, or `pipe(S)`, where _S_ is a pipe stream. Note that it is up to the user to close the pipe.
  • popen(+ _Command_, + _TYPE_, - _Stream_) @anchor popen Interface to the popen function. It opens a process by creating a pipe, forking and invoking _Command_ on the current shell. Since a pipe is by definition unidirectional the _Type_ argument may be `read` or `write`, not both. The stream should be closed using [close/1](@ref close), there is no need for a special `pclose` command. The following example demonstrates the use of [popen/3](@ref popen) to process the output of a command, as [exec/3](@ref exec) would do: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~{.prolog} ?- popen(ls,read,X),repeat, get0(X,C), (C = -1, ! ; put(C)). X = 'C:\\cygwin\\home\\administrator' ? ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ The WIN32 implementation of [popen/3](@ref popen) relies on [exec/3](@ref exec).
  • shell @anchor shell Start a new shell and leave YAP in background until the shell completes. YAP uses the shell given by the environment variable `SHELL`. In WIN32 environment YAP will use `COMSPEC` if `SHELL` is undefined.
  • shell(+ _Command_) Execute command _Command_ under a new shell. YAP will be in background until the command completes. In Unix environments YAP uses the shell given by the environment variable `SHELL` with the option `" -c "`. In WIN32 environment YAP will use `COMSPEC` if `SHELL` is undefined, in this case with the option `" /c "`.
  • shell(+ _Command_,- _Status_) Execute command _Command_ under a new shell and unify _Status_ with the exit for the command. YAP will be in background until the command completes. In Unix environments YAP uses the shell given by the environment variable `SHELL` with the option `" -c "`. In WIN32 environment YAP will use `COMSPEC` if `SHELL` is undefined, in this case with the option `" /c "`.
  • sleep(+ _Time_) @anchor sleep Block the current thread for _Time_ seconds. When YAP is compiled without multi-threading support, this predicate blocks the YAP process. The number of seconds must be a positive number, and it may an integer or a float. The Unix implementation uses `usleep` if the number of seconds is below one, and `sleep` if it is over a second. The WIN32 implementation uses `Sleep` for both cases.
  • system Start a new default shell and leave YAP in background until the shell completes. YAP uses `/bin/sh` in Unix systems and `COMSPEC` in WIN32.
  • system(+ _Command_,- _Res_) Interface to `system`: execute command _Command_ and unify _Res_ with the result.
  • wait(+ _PID_,- _Status_) @anchor wait Wait until process _PID_ terminates, and return its exits _Status_.
@section Terms Utilities On Terms The next routines provide a set of commonly used utilities to manipulate terms. Most of these utilities have been implemented in `C` for efficiency. They are available through the `use_module(library(terms))` command.
  • cyclic_term(? _Term_) @anchor cyclic_term Succeed if the argument _Term_ is not a cyclic term.
  • term_hash(+ _Term_, ? _Hash_) @anchor term_hash If _Term_ is ground unify _Hash_ with a positive integer calculated from the structure of the term. Otherwise the argument _Hash_ is left unbound. The range of the positive integer is from `0` to, but not including, `33554432`.
  • term_hash(+ _Term_, + _Depth_, + _Range_, ? _Hash_) Unify _Hash_ with a positive integer calculated from the structure of the term. The range of the positive integer is from `0` to, but not including, _Range_. If _Depth_ is `-1` the whole term is considered. Otherwise, the term is considered only up to depth `1`, where the constants and the principal functor have depth `1`, and an argument of a term with depth _I_ has depth _I+1_.
  • variables_within_term(+ _Variables_,? _Term_, - _OutputVariables_) @anchor variables_within_term Unify _OutputVariables_ with the subset of the variables _Variables_ that occurs in _Term_.
  • new_variables_in_term(+ _Variables_,? _Term_, - _OutputVariables_) @anchor new_variables_in_term Unify _OutputVariables_ with all variables occurring in _Term_ that are not in the list _Variables_.
  • variant(? _Term1_, ? _Term2_) @anchor variant Succeed if _Term1_ and _Term2_ are variant terms.
  • subsumes(? _Term1_, ? _Term2_) @anchor subsumes Succeed if _Term1_ subsumes _Term2_. Variables in term _Term1_ are bound so that the two terms become equal.
  • subsumes_chk(? _Term1_, ? _Term2_) @anchor subsumes_chk Succeed if _Term1_ subsumes _Term2_ but does not bind any variable in _Term1_.
  • variable_in_term(? _Term_,? _Var_) @anchor variable_in_term Succeed if the second argument _Var_ is a variable and occurs in term _Term_.
  • unifiable(? _Term1_, ? _Term2_, - _Bindings_) @anchor unifiable Succeed if _Term1_ and _Term2_ are unifiable with substitution _Bindings_.
@section Tries Trie DataStructure The next routines provide a set of utilities to create and manipulate prefix trees of Prolog terms. Tries were originally proposed to implement tabling in Logic Programming, but can be used for other purposes. The tries will be stored in the Prolog database and can seen as alternative to `assert` and `record` family of primitives. Most of these utilities have been implemented in `C` for efficiency. They are available through the `use_module(library(tries))` command.
  • trie_open(- _Id_) @anchor trie_open Open a new trie with identifier _Id_.
  • trie_close(+ _Id_) @anchor trie_close Close trie with identifier _Id_.
  • trie_close_all @anchor trie_close_all Close all available tries.
  • trie_mode(? _Mode_) @anchor trie_mode Unify _Mode_ with trie operation mode. Allowed values are either `std` (default) or `rev`.
  • trie_put_entry(+ _Trie_,+ _Term_,- _Ref_) @anchor trie_put_entry Add term _Term_ to trie _Trie_. The handle _Ref_ gives a reference to the term.
  • trie_check_entry(+ _Trie_,+ _Term_,- _Ref_) @anchor trie_check_entry Succeeds if a variant of term _Term_ is in trie _Trie_. An handle _Ref_ gives a reference to the term.
  • trie_get_entry(+ _Ref_,- _Term_) @anchor trie_get_entry Unify _Term_ with the entry for handle _Ref_.
  • trie_remove_entry(+ _Ref_) @anchor trie_remove_entry Remove entry for handle _Ref_.
  • trie_remove_subtree(+ _Ref_) @anchor trie_remove_subtree Remove subtree rooted at handle _Ref_.
  • trie_save(+ _Trie_,+ _FileName_) @anchor trie_save Dump trie _Trie_ into file _FileName_.
  • trie_load(+ _Trie_,+ _FileName_) @anchor trie_load Load trie _Trie_ from the contents of file _FileName_.
  • trie_stats(- _Memory_,- _Tries_,- _Entries_,- _Nodes_) @anchor trie_stats Give generic statistics on tries, including the amount of memory, _Memory_, the number of tries, _Tries_, the number of entries, _Entries_, and the total number of nodes, _Nodes_.
  • trie_max_stats(- _Memory_,- _Tries_,- _Entries_,- _Nodes_) @anchor trie_max_stats Give maximal statistics on tries, including the amount of memory, _Memory_, the number of tries, _Tries_, the number of entries, _Entries_, and the total number of nodes, _Nodes_.
  • trie_usage(+ _Trie_,- _Entries_,- _Nodes_,- _VirtualNodes_) @anchor trie_usage Give statistics on trie _Trie_, the number of entries, _Entries_, and the total number of nodes, _Nodes_, and the number of _VirtualNodes_.
  • trie_print(+ _Trie_) @anchor trie_print Print trie _Trie_ on standard output.
@section Cleanup Call Cleanup call_cleanup/1 and call_cleanup/2 allow predicates to register code for execution after the call is finished. Predicates can be declared to be fragile to ensure that call_cleanup is called for any Goal which needs it. This library is loaded with the `use_module(library(cleanup))` command.
  • :- fragile _P_,...., _Pn_ @anchor fragile Declares the predicate _P_=[module:]name/arity as a fragile predicate, module is optional, default is the current typein_module. Whenever such a fragile predicate is used in a query it will be called through call_cleanup/1. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~{.prolog} :- fragile foo/1,bar:baz/2. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  • call_cleanup(: _Goal_) @anchor call_cleanup Execute goal _Goal_ within a cleanup-context. Called predicates might register cleanup Goals which are called right after the end of the call to _Goal_. Cuts and exceptions inside Goal do not prevent the execution of the cleanup calls. call_cleanup might be nested.
  • call_cleanup(: _Goal_, : _CleanUpGoal_) This is similar to call_cleanup/1 with an additional _CleanUpGoal_ which gets called after _Goal_ is finished.
  • setup_call_cleanup(: _Setup_,: _Goal_, : _CleanUpGoal_) @anchor setup_call_cleanup Calls `(Setup, Goal)`. For each sucessful execution of _Setup_, calling _Goal_, the cleanup handler _Cleanup_ is guaranteed to be called exactly once. This will happen after _Goal_ completes, either through failure, deterministic success, commit, or an exception. _Setup_ will contain the goals that need to be protected from asynchronous interrupts such as the ones received from `call_with_time_limit/2` or [thread_signal/2](@ref thread_signal). In most uses, _Setup_ will perform temporary side-effects required by _Goal_ that are finally undone by _Cleanup_. Success or failure of _Cleanup_ is ignored and choice-points it created are destroyed (as [once/1](@ref once)). If _Cleanup_ throws an exception, this is executed as normal. Typically, this predicate is used to cleanup permanent data storage required to execute _Goal_, close file-descriptors, etc. The example below provides a non-deterministic search for a term in a file, closing the stream as needed. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~{.prolog} term_in_file(Term, File) :- setup_call_cleanup(open(File, read, In), term_in_stream(Term, In), close(In) ). term_in_stream(Term, In) :- repeat, read(In, T), ( T == end_of_file -> !, fail ; T = Term ). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Note that it is impossible to implement this predicate in Prolog other than by reading all terms into a list, close the file and call [member/2](@ref member). Without [setup_call_cleanup/3](@ref setup_call_cleanup) there is no way to gain control if the choice-point left by `repeat` is removed by a cut or an exception. `setup_call_cleanup/2` can also be used to test determinism of a goal: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ?- setup_call_cleanup(true,(X=1;X=2), Det=yes). X = 1 ; X = 2, Det = yes ; ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ This predicate is under consideration for inclusion into the ISO standard. For compatibility with other Prolog implementations see `call_cleanup/2`.
  • setup_call_catcher_cleanup(: _Setup_,: _Goal_, + _Catcher_,: _CleanUpGoal_) @anchor setup_call_catcher_cleanup Similar to `setup_call_cleanup( _Setup_, _Goal_, _Cleanup_)` with additional information on the reason of calling _Cleanup_. Prior to calling _Cleanup_, _Catcher_ unifies with the termination code. If this unification fails, _Cleanup_ is *not* called.
  • on_cleanup(+ _CleanUpGoal_) @anchor on_cleanup Any Predicate might registers a _CleanUpGoal_. The _CleanUpGoal_ is put onto the current cleanup context. All such CleanUpGoals are executed in reverse order of their registration when the surrounding cleanup-context ends. This call will throw an exception if a predicate tries to register a _CleanUpGoal_ outside of any cleanup-context.
  • cleanup_all @anchor cleanup_all Calls all pending CleanUpGoals and resets the cleanup-system to an initial state. Should only be used as one of the last calls in the main program.
There are some private predicates which could be used in special cases, such as manually setting up cleanup-contexts and registering CleanUpGoals for other than the current cleanup-context. Read the Source Luke. @section Timeout Calls With Timeout The time_out/3 command relies on the alarm/3 built-in to implement a call with a maximum time of execution. The command is available with the `use_module(library(timeout))` command.
  • time_out(+ _Goal_, + _Timeout_, - _Result_) @anchor time_out Execute goal _Goal_ with time limited _Timeout_, where _Timeout_ is measured in milliseconds. If the goal succeeds, unify _Result_ with success. If the timer expires before the goal terminates, unify _Result_ with time_out. This command is implemented by activating an alarm at procedure entry. If the timer expires before the goal completes, the alarm will throw an exception _timeout_. One should note that [time_out/3](@ref time_out) is not reentrant, that is, a goal called from `time_out` should never itself call [time_out/3](@ref time_out). Moreover, [time_out/3](@ref time_out) will deactivate any previous alarms set by [alarm/3](@ref alarm) and vice-versa, hence only one of these calls should be used in a program. Last, even though the timer is set in milliseconds, the current implementation relies on alarm/3, and therefore can only offer precision on the scale of seconds.
@section Trees Updatable Binary Trees The following queue manipulation routines are available once included with the `use_module(library(trees))` command.
  • get_label(+ _Index_, + _Tree_, ? _Label_) @anchor get_label Treats the tree as an array of _N_ elements and returns the _Index_-th.
  • list_to_tree(+ _List_, - _Tree_) @anchor list_to_tree Takes a given _List_ of _N_ elements and constructs a binary _Tree_.
  • map_tree(+ _Pred_, + _OldTree_, - _NewTree_) @anchor map_tree Holds when _OldTree_ and _NewTree_ are binary trees of the same shape and `Pred(Old,New)` is true for corresponding elements of the two trees.
  • put_label(+ _Index_, + _OldTree_, + _Label_, - _NewTree_) @anchor put_label constructs a new tree the same shape as the old which moreover has the same elements except that the _Index_-th one is _Label_.
  • tree_size(+ _Tree_, - _Size_) @anchor tree_size Calculates the number of elements in the _Tree_.
  • tree_to_list(+ _Tree_, - _List_) @anchor tree_to_list Is the converse operation to list_to_tree.
@section UGraphs Unweighted Graphs The following graph manipulation routines are based in code originally written by Richard O'Keefe. The code was then extended to be compatible with the SICStus Prolog ugraphs library. The routines assume directed graphs, undirected graphs may be implemented by using two edges. Graphs are represented in one of two ways:
  • The P-representation of a graph is a list of (from-to) vertex pairs, where the pairs can be in any old order. This form is convenient for input/output.
  • The S-representation of a graph is a list of (vertex-neighbors) pairs, where the pairs are in standard order (as produced by keysort) and the neighbors of each vertex are also in standard order (as produced by sort). This form is convenient for many calculations.
These built-ins are available once included with the `use_module(library(ugraphs))` command.
  • vertices_edges_to_ugraph(+ _Vertices_, + _Edges_, - _Graph_) @anchor vertices_edges_to_ugraph Given a graph with a set of vertices _Vertices_ and a set of edges _Edges_, _Graph_ must unify with the corresponding s-representation. Note that the vertices without edges will appear in _Vertices_ but not in _Edges_. Moreover, it is sufficient for a vertex to appear in _Edges_. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~{.prolog} ?- vertices_edges_to_ugraph([],[1-3,2-4,4-5,1-5],L). L = [1-[3,5],2-[4],3-[],4-[5],5-[]] ? ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ In this case all edges are defined implicitly. The next example shows three unconnected edges: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~{.prolog} ?- vertices_edges_to_ugraph([6,7,8],[1-3,2-4,4-5,1-5],L). L = [1-[3,5],2-[4],3-[],4-[5],5-[],6-[],7-[],8-[]] ? ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  • vertices(+ _Graph_, - _Vertices_) @anchor vertices Unify _Vertices_ with all vertices appearing in graph _Graph_. In the next example: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~{.prolog} ?- vertices([1-[3,5],2-[4],3-[],4-[5],5-[]], V). L = [1,2,3,4,5] ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  • edges(+ _Graph_, - _Edges_) @anchor edges Unify _Edges_ with all edges appearing in graph _Graph_. In the next example: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~{.prolog} ?- vertices([1-[3,5],2-[4],3-[],4-[5],5-[]], V). L = [1,2,3,4,5] ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  • add_vertices(+ _Graph_, + _Vertices_, - _NewGraph_) @anchor add_vertices Unify _NewGraph_ with a new graph obtained by adding the list of vertices _Vertices_ to the graph _Graph_. In the next example: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~{.prolog} ?- add_vertices([1-[3,5],2-[4],3-[],4-[5], 5-[],6-[],7-[],8-[]], [0,2,9,10,11], NG). NG = [0-[],1-[3,5],2-[4],3-[],4-[5],5-[], 6-[],7-[],8-[],9-[],10-[],11-[]] ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  • del_vertices(+ _Graph_, + _Vertices_, - _NewGraph_) @anchor del_vertices Unify _NewGraph_ with a new graph obtained by deleting the list of vertices _Vertices_ and all the edges that start from or go to a vertex in _Vertices_ to the graph _Graph_. In the next example: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~{.prolog} ?- del_vertices([2,1],[1-[3,5],2-[4],3-[], 4-[5],5-[],6-[],7-[2,6],8-[]],NL). NL = [3-[],4-[5],5-[],6-[],7-[6],8-[]] ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  • add_edges(+ _Graph_, + _Edges_, - _NewGraph_) @anchor add_edges Unify _NewGraph_ with a new graph obtained by adding the list of edges _Edges_ to the graph _Graph_. In the next example: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~{.prolog} ?- add_edges([1-[3,5],2-[4],3-[],4-[5],5-[],6-[], 7-[],8-[]],[1-6,2-3,3-2,5-7,3-2,4-5],NL). NL = [1-[3,5,6],2-[3,4],3-[2],4-[5],5-[7],6-[],7-[],8-[]] ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  • del_edges(+ _Graph_, + _Edges_, - _NewGraph_) @anchor del_edges Unify _NewGraph_ with a new graph obtained by removing the list of edges _Edges_ from the graph _Graph_. Notice that no vertices are deleted. In the next example: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~{.prolog} ?- del_edges([1-[3,5],2-[4],3-[],4-[5],5-[], 6-[],7-[],8-[]], [1-6,2-3,3-2,5-7,3-2,4-5,1-3],NL). NL = [1-[5],2-[4],3-[],4-[],5-[],6-[],7-[],8-[]] ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  • transpose(+ _Graph_, - _NewGraph_) @anchor transpose Unify _NewGraph_ with a new graph obtained from _Graph_ by replacing all edges of the form _V1-V2_ by edges of the form _V2-V1_. The cost is `O(|V|^2)`. In the next example: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~{.prolog} ?- transpose([1-[3,5],2-[4],3-[], 4-[5],5-[],6-[],7-[],8-[]], NL). NL = [1-[],2-[],3-[1],4-[2],5-[1,4],6-[],7-[],8-[]] ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Notice that an undirected graph is its own transpose.
  • neighbors(+ _Vertex_, + _Graph_, - _Vertices_) @anchor neighbors Unify _Vertices_ with the list of neighbors of vertex _Vertex_ in _Graph_. If the vertice is not in the graph fail. In the next example: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~{.prolog} ?- neighbors(4,[1-[3,5],2-[4],3-[], 4-[1,2,7,5],5-[],6-[],7-[],8-[]], NL). NL = [1,2,7,5] ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  • neighbours(+ _Vertex_, + _Graph_, - _Vertices_) @anchor neighbours Unify _Vertices_ with the list of neighbours of vertex _Vertex_ in _Graph_. In the next example: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~{.prolog} ?- neighbours(4,[1-[3,5],2-[4],3-[], 4-[1,2,7,5],5-[],6-[],7-[],8-[]], NL). NL = [1,2,7,5] ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  • complement(+ _Graph_, - _NewGraph_) @anchor complement Unify _NewGraph_ with the graph complementary to _Graph_. In the next example: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~{.prolog} ?- complement([1-[3,5],2-[4],3-[], 4-[1,2,7,5],5-[],6-[],7-[],8-[]], NL). NL = [1-[2,4,6,7,8],2-[1,3,5,6,7,8],3-[1,2,4,5,6,7,8], 4-[3,5,6,8],5-[1,2,3,4,6,7,8],6-[1,2,3,4,5,7,8], 7-[1,2,3,4,5,6,8],8-[1,2,3,4,5,6,7]] ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  • compose(+ _LeftGraph_, + _RightGraph_, - _NewGraph_) @anchor compose Compose the graphs _LeftGraph_ and _RightGraph_ to form _NewGraph_. In the next example: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~{.prolog} ?- compose([1-[2],2-[3]],[2-[4],3-[1,2,4]],L). L = [1-[4],2-[1,2,4],3-[]] ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  • top_sort(+ _Graph_, - _Sort_) @anchor top_sort Generate the set of nodes _Sort_ as a topological sorting of graph _Graph_, if one is possible. In the next example we show how topological sorting works for a linear graph: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~{.prolog} ?- top_sort([_138-[_219],_219-[_139], _139-[]],L). L = [_138,_219,_139] ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  • top_sort(+ _Graph_, - _Sort0_, - _Sort_) Generate the difference list _Sort_- _Sort0_ as a topological sorting of graph _Graph_, if one is possible.
  • transitive_closure(+ _Graph_, + _Closure_) @anchor transitive_closure Generate the graph _Closure_ as the transitive closure of graph _Graph_. In the next example: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~{.prolog} ?- transitive_closure([1-[2,3],2-[4,5],4-[6]],L). L = [1-[2,3,4,5,6],2-[4,5,6],4-[6]] ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  • reachable(+ _Node_, + _Graph_, - _Vertices_) @anchor reachable Unify _Vertices_ with the set of all vertices in graph _Graph_ that are reachable from _Node_. In the next example: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~{.prolog} ?- reachable(1,[1-[3,5],2-[4],3-[],4-[5],5-[]],V). V = [1,3,5] ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
@section DGraphs Directed Graphs The following graph manipulation routines use the red-black tree library to try to avoid linear-time scans of the graph for all graph operations. Graphs are represented as a red-black tree, where the key is the vertex, and the associated value is a list of vertices reachable from that vertex through an edge (ie, a list of edges).
  • dgraph_new(+ _Graph_) @anchor dgraph_new Create a new directed graph. This operation must be performed before trying to use the graph.
  • dgraph_vertices(+ _Graph_, - _Vertices_) @anchor dgraph_vertices Unify _Vertices_ with all vertices appearing in graph _Graph_.
  • dgraph_edge(+ _N1_, + _N2_, + _Graph_) @anchor dgraph_edge Edge _N1_- _N2_ is an edge in directed graph _Graph_.
  • dgraph_edges(+ _Graph_, - _Edges_) @anchor dgraph_edges Unify _Edges_ with all edges appearing in graph _Graph_.
  • dgraph_add_vertices(+ _Graph_, + _Vertex_, - _NewGraph_) @anchor dgraph_add_vertex Unify _NewGraph_ with a new graph obtained by adding vertex _Vertex_ to the graph _Graph_.
  • dgraph_add_vertices(+ _Graph_, + _Vertices_, - _NewGraph_) @anchor dgraph_add_vertices Unify _NewGraph_ with a new graph obtained by adding the list of vertices _Vertices_ to the graph _Graph_.
  • dgraph_del_vertex(+ _Graph_, + _Vertex_, - _NewGraph_) @anchor dgraph_del_vertex Unify _NewGraph_ with a new graph obtained by deleting vertex _Vertex_ and all the edges that start from or go to _Vertex_ to the graph _Graph_.
  • dgraph_del_vertices(+ _Graph_, + _Vertices_, - _NewGraph_) @anchor dgraph_del_vertices Unify _NewGraph_ with a new graph obtained by deleting the list of vertices _Vertices_ and all the edges that start from or go to a vertex in _Vertices_ to the graph _Graph_.
  • dgraph_add_edge(+ _Graph_, + _N1_, + _N2_, - _NewGraph_) @anchor dgraph_add_edge Unify _NewGraph_ with a new graph obtained by adding the edge _N1_- _N2_ to the graph _Graph_.
  • dgraph_add_edges(+ _Graph_, + _Edges_, - _NewGraph_) @anchor dgraph_add_edges Unify _NewGraph_ with a new graph obtained by adding the list of edges _Edges_ to the graph _Graph_.
  • dgraph_del_edge(+ _Graph_, + _N1_, + _N2_, - _NewGraph_) @anchor dgraph_del_edge Succeeds if _NewGraph_ unifies with a new graph obtained by removing the edge _N1_- _N2_ from the graph _Graph_. Notice that no vertices are deleted.
  • dgraph_del_edges(+ _Graph_, + _Edges_, - _NewGraph_) @anchor dgraph_del_edges Unify _NewGraph_ with a new graph obtained by removing the list of edges _Edges_ from the graph _Graph_. Notice that no vertices are deleted.
  • dgraph_to_ugraph(+ _Graph_, - _UGraph_) @anchor dgraph_to_ugraph Unify _UGraph_ with the representation used by the _ugraphs_ unweighted graphs library, that is, a list of the form _V-Neighbors_, where _V_ is a node and _Neighbors_ the nodes children.
  • ugraph_to_dgraph( + _UGraph_, - _Graph_) @anchor ugraph_to_dgraph Unify _Graph_ with the directed graph obtain from _UGraph_, represented in the form used in the _ugraphs_ unweighted graphs library.
  • dgraph_neighbors(+ _Vertex_, + _Graph_, - _Vertices_) @anchor dgraph_neighbors Unify _Vertices_ with the list of neighbors of vertex _Vertex_ in _Graph_. If the vertice is not in the graph fail.
  • dgraph_neighbours(+ _Vertex_, + _Graph_, - _Vertices_) @anchor dgraph_neighbours Unify _Vertices_ with the list of neighbours of vertex _Vertex_ in _Graph_.
  • dgraph_complement(+ _Graph_, - _NewGraph_) @anchor dgraph_complement Unify _NewGraph_ with the graph complementary to _Graph_.
  • dgraph_transpose(+ _Graph_, - _Transpose_) @anchor dgraph_transpose Unify _NewGraph_ with a new graph obtained from _Graph_ by replacing all edges of the form _V1-V2_ by edges of the form _V2-V1_.
  • dgraph_compose(+ _Graph1_, + _Graph2_, - _ComposedGraph_) @anchor dgraph_compose Unify _ComposedGraph_ with a new graph obtained by composing _Graph1_ and _Graph2_, ie, _ComposedGraph_ has an edge _V1-V2_ iff there is a _V_ such that _V1-V_ in _Graph1_ and _V-V2_ in _Graph2_.
  • dgraph_transitive_closure(+ _Graph_, - _Closure_) @anchor dgraph_transitive_closure Unify _Closure_ with the transitive closure of graph _Graph_.
  • dgraph_symmetric_closure(+ _Graph_, - _Closure_) @anchor dgraph_symmetric_closure Unify _Closure_ with the symmetric closure of graph _Graph_, that is, if _Closure_ contains an edge _U-V_ it must also contain the edge _V-U_.
  • dgraph_top_sort(+ _Graph_, - _Vertices_) @anchor dgraph_top_sort Unify _Vertices_ with the topological sort of graph _Graph_.
  • dgraph_top_sort(+ _Graph_, - _Vertices_, ? _Vertices0_) Unify the difference list _Vertices_- _Vertices0_ with the topological sort of graph _Graph_.
  • dgraph_min_path(+ _V1_, + _V1_, + _Graph_, - _Path_, ? _Costt_) @anchor dgraph_min_path Unify the list _Path_ with the minimal cost path between nodes _N1_ and _N2_ in graph _Graph_. Path _Path_ has cost _Cost_.
  • dgraph_max_path(+ _V1_, + _V1_, + _Graph_, - _Path_, ? _Costt_) @anchor dgraph_max_path Unify the list _Path_ with the maximal cost path between nodes _N1_ and _N2_ in graph _Graph_. Path _Path_ has cost _Cost_.
  • dgraph_min_paths(+ _V1_, + _Graph_, - _Paths_) @anchor dgraph_min_paths Unify the list _Paths_ with the minimal cost paths from node _N1_ to the nodes in graph _Graph_.
  • dgraph_isomorphic(+ _Vs_, + _NewVs_, + _G0_, - _GF_) @anchor dgraph_isomorphic Unify the list _GF_ with the graph isomorphic to _G0_ where vertices in _Vs_ map to vertices in _NewVs_.
  • dgraph_path(+ _Vertex_, + _Graph_, ? _Path_) @anchor dgraph_path The path _Path_ is a path starting at vertex _Vertex_ in graph _Graph_.
  • dgraph_path(+ _Vertex_, + _Vertex1_, + _Graph_, ? _Path_) The path _Path_ is a path starting at vertex _Vertex_ in graph _Graph_ and ending at path _Vertex2_.
  • dgraph_reachable(+ _Vertex_, + _Graph_, ? _Edges_) @anchor dgraph_reachable The path _Path_ is a path starting at vertex _Vertex_ in graph _Graph_.
  • dgraph_leaves(+ _Graph_, ? _Vertices_) @anchor dgraph_leaves The vertices _Vertices_ have no outgoing edge in graph _Graph_.
@section UnDGraphs Undirected Graphs The following graph manipulation routines use the red-black tree graph library to implement undirected graphs. Mostly, this is done by having two directed edges per undirected edge.
  • undgraph_new(+ _Graph_) @anchor undgraph_new Create a new directed graph. This operation must be performed before trying to use the graph.
  • undgraph_vertices(+ _Graph_, - _Vertices_) @anchor undgraph_vertices Unify _Vertices_ with all vertices appearing in graph _Graph_.
  • undgraph_edge(+ _N1_, + _N2_, + _Graph_) @anchor undgraph_edge Edge _N1_- _N2_ is an edge in undirected graph _Graph_.
  • undgraph_edges(+ _Graph_, - _Edges_) @anchor undgraph_edges Unify _Edges_ with all edges appearing in graph _Graph_.
  • undgraph_add_vertices(+ _Graph_, + _Vertices_, - _NewGraph_) @anchor undgraph_add_vertices Unify _NewGraph_ with a new graph obtained by adding the list of vertices _Vertices_ to the graph _Graph_.
  • undgraph_del_vertices(+ _Graph_, + _Vertices_, - _NewGraph_) @anchor undgraph_del_vertices Unify _NewGraph_ with a new graph obtained by deleting the list of vertices _Vertices_ and all the edges that start from or go to a vertex in _Vertices_ to the graph _Graph_.
  • undgraph_add_edges(+ _Graph_, + _Edges_, - _NewGraph_) @anchor undgraph_add_edges Unify _NewGraph_ with a new graph obtained by adding the list of edges _Edges_ to the graph _Graph_.
  • undgraph_del_edges(+ _Graph_, + _Edges_, - _NewGraph_) @anchor undgraph_del_edges Unify _NewGraph_ with a new graph obtained by removing the list of edges _Edges_ from the graph _Graph_. Notice that no vertices are deleted.
  • undgraph_neighbors(+ _Vertex_, + _Graph_, - _Vertices_) @anchor undgraph_neighbors Unify _Vertices_ with the list of neighbors of vertex _Vertex_ in _Graph_. If the vertice is not in the graph fail.
  • undgraph_neighbours(+ _Vertex_, + _Graph_, - _Vertices_) @anchor undgraph_neighbours Unify _Vertices_ with the list of neighbours of vertex _Vertex_ in _Graph_.
  • undgraph_complement(+ _Graph_, - _NewGraph_) @anchor undgraph_complement Unify _NewGraph_ with the graph complementary to _Graph_.
  • dgraph_to_undgraph( + _DGraph_, - _UndGraph_) @anchor dgraph_to_undgraph Unify _UndGraph_ with the undirected graph obtained from the directed graph _DGraph_.
@section DBUsage Memory Usage in Prolog Data-Base This library provides a set of utilities for studying memory usage in YAP. The following routines are available once included with the `use_module(library(dbusage))` command.
  • db_usage @anchor db_usage Give general overview of data-base usage in the system.
  • db_static @anchor db_static List memory usage for every static predicate.
  • db_static(+ _Threshold_) List memory usage for every static predicate. Predicate must use more than _Threshold_ bytes.
  • db_dynamic @anchor db_dynamic List memory usage for every dynamic predicate.
  • db_dynamic(+ _Threshold_) List memory usage for every dynamic predicate. Predicate must use more than _Threshold_ bytes.
@section Lambda Lambda Expressions This library, designed and implemented by Ulrich Neumerkel, provides lambda expressions to simplify higher order programming based on `call/N`. Lambda expressions are represented by ordinary Prolog terms. There are two kinds of lambda expressions: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~{.prolog} Free+\X1^X2^ ..^XN^Goal \X1^X2^ ..^XN^Goal ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ The second is a shorthand for` t+\\X1^X2^..^XN^Goal`, where `Xi` are the parameters. _Goal_ is a goal or continuation (Syntax note: _Operators_ within _Goal_ require parentheses due to the low precedence of the `^` operator). Free contains variables that are valid outside the scope of the lambda expression. They are thus free variables within. All other variables of _Goal_ are considered local variables. They must not appear outside the lambda expression. This restriction is currently not checked. Violations may lead to unexpected bindings. In the following example the parentheses around `X\>3` are necessary. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~{.prolog} ?- use_module(library(lambda)). ?- use_module(library(apply)). ?- maplist(\X^(X>3),[4,5,9]). true. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ In the following _X_ is a variable that is shared by both instances of the lambda expression. The second query illustrates the cooperation of continuations and lambdas. The lambda expression is in this case a continuation expecting a further argument. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~{.prolog} ?- Xs = [A,B], maplist(X+\Y^dif(X,Y), Xs). Xs = [A, B], dif(X, A), dif(X, B). ?- Xs = [A,B], maplist(X+\dif(X), Xs). Xs = [A, B], dif(X, A), dif(X, B). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ The following queries are all equivalent. To see this, use the fact `f(x,y)`. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~{.prolog} ?- call(f,A1,A2). ?- call(\X^f(X),A1,A2). ?- call(\X^Y^f(X,Y), A1,A2). ?- call(\X^(X+\Y^f(X,Y)), A1,A2). ?- call(call(f, A1),A2). ?- call(f(A1),A2). ?- f(A1,A2). A1 = x, A2 = y. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Further discussions at Ulrich Neumerker's page in . @section LAM LAM This library provides a set of utilities for interfacing with LAM MPI. The following routines are available once included with the `use_module(library(lam_mpi))` command. The yap should be invoked using the LAM mpiexec or mpirun commands (see LAM manual for more details).
  • mpi_init @anchor mpi_init Sets up the mpi environment. This predicate should be called before any other MPI predicate.
  • mpi_finalize @anchor mpi_finalize Terminates the MPI execution environment. Every process must call this predicate before exiting.
  • mpi_comm_size(- _Size_) @anchor mpi_comm_size Unifies _Size_ with the number of processes in the MPI environment.
  • mpi_comm_rank(- _Rank_) @anchor mpi_comm_rank Unifies _Rank_ with the rank of the current process in the MPI environment.
  • mpi_version(- _Major_,- _Minor_) @anchor mpi_version Unifies _Major_ and _Minor_ with, respectively, the major and minor version of the MPI.
  • mpi_send(+ _Data_,+ _Dest_,+ _Tag_) @anchor mpi_send Blocking communication predicate. The message in _Data_, with tag _Tag_, is sent immediately to the processor with rank _Dest_. The predicate succeeds after the message being sent.
  • mpi_isend(+ _Data_,+ _Dest_,+ _Tag_,- _Handle_) @anchor mpi_isend Non blocking communication predicate. The message in _Data_, with tag _Tag_, is sent whenever possible to the processor with rank _Dest_. An _Handle_ to the message is returned to be used to check for the status of the message, using the `mpi_wait` or `mpi_test` predicates. Until `mpi_wait` is called, the memory allocated for the buffer containing the message is not released.
  • mpi_recv(? _Source_,? _Tag_,- _Data_) @anchor mpi_recv Blocking communication predicate. The predicate blocks until a message is received from processor with rank _Source_ and tag _Tag_. The message is placed in _Data_.
  • mpi_irecv(? _Source_,? _Tag_,- _Handle_) @anchor mpi_irecv Non-blocking communication predicate. The predicate returns an _Handle_ for a message that will be received from processor with rank _Source_ and tag _Tag_. Note that the predicate succeeds immediately, even if no message has been received. The predicate `mpi_wait_recv` should be used to obtain the data associated to the handle.
  • mpi_wait_recv(? _Handle_,- _Status_,- _Data_) @anchor mpi_wait_recv Completes a non-blocking receive operation. The predicate blocks until a message associated with handle _Hanlde_ is buffered. The predicate succeeds unifying _Status_ with the status of the message and _Data_ with the message itself.
  • mpi_test_recv(? _Handle_,- _Status_,- _Data_) @anchor mpi_test_recv Provides information regarding a handle. If the message associated with handle _Hanlde_ is buffered then the predicate succeeds unifying _Status_ with the status of the message and _Data_ with the message itself. Otherwise, the predicate fails.
  • mpi_wait(? _Handle_,- _Status_) @anchor mpi_wait Completes a non-blocking operation. If the operation was a `mpi_send`, the predicate blocks until the message is buffered or sent by the runtime system. At this point the send buffer is released. If the operation was a `mpi_recv`, it waits until the message is copied to the receive buffer. _Status_ is unified with the status of the message.
  • mpi_test(? _Handle_,- _Status_) @anchor mpi_test Provides information regarding the handle _Handle_, ie., if a communication operation has been completed. If the operation associate with _Hanlde_ has been completed the predicate succeeds with the completion status in _Status_, otherwise it fails.
  • mpi_barrier @anchor mpi_barrier Collective communication predicate. Performs a barrier synchronization among all processes. Note that a collective communication means that all processes call the same predicate. To be able to use a regular `mpi_recv` to receive the messages, one should use `mpi_bcast2`.
  • mpi_bcast2(+ _Root_, ? _Data_) @anchor mpi_bcast Broadcasts the message _Data_ from the process with rank _Root_ to all other processes.
  • mpi_bcast3(+ _Root_, + _Data_, + _Tag_) Broadcasts the message _Data_ with tag _Tag_ from the process with rank _Root_ to all other processes.
  • mpi_ibcast(+ _Root_, + _Data_, + _Tag_) @anchor mpi_ibcast Non-blocking operation. Broadcasts the message _Data_ with tag _Tag_ from the process with rank _Root_ to all other processes.
  • mpi_default_buffer_size(- _OldBufferSize_, ? _NewBufferSize_) @anchor mpi_default_buffer_size The _OldBufferSize_ argument unifies with the current size of the MPI communication buffer size and sets the communication buffer size _NewBufferSize_. The buffer is used for assynchronous waiting and for broadcast receivers. Notice that buffer is local at each MPI process.
  • mpi_msg_size( _Msg_, - _MsgSize_) @anchor mpi_msg_size Unify _MsgSize_ with the number of bytes YAP would need to send the message _Msg_.
  • mpi_gc @anchor mpi_gc Attempts to perform garbage collection with all the open handles associated with send and non-blocking broadcasts. For each handle it tests it and the message has been delivered the handle and the buffer are released.
@section BDDs Binary Decision Diagrams and Friends This library provides an interface to the BDD package CUDD. It requires CUDD compiled as a dynamic library. In Linux this is available out of box in Fedora, but can easily be ported to other Linux distributions. CUDD is available in the ports OSX package, and in cygwin. To use it, call `:-use_module(library(bdd))`. The following predicates construct a BDD:
  • bbd_new(? _Exp_, - _BddHandle_) @anchor bdd_new create a new BDD from the logical expression _Exp_. The expression may include:
    • Logical Variables: a leaf-node can be a logical variable.
    • Constants 0 and 1 a leaf-node can also be one of these two constants.
    • or( _X_, _Y_), _X_ \\/ _Y_, _X_ + _Y_ disjunction
    • and( _X_, _Y_), _X_ /\\ _Y_, _X_ \* _Y_ conjunction
    • nand( _X_, _Y_) negated conjunction@
    • nor( _X_, _Y_) negated disjunction
    • xor( _X_, _Y_) exclusive or
    • not( _X_), - _X_ negation
  • bdd_from_list(? _List_, - _BddHandle_) @anchor bdd_from_list Convert a _List_ of logical expressions of the form above into a BDD accessible through _BddHandle_.
  • mtbdd_new(? _Exp_, - _BddHandle_) @anchor mtbdd_new create a new algebraic decision diagram (ADD) from the logical expression _Exp_. The expression may include:
    • Logical Variables: a leaf-node can be a logical variable, or parameter.
    • Number a leaf-node can also be any number
    • _X_ \* _Y_ product
    • _X_ + _Y_ sum
    • _X_ - _Y_ subtraction
    • or( _X_, _Y_), _X_ \\/ _Y_ logical or
  • bdd_tree(+ _BDDHandle_, _Term_) @anchor bdd_tree Convert the BDD or ADD represented by _BDDHandle_ to a Prolog term of the form `bdd( _Dir_, _Nodes_, _Vars_)` or `mtbdd( _Nodes_, _Vars_)`, respectively. The arguments are:
    • _Dir_ direction of the BDD, usually 1
    • _Nodes_ list of nodes in the BDD or ADD. In a BDD nodes may be pp (both terminals are positive) or pn (right-hand-side is negative), and have four arguments: a logical variable that will be bound to the value of the node, the logical variable corresponding to the node, a logical variable, a 0 or a 1 with the value of the left-hand side, and a logical variable, a 0 or a 1 with the right-hand side.
    • _Vars_ are the free variables in the original BDD, or the parameters of the BDD/ADD.
    As an example, the BDD for the expression `X+(Y+X)\*(-Z)` becomes: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ bdd(1,[pn(N2,X,1,N1),pp(N1,Y,N0,1),pn(N0,Z,1,1)],vs(X,Y,Z)) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  • bdd_eval(+ _BDDHandle_, _Val_) @anchor bdd_eval Unify _Val_ with the value of the logical expression compiled in _BDDHandle_ given an assignment to its variables. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ bdd_new(X+(Y+X)*(-Z), BDD), [X,Y,Z] = [0,0,0], bdd_eval(BDD, V), writeln(V). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ would write 0 in the standard output stream. The Prolog code equivalent to bdd_eval/2 is: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Tree = bdd(1, T, _Vs), reverse(T, RT), foldl(eval_bdd, RT, _, V). eval_bdd(pp(P,X,L,R), _, P) :- P is ( X/\L ) \/ ( (1-X) /\ R ). eval_bdd(pn(P,X,L,R), _, P) :- P is ( X/\L ) \/ ( (1-X) /\ (1-R) ). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ First, the nodes are reversed to implement bottom-up evaluation. Then, we use the `foldl` list manipulation predicate to walk every node, computing the disjunction of the two cases and binding the output variable. The top node gives the full expression value. Notice that `(1- _X_)` implements negation.
  • bdd_size(+ _BDDHandle_, - _Size_) @anchor bdd_size Unify _Size_ with the number of nodes in _BDDHandle_.
  • bdd_print(+ _BDDHandle_, + _File_) @anchor bdd_print Output bdd _BDDHandle_ as a dot file to _File_.
  • bdd_to_probability_sum_product(+ _BDDHandle_, - _Prob_) @anchor bdd_to_probability_sum_product Each node in a BDD is given a probability _Pi_. The total probability of a corresponding sum-product network is _Prob_.
  • bdd_to_probability_sum_product(+ _BDDHandle_, - _Probs_, - _Prob_) Each node in a BDD is given a probability _Pi_. The total probability of a corresponding sum-product network is _Prob_, and the probabilities of the inner nodes are _Probs_. In Prolog, this predicate would correspond to computing the value of a BDD. The input variables will be bound to probabilities, eg `[ _X_, _Y_, _Z_] = [0.3.0.7,0.1]`, and the previous `eval_bdd` would operate over real numbers: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Tree = bdd(1, T, _Vs), reverse(T, RT), foldl(eval_prob, RT, _, V). eval_prob(pp(P,X,L,R), _, P) :- P is X * L + (1-X) * R. eval_prob(pn(P,X,L,R), _, P) :- P is X * L + (1-X) * (1-R). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  • bdd_close( _BDDHandle_) @anchor bdd_close close the BDD and release any resources it holds.
@section Block_Diagram Block Diagram This library provides a way of visualizing a prolog program using modules with blocks. To use it use: `:-use_module(library(block_diagram))`.
  • make_diagram(+inputfilename, +ouputfilename) @anchor make_diagram This will crawl the files following the use_module, ensure_loaded directives withing the inputfilename. The result will be a file in dot format. You can make a pdf at the shell by asking `dot -Tpdf filename \> output.pdf`.
  • make_diagram(+inputfilename, +ouputfilename, +predicate, +depth, +extension) The same as [make_diagram/2](@ref make_diagram) but you can define how many of the imported/exporeted predicates will be shown with predicate, and how deep the crawler is allowed to go with depth. The extension is used if the file use module directives do not include a file extension.
@page SWIhYProlog_Emulation SWI-Prolog Emulation This library provides a number of SWI-Prolog builtins that are not by default in YAP. This support is loaded with the `expects_dialect(swi)` command.
  • append(? _List1_,? _List2_,? _List3_) @anchor swi_append Succeeds when _List3_ unifies with the concatenation of _List1_ and _List2_. The predicate can be used with any instantiation pattern (even three variables).
  • between(+ _Low_,+ _High_,? _Value_) @anchor swi_between _Low_ and _High_ are integers, _High_ less or equal than _Low_. If _Value_ is an integer, _Low_ less or equal than _Value_ less or equal than _High_. When _Value_ is a variable it is successively bound to all integers between _Low_ and _High_. If _High_ is `inf`, [between/3](@ref between) is true iff _Value_ less or equal than _Low_, a feature that is particularly interesting for generating integers from a certain value.
  • chdir(+ _Dir_) @anchor chdir Compatibility predicate. New code should use [working_directory/2](@ref working_directory).
  • concat_atom(+ _List_,- _Atom_) @anchor concat_atom _List_ is a list of atoms, integers or floating point numbers. Succeeds if _Atom_ can be unified with the concatenated elements of _List_. If _List_ has exactly 2 elements it is equivalent to `atom_concat/3`, allowing for variables in the list.
  • concat_atom(? _List_,+ _Separator_,? _Atom_) Creates an atom just like concat_atom/2, but inserts _Separator_ between each pair of atoms. For example: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ?- concat_atom([gnu, gnat], ', ', A). A = 'gnu, gnat' ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ (Unimplemented) This predicate can also be used to split atoms by instantiating _Separator_ and _Atom_: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ?- concat_atom(L, -, 'gnu-gnat'). L = [gnu, gnat] ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  • nth1(+ _Index_,? _List_,? _Elem_) @anchor swi_nth1 Succeeds when the _Index_-th element of _List_ unifies with _Elem_. Counting starts at 1. Set environment variable. _Name_ and _Value_ should be instantiated to atoms or integers. The environment variable will be passed to `shell/[0-2]` and can be requested using `getenv/2`. They also influence [expand_file_name/2](@ref expand_file_name).
  • setenv(+ _Name_,+ _Value_) @anchor swi_setenv Set environment variable. _Name_ and _Value_ should be instantiated to atoms or integers. The environment variable will be passed to `shell/[0-2]` and can be requested using `getenv/2`. They also influence [expand_file_name/2](@ref expand_file_name).
  • term_to_atom(? _Term_,? _Atom_) @anchor swi_term_to_atom Succeeds if _Atom_ describes a term that unifies with _Term_. When _Atom_ is instantiated _Atom_ is converted and then unified with _Term_. If _Atom_ has no valid syntax, a `syntax_error` exception is raised. Otherwise _Term_ is ``written'' on _Atom_ using [write/1](@ref write).
  • working_directory(- _Old_,+ _New_) @anchor swi_working_directory Unify _Old_ with an absolute path to the current working directory and change working directory to _New_. Use the pattern `working_directory(CWD, CWD)` to get the current directory. See also `absolute_file_name/2` and [chdir/1](@ref chdir).
  • @ _Term1_ =@= @ _Term2_ @anchor qQaAaAqQ True iff _Term1_ and _Term2_ are structurally equivalent. I.e. if _Term1_ and _Term2_ are variants of each other.
@section Invoking_Predicates_on_all_Members_of_a_List Invoking Predicates on all Members of a List All the predicates in this section call a predicate on all members of a list or until the predicate called fails. The predicate is called via `call/[2..]`, which implies common arguments can be put in front of the arguments obtained from the list(s). For example: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ?- maplist(plus(1), [0, 1, 2], X). X = [1, 2, 3] ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ we will phrase this as `` _Predicate_ is applied on ...''
  • maplist(+ _Pred_,+ _List_) @anchor swi_maplist _Pred_ is applied successively on each element of _List_ until the end of the list or _Pred_ fails. In the latter case `maplist/2` fails.
  • maplist(+ _Pred_,+ _List1_,+ _List2_) Apply _Pred_ on all successive pairs of elements from _List1_ and _List2_. Fails if _Pred_ can not be applied to a pair. See the example above.
  • maplist(+ _Pred_,+ _List1_,+ _List2_,+ _List4_) Apply _Pred_ on all successive triples of elements from _List1_, _List2_ and _List3_. Fails if _Pred_ can not be applied to a triple. See the example above.
@section Forall Forall
  • forall(+ _Cond_,+ _Action_) @anchor swi_forall For all alternative bindings of _Cond_ _Action_ can be proven. The next example verifies that all arithmetic statements in the list _L_ are correct. It does not say which is wrong if one proves wrong. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ?- forall(member(Result = Formula, [2 = 1 + 1, 4 = 2 * 2]), Result =:= Formula). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
@page SWIhYProlog_Global_Variables SWI Global variables SWI-Prolog global variables are associations between names (atoms) and terms. They differ in various ways from storing information using [assert/1](@ref assert) or [recorda/3](@ref recorda).
  • The value lives on the Prolog (global) stack. This implies that lookup time is independent from the size of the term. This is particulary interesting for large data structures such as parsed XML documents or the CHR global constraint store.
  • They support both global assignment using [nb_setval/2](@ref nb_setval) and backtrackable assignment using [b_setval/2](@ref b_setval).
  • Only one value (which can be an arbitrary complex Prolog term) can be associated to a variable at a time.
  • Their value cannot be shared among threads. Each thread has its own namespace and values for global variables.
  • Currently global variables are scoped globally. We may consider module scoping in future versions.
Both [b_setval/2](@ref b_setval) and [nb_setval/2](@ref nb_setval) implicitly create a variable if the referenced name does not already refer to a variable. Global variables may be initialised from directives to make them available during the program lifetime, but some considerations are necessary for saved-states and threads. Saved-states to not store global variables, which implies they have to be declared with [initialization/1](@ref initialization) to recreate them after loading the saved state. Each thread has its own set of global variables, starting with an empty set. Using `thread_inititialization/1` to define a global variable it will be defined, restored after reloading a saved state and created in all threads that are created after the registration.
  • b_setval(+ _Name_,+ _Value_) @anchor swi_b_setval Associate the term _Value_ with the atom _Name_ or replaces the currently associated value with _Value_. If _Name_ does not refer to an existing global variable a variable with initial value `[]` is created (the empty list). On backtracking the assignment is reversed.
  • b_getval(+ _Name_,- _Value_) @anchor swi_b_getval Get the value associated with the global variable _Name_ and unify it with _Value_. Note that this unification may further instantiate the value of the global variable. If this is undesirable the normal precautions (double negation or [copy_term/2](@ref copy_term)) must be taken. The [b_getval/2](@ref b_getval) predicate generates errors if _Name_ is not an atom or the requested variable does not exist.
  • nb_setval(+ _Name_,+ _Value_) @anchor swi_nb_setval Associates a copy of _Value_ created with [duplicate_term/2](@ref duplicate_term) with the atom _Name_. Note that this can be used to set an initial value other than `[]` prior to backtrackable assignment.
  • nb_getval(+ _Name_,- _Value_) @anchor swi_nb_getval The [nb_getval/2](@ref nb_getval) predicate is a synonym for b_getval/2, introduced for compatibility and symmetry. As most scenarios will use a particular global variable either using non-backtrackable or backtrackable assignment, using [nb_getval/2](@ref nb_getval) can be used to document that the variable is used non-backtrackable.
  • nb_current(? _Name_,? _Value_) @anchor swi_nb_current Enumerate all defined variables with their value. The order of enumeration is undefined.
  • nb_delete(? _Name_) Delete the named global variable.
@section Compatibility_of_Global_Variables Compatibility of Global Variables Global variables have been introduced by various Prolog implementations recently. YAP follows their implementation in SWI-Prolog, itself based on hProlog by Bart Demoen. Jan and Bart decided that the semantics if hProlog [nb_setval/2](@ref nb_setval), which is equivalent to [nb_linkval/2](@ref nb_linkval) is not acceptable for normal Prolog users as the behaviour is influenced by how builtin predicates constructing terms ([read/1](@ref read), [=../2](@ref qQdOdO), etc.) are implemented. GNU-Prolog provides a rich set of global variables, including arrays. Arrays can be implemented easily in SWI-Prolog using [functor/3](@ref functor) and `setarg/3` due to the unrestricted arity of compound terms. @page Extensions Extensions to Prolog YAP includes a number of extensions over the original Prolog language. Next, we discuss support to the most important ones. @section Rational_Trees Rational Trees Prolog unification is not a complete implementation. For efficiency considerations, Prolog systems do not perform occur checks while unifying terms. As an example, `X = a(X)` will not fail but instead will create an infinite term of the form `a(a(a(a(a(...)))))`, or rational tree. Rational trees are now supported by default in YAP. In previous versions, this was not the default and these terms could easily lead to infinite computation. For example, `X = a(X), X = X` would enter an infinite loop. The `RATIONAL_TREES` flag improves support for these terms. Internal primitives are now aware that these terms can exist, and will not enter infinite loops. Hence, the previous unification will succeed. Another example, `X = a(X), ground(X)` will succeed instead of looping. Other affected built-ins include the term comparison primitives, [numbervars/3](@ref numbervars), [copy_term/2](@ref copy_term), and the internal data base routines. The support does not extend to Input/Output routines or to [assert/1](@ref assert) YAP does not allow directly reading rational trees, and you need to use `write_depth/2` to avoid entering an infinite cycle when trying to write an infinite term. @section CohYroutining Co-routining Prolog uses a simple left-to-right flow of control. It is sometimes convenient to change this control so that goals will only be executed when conditions are fulfilled. This may result in a more "data-driven" execution, or may be necessary to correctly implement extensions such as negation by default. The `COROUTINING` flag enables this option. Note that the support for coroutining will in general slow down execution. The following declaration is supported:
  • block/1 The argument to `block/1` is a condition on a goal or a conjunction of conditions, with each element separated by commas. Each condition is of the form `predname( _C1_,..., _CN_)`, where _N_ is the arity of the goal, and each _CI_ is of the form `-`, if the argument must suspend until the first such variable is bound, or `?`, otherwise.
  • wait/1 The argument to `wait/1` is a predicate descriptor or a conjunction of these predicates. These predicates will suspend until their first argument is bound.
The following primitives are supported:
  • dif( _X_, _Y_) @anchor dif Succeed if the two arguments do not unify. A call to [dif/2](@ref dif) will suspend if unification may still succeed or fail, and will fail if they always unify.
  • freeze(? _X_,: _G_) @anchor freeze Delay execution of goal _G_ until the variable _X_ is bound.
  • frozen( _X_, _G_) @anchor frozen Unify _G_ with a conjunction of goals suspended on variable _X_, or `true` if no goal has suspended.
  • when(+ _C_,: _G_) @anchor when Delay execution of goal _G_ until the conditions _C_ are satisfied. The conditions are of the following form:
    • _C1_, _C2_ Delay until both conditions _C1_ and _C2_ are satisfied.
    • _C1_; _C2_ Delay until either condition _C1_ or condition _C2_ is satisfied.
    • ?=( _V1_, _C2_) Delay until terms _V1_ and _V1_ have been unified.
    • nonvar( _V_) Delay until variable _V_ is bound.
    • ground( _V_) Delay until variable _V_ is ground.
    Note that [when/2](@ref when) will fail if the conditions fail.
  • call_residue(: _G_, _L_) @anchor call_residue Call goal _G_. If subgoals of _G_ are still blocked, return a list containing these goals and the variables they are blocked in. The goals are then considered as unblocked. The next example shows a case where [dif/2](@ref dif) suspends twice, once outside [call_residue/2](@ref call_residue), and the other inside: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ?- dif(X,Y), call_residue((dif(X,Y),(X = f(Z) ; Y = f(Z))), L). X = f(Z), L = [[Y]-dif(f(Z),Y)], dif(f(Z),Y) ? ; Y = f(Z), L = [[X]-dif(X,f(Z))], dif(X,f(Z)) ? ; no ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ The system only reports one invocation of [dif/2](@ref dif) as having suspended.
  • call_residue_vars(: _G_, _L_) @anchor call_residue_vars Call goal _G_ and unify _L_ with a list of all constrained variables created during execution of _G_: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ?- dif(X,Z), call_residue_vars(dif(X,Y),L). dif(X,Z), call_residue_vars(dif(X,Y),L). L = [Y], dif(X,Z), dif(X,Y) ? ; no ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
@section Attributed_Variables Attributed Variables YAP supports attributed variables, originally developed at OFAI by Christian Holzbaur. Attributes are a means of declaring that an arbitrary term is a property for a variable. These properties can be updated during forward execution. Moreover, the unification algorithm is aware of attributed variables and will call user defined handlers when trying to unify these variables. Attributed variables provide an elegant abstraction over which one can extend Prolog systems. Their main application so far has been in implementing constraint handlers, such as Holzbaur's CLPQR, Fruewirth and Holzbaur's CHR, and CLP(BN). Different Prolog systems implement attributed variables in different ways. Traditionally, YAP has used the interface designed by SICStus Prolog. This interface is still available in the atts library, but from YAP-6.0.3 we recommend using the hProlog, SWI style interface. The main reason to do so is that most packages included in YAP that use attributed variables, such as CHR, CLP(FD), and CLP(QR), rely on the SWI-Prolog interface. @section New_Style_Attribute_Declarations hProlog and SWI-Prolog style Attribute Declarations The following documentation is taken from the SWI-Prolog manual. Binding an attributed variable schedules a goal to be executed at the first possible opportunity. In the current implementation the hooks are executed immediately after a successful unification of the clause-head or successful completion of a foreign language (built-in) predicate. Each attribute is associated to a module and the hook [attr_unify_hook/2](@ref attr_unify_hook) is executed in this module. The example below realises a very simple and incomplete finite domain reasoner. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ :- module(domain, [ domain/2 % Var, ?Domain ]). :- use_module(library(ordsets)). domain(X, Dom) :- var(Dom), !, get_attr(X, domain, Dom). domain(X, List) :- list_to_ord_set(List, Domain), put_attr(Y, domain, Domain), X = Y. % An attributed variable with attribute value Domain has been % assigned the value Y attr_unify_hook(Domain, Y) :- ( get_attr(Y, domain, Dom2) -> ord_intersection(Domain, Dom2, NewDomain), ( NewDomain == [] -> fail ; NewDomain = [Value] -> Y = Value ; put_attr(Y, domain, NewDomain) ) ; var(Y) -> put_attr( Y, domain, Domain ) ; ord_memberchk(Y, Domain) ). % Translate attributes from this module to residual goals attribute_goals(X) --> { get_attr(X, domain, List) }, [domain(X, List)]. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Before explaining the code we give some example queries: The predicate `domain/2` fetches (first clause) or assigns (second clause) the variable a domain, a set of values it can be unified with. In the second clause first associates the domain with a fresh variable and then unifies X to this variable to deal with the possibility that X already has a domain. The predicate [attr_unify_hook/2](@ref attr_unify_hook) is a hook called after a variable with a domain is assigned a value. In the simple case where the variable is bound to a concrete value we simply check whether this value is in the domain. Otherwise we take the intersection of the domains and either fail if the intersection is empty (first example), simply assign the value if there is only one value in the intersection (second example) or assign the intersection as the new domain of the variable (third example). The nonterminal `attribute_goals/3` is used to translate remaining attributes to user-readable goals that, when executed, reinstate these attributes.
  • put_attr(+ _Var_,+ _Module_,+ _Value_) @anchor put_attr If _Var_ is a variable or attributed variable, set the value for the attribute named _Module_ to _Value_. If an attribute with this name is already associated with _Var_, the old value is replaced. Backtracking will restore the old value (i.e., an attribute is a mutable term. See also `setarg/3`). This predicate raises a representation error if _Var_ is not a variable and a type error if _Module_ is not an atom.
  • get_attr(+ _Var_,+ _Module_,- _Value_) @anchor get_attr Request the current _value_ for the attribute named _Module_. If _Var_ is not an attributed variable or the named attribute is not associated to _Var_ this predicate fails silently. If _Module_ is not an atom, a type error is raised.
  • del_attr(+ _Var_,+ _Module_) @anchor del_attr Delete the named attribute. If _Var_ loses its last attribute it is transformed back into a traditional Prolog variable. If _Module_ is not an atom, a type error is raised. In all other cases this predicate succeeds regardless whether or not the named attribute is present.
  • attr_unify_hook(+ _AttValue_,+ _VarValue_) @anchor attr_unify_hook Hook that must be defined in the module an attributed variable refers to. Is is called after the attributed variable has been unified with a non-var term, possibly another attributed variable. _AttValue_ is the attribute that was associated to the variable in this module and _VarValue_ is the new value of the variable. Normally this predicate fails to veto binding the variable to _VarValue_, forcing backtracking to undo the binding. If _VarValue_ is another attributed variable the hook often combines the two attribute and associates the combined attribute with _VarValue_ using [put_attr/3](@ref put_attr).
  • attr_portray_hook(+ _AttValue_,+ _Var_) @anchor attr_portray_hook Called by [write_term/2](@ref write_term) and friends for each attribute if the option `attributes(portray)` is in effect. If the hook succeeds the attribute is considered printed. Otherwise `Module = ...` is printed to indicate the existence of a variable.
  • attribute_goals(+ _Var_,- _Gs_,+ _GsRest_) @anchor attribute_goals This nonterminal, if it is defined in a module, is used by _copy_term/3_ to project attributes of that module to residual goals. It is also used by the toplevel to obtain residual goals after executing a query.
Normal user code should deal with [put_attr/3](@ref put_attr), [get_attr/3](@ref get_attr) and [del_attr/2](@ref del_attr). The routines in this section fetch or set the entire attribute list of a variables. Use of these predicates is anticipated to be restricted to printing and other special purpose operations.
  • get_attrs(+ _Var_,- _Attributes_) @anchor get_attrs Get all attributes of _Var_. _Attributes_ is a term of the form `att( _Module_, _Value_, _MoreAttributes_)`, where _MoreAttributes_ is `[]` for the last attribute.
  • put_attrs(+ _Var_,+ _Attributes_) @anchor put_attrs Set all attributes of _Var_. See [get_attrs/2](@ref get_attrs) for a description of _Attributes_.
  • del_attrs(+ _Var_) @anchor del_attrs If _Var_ is an attributed variable, delete all its attributes. In all other cases, this predicate succeeds without side-effects.
  • term_attvars(+ _Term_,- _AttVars_) @anchor term_attvars _AttVars_ is a list of all attributed variables in _Term_ and its attributes. I.e., [term_attvars/2](@ref term_attvars) works recursively through attributes. This predicate is Cycle-safe.
  • copy_term(? _TI_,- _TF_,- _Goals_) Term _TF_ is a variant of the original term _TI_, such that for each variable _V_ in the term _TI_ there is a new variable _V'_ in term _TF_ without any attributes attached. Attributed variables are thus converted to standard variables. _Goals_ is unified with a list that represents the attributes. The goal `maplist(call, _Goals_)` can be called to recreate the attributes. Before the actual copying, `copy_term/3` calls `attribute_goals/1` in the module where the attribute is defined.
  • copy_term_nat(? _TI_,- _TF_) @anchor copy_term_nat As [copy_term/2](@ref copy_term). Attributes however, are not copied but replaced by fresh variables.
@section Old_Style_Attribute_Declarations SICStus Prolog style Attribute Declarations Old style attribute declarations are activated through loading the library atts . The command ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ | ?- use_module(library(atts)). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ enables this form of use of attributed variables. The package provides the following functionality:
  • Each attribute must be declared first. Attributes are described by a functor and are declared per module. Each Prolog module declares its own sets of attributes. Different modules may have different functors with the same module.
  • The built-in [put_atts/2](@ref put_atts) adds or deletes attributes to a variable. The variable may be unbound or may be an attributed variable. In the latter case, YAP discards previous values for the attributes.
  • The built-in [get_atts/2](@ref get_atts) can be used to check the values of an attribute associated with a variable.
  • The unification algorithm calls the user-defined predicate verify_attributes/3 before trying to bind an attributed variable. Unification will resume after this call.
  • The user-defined predicate attribute_goal/2 converts from an attribute to a goal.
  • The user-defined predicate project_attributes/2 is used from a set of variables into a set of constraints or goals. One application of project_attributes/2 is in the top-level, where it is used to output the set of floundered constraints at the end of a query.
@subsection Attribute_Declarations Attribute Declarations Attributes are compound terms associated with a variable. Each attribute has a name which is private to the module in which the attribute was defined. Variables may have at most one attribute with a name. Attribute names are defined with the following declaration: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ :- attribute AttributeSpec, ..., AttributeSpec. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ where each _AttributeSpec_ has the form ( _Name_/ _Arity_). One single such declaration is allowed per module _Module_. Although the YAP module system is predicate based, attributes are local to modules. This is implemented by rewriting all calls to the built-ins that manipulate attributes so that attribute names are preprocessed depending on the module. The `user:goal_expansion/3` mechanism is used for this purpose. @subsection Attribute_Manipulation Attribute Manipulation The attribute manipulation predicates always work as follows:
  1. The first argument is the unbound variable associated with attributes,
  2. The second argument is a list of attributes. Each attribute will be a Prolog term or a constant, prefixed with the + and - unary operators. The prefix + may be dropped for convenience.
The following three procedures are available to the user. Notice that these built-ins are rewritten by the system into internal built-ins, and that the rewriting process depends on the module on which the built-ins have been invoked.
  • _Module_:get_atts( _-Var_, _?ListOfAttributes_) @anchor get_atts Unify the list _?ListOfAttributes_ with the attributes for the unbound variable _Var_. Each member of the list must be a bound term of the form `+( _Attribute_)`, `-( _Attribute_)` (the kbd prefix may be dropped). The meaning of + and - is:
  • +( _Attribute_) Unifies _Attribute_ with a corresponding attribute associated with _Var_, fails otherwise.
  • -( _Attribute_) Succeeds if a corresponding attribute is not associated with _Var_. The arguments of _Attribute_ are ignored.
  • _Module_:put_atts( _-Var_, _?ListOfAttributes_) @anchor put_atts Associate with or remove attributes from a variable _Var_. The attributes are given in _?ListOfAttributes_, and the action depends on how they are prefixed:
  • +( _Attribute_) Associate _Var_ with _Attribute_. A previous value for the attribute is simply replace (like with `set_mutable/2`).
  • -( _Attribute_) Remove the attribute with the same name. If no such attribute existed, simply succeed.
@subsection Attributed_Unification Attributed Unification The user-predicate predicate [verify_attributes/3](@ref verify_attributes) is called when attempting to unify an attributed variable which might have attributes in some _Module_.
  • _Module_:verify_attributes( _-Var_, _+Value_, _-Goals_) @anchor verify_attributes The predicate is called when trying to unify the attributed variable _Var_ with the Prolog term _Value_. Note that _Value_ may be itself an attributed variable, or may contain attributed variables. The goal verify_attributes/3 is actually called before _Var_ is unified with _Value_. It is up to the user to define which actions may be performed by verify_attributes/3 but the procedure is expected to return in _Goals_ a list of goals to be called after _Var_ is unified with _Value_. If verify_attributes/3 fails, the unification will fail. Notice that the verify_attributes/3 may be called even if _Var_\< has no attributes in module Module. In this case the routine should simply succeed with _Goals_ unified with the empty list.
  • attvar( _-Var_) @anchor attvar Succeed if _Var_ is an attributed variable.
@subsection Displaying_Attributes Displaying Attributes Attributes are usually presented as goals. The following routines are used by built-in predicates such as [call_residue/2](@ref call_residue) and by the Prolog top-level to display attributes:
  • _Module_:attribute_goal( _-Var_, _-Goal_) @anchor attribute_goal User-defined procedure, called to convert the attributes in _Var_ to a _Goal_. Should fail when no interpretation is available.
@subsection Projecting_Attributes Projecting Attributes Constraint solvers must be able to project a set of constraints to a set of variables. This is useful when displaying the solution to a goal, but may also be used to manipulate computations. The user-defined [project_attributes/2](@ref project_attributes) is responsible for implementing this projection.
  • _Module_:project_attributes( _+QueryVars_, _+AttrVars_) @anchor project_attributes Given a list of variables _QueryVars_ and list of attributed variables _AttrVars_, project all attributes in _AttrVars_ to _QueryVars_. Although projection is constraint system dependent, typically this will involve expressing all constraints in terms of _QueryVars_ and considering all remaining variables as existentially quantified.
Projection interacts with [attribute_goal/2](@ref attribute_goal) at the Prolog top level. When the query succeeds, the system first calls [project_attributes/2](@ref project_attributes). The system then calls [attribute_goal/2](@ref attribute_goal) to get a user-level representation of the constraints. Typically, [attribute_goal/2](@ref attribute_goal) will convert from the original constraints into a set of new constraints on the projection, and these constraints are the ones that will have an [attribute_goal/2](@ref attribute_goal) handler. @subsection Attribute_Examples Attribute Examples The following two examples example is taken from the SICStus Prolog manual. It sketches the implementation of a simple finite domain ``solver''. Note that an industrial strength solver would have to provide a wider range of functionality and that it quite likely would utilize a more efficient representation for the domains proper. The module exports a single predicate `domain( _-Var_, _?Domain_)` which associates _Domain_ (a list of terms) with _Var_. A variable can be queried for its domain by leaving _Domain_ unbound. We do not present here a definition for [project_attributes/2](@ref project_attributes). Projecting finite domain constraints happens to be difficult. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ :- module(domain, [domain/2]). :- use_module(library(atts)). :- use_module(library(ordsets), [ ord_intersection/3, ord_intersect/2, list_to_ord_set/2 ]). :- attribute dom/1. verify_attributes(Var, Other, Goals) :- get_atts(Var, dom(Da)), !, % are we involved? ( var(Other) -> % must be attributed then ( get_atts(Other, dom(Db)) -> % has a domain? ord_intersection(Da, Db, Dc), Dc = [El|Els], % at least one element ( Els = [] -> % exactly one element Goals = [Other=El] % implied binding ; Goals = [], put_atts(Other, dom(Dc))% rescue intersection ) ; Goals = [], put_atts(Other, dom(Da)) % rescue the domain ) ; Goals = [], ord_intersect([Other], Da) % value in domain? ). verify_attributes(_, _, []). % unification triggered % because of attributes % in other modules attribute_goal(Var, domain(Var,Dom)) :- % interpretation as goal get_atts(Var, dom(Dom)). domain(X, Dom) :- var(Dom), !, get_atts(X, dom(Dom)). domain(X, List) :- list_to_ord_set(List, Set), Set = [El|Els], % at least one element ( Els = [] -> % exactly one element X = El % implied binding ; put_atts(Fresh, dom(Set)), X = Fresh % may call % verify_attributes/3 ). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Note that the ``implied binding'' `Other=El` was deferred until after the completion of `verify_attribute/3`. Otherwise, there might be a danger of recursively invoking `verify_attribute/3`, which might bind `Var`, which is not allowed inside the scope of `verify_attribute/3`. Deferring unifications into the third argument of `verify_attribute/3` effectively serializes the calls to `verify_attribute/3`. Assuming that the code resides in the file domain.yap, we can use it via: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ | ?- use_module(domain). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Let's test it: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ | ?- domain(X,[5,6,7,1]), domain(Y,[3,4,5,6]), domain(Z,[1,6,7,8]). domain(X,[1,5,6,7]), domain(Y,[3,4,5,6]), domain(Z,[1,6,7,8]) ? yes | ?- domain(X,[5,6,7,1]), domain(Y,[3,4,5,6]), domain(Z,[1,6,7,8]), X=Y. Y = X, domain(X,[5,6]), domain(Z,[1,6,7,8]) ? yes | ?- domain(X,[5,6,7,1]), domain(Y,[3,4,5,6]), domain(Z,[1,6,7,8]), X=Y, Y=Z. X = 6, Y = 6, Z = 6 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ To demonstrate the use of the _Goals_ argument of [verify_attributes/3](@ref verify_attributes), we give an implementation of [freeze/2](@ref freeze). We have to name it `myfreeze/2` in order to avoid a name clash with the built-in predicate of the same name. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ :- module(myfreeze, [myfreeze/2]). :- use_module(library(atts)). :- attribute frozen/1. verify_attributes(Var, Other, Goals) :- get_atts(Var, frozen(Fa)), !, % are we involved? ( var(Other) -> % must be attributed then ( get_atts(Other, frozen(Fb)) % has a pending goal? -> put_atts(Other, frozen((Fa,Fb))) % rescue conjunction ; put_atts(Other, frozen(Fa)) % rescue the pending goal ), Goals = [] ; Goals = [Fa] ). verify_attributes(_, _, []). attribute_goal(Var, Goal) :- % interpretation as goal get_atts(Var, frozen(Goal)). myfreeze(X, Goal) :- put_atts(Fresh, frozen(Goal)), Fresh = X. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Assuming that this code lives in file myfreeze.yap, we would use it via: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ | ?- use_module(myfreeze). | ?- myfreeze(X,print(bound(x,X))), X=2. bound(x,2) % side effect X = 2 % bindings ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ The two solvers even work together: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ | ?- myfreeze(X,print(bound(x,X))), domain(X,[1,2,3]), domain(Y,[2,10]), X=Y. bound(x,2) % side effect X = 2, % bindings Y = 2 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ The two example solvers interact via bindings to shared attributed variables only. More complicated interactions are likely to be found in more sophisticated solvers. The corresponding [verify_attributes/3](@ref verify_attributes) predicates would typically refer to the attributes from other known solvers/modules via the module prefix in ` _Module_:get_atts/2`. @page Constraint_Logic_Programming_over_Reals Constraint Logic Programming over Reals YAP now uses the CLP(R) package developed by Leslie De Koninck, K.U. Leuven as part of a thesis with supervisor Bart Demoen and daily advisor Tom Schrijvers, and distributed with SWI-Prolog. This CLP(R) system is a port of the CLP(Q,R) system of Sicstus Prolog and YAP by Christian Holzbaur: Holzbaur C.: OFAI clp(q,r) Manual, Edition 1.3.3, Austrian Research Institute for Artificial Intelligence, Vienna, TR-95-09, 1995, This port only contains the part concerning real arithmetics. This manual is roughly based on the manual of the above mentioned *CLP(QR)* implementation. Please note that the clpr library is not an `autoload` library and therefore this library must be loaded explicitely before using it: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ :- use_module(library(clpr)). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ @section CLPR_Solver_Predicates Solver Predicates The following predicates are provided to work with constraints:
  • {+ _Constraints_} Adds the constraints given by _Constraints_ to the constraint store.
  • entailed(+ _Constraint_) Succeeds if _Constraint_ is necessarily true within the current constraint store. This means that adding the negation of the constraint to the store results in failure.
  • inf(+ _Expression_,- _Inf_) Computes the infimum of _Expression_ within the current state of the constraint store and returns that infimum in _Inf_. This predicate does not change the constraint store.
  • inf(+ _Expression_,- _Sup_) Computes the supremum of _Expression_ within the current state of the constraint store and returns that supremum in _Sup_. This predicate does not change the constraint store.
  • min(+ _Expression_) Minimizes _Expression_ within the current constraint store. This is the same as computing the infimum and equation the expression to that infimum.
  • max(+ _Expression_) Maximizes _Expression_ within the current constraint store. This is the same as computing the supremum and equating the expression to that supremum.
  • bb_inf(+ _Ints_,+ _Expression_,- _Inf_,- _Vertext_,+ _Eps_) Computes the infimum of _Expression_ within the current constraint store, with the additional constraint that in that infimum, all variables in _Ints_ have integral values. _Vertex_ will contain the values of _Ints_ in the infimum. _Eps_ denotes how much a value may differ from an integer to be considered an integer. E.g. when _Eps_ = 0.001, then X = 4.999 will be considered as an integer (5 in this case). _Eps_ should be between 0 and 0.5.
  • bb_inf(+ _Ints_,+ _Expression_,- _Inf_) The same as bb_inf/5 but without returning the values of the integers and with an eps of 0.001.
  • dump(+ _Target_,+ _Newvars_,- _CodedAnswer_) Returns the constraints on _Target_ in the list _CodedAnswer_ where all variables of _Target_ have veen replaced by _NewVars_. This operation does not change the constraint store. E.g. in ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ dump([X,Y,Z],[x,y,z],Cons) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ _Cons_ will contain the constraints on _X_, _Y_ and _Z_ where these variables have been replaced by atoms `x`, `y` and `z`.
@section CLPR_Syntax Syntax of the predicate arguments The arguments of the predicates defined in the subsection above are defined in the following table. Failing to meet the syntax rules will result in an exception. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ---> \\ single constraint \\ | , \\ conjunction \\ | ; \\ disjunction \\ ---> {<} \\ less than \\ | {>} \\ greater than \\ | {=<} \\ less or equal \\ | {<=}(, ) \\ less or equal \\ | {>=} \\ greater or equal \\ | {=\=} \\ not equal \\ | =:= \\ equal \\ | = \\ equal \\ ---> \\ Prolog variable \\ | \\ Prolog number (float, integer) \\ | + \\ unary plus \\ | - \\ unary minus \\ | + \\ addition \\ | - \\ substraction \\ | * \\ multiplication \\ | / \\ division \\ | abs() \\ absolute value \\ | sin() \\ sine \\ | cos() \\ cosine \\ | tan() \\ tangent \\ | exp() \\ exponent \\ | pow() \\ exponent \\ | {^} \\ exponent \\ | min(, ) \\ minimum \\ | max(, ) \\ maximum \\ ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ @section CLPR_Unification Use of unification Instead of using the `{}/1` predicate, you can also use the standard unification mechanism to store constraints. The following code samples are equivalent:
  • Unification with a variable ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ {X =:= Y} {X = Y} X = Y ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  • Unification with a number ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ {X =:= 5.0} {X = 5.0} X = 5.0 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
@section CLPR_NonhYlinear_Constraints Non-Linear Constraints In this version, non-linear constraints do not get solved until certain conditions are satisfied. We call these conditions the isolation axioms. They are given in the following table. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ A = B * C when B or C is ground or // A = 5 * C or A = B * 4 \\ A and (B or C) are ground // 20 = 5 * C or 20 = B * 4 \\ A = B / C when C is ground or // A = B / 3 A and B are ground // 4 = 12 / C X = min(Y,Z) when Y and Z are ground or // X = min(4,3) X = max(Y,Z) Y and Z are ground // X = max(4,3) X = abs(Y) Y is ground // X = abs(-7) X = pow(Y,Z) when X and Y are ground or // 8 = 2 ^ Z X = exp(Y,Z) X and Z are ground // 8 = Y ^ 3 X = Y ^ Z Y and Z are ground // X = 2 ^ 3 X = sin(Y) when X is ground or // 1 = sin(Y) X = cos(Y) Y is ground // X = sin(1.5707) X = tan(Y) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ @page CHRcC_Constraint_Handling_Rules_ CHR: Constraint Handling Rules This chapter is written by Tom Schrijvers, K.U. Leuven for the hProlog system. Adjusted by Jan Wielemaker to fit the SWI-Prolog documentation infrastructure and remove hProlog specific references. The CHR system of SWI-Prolog is the K.U.Leuven CHR system. The runtime environment is written by Christian Holzbaur and Tom Schrijvers while the compiler is written by Tom Schrijvers. Both are integrated with SWI-Prolog and licenced under compatible conditions with permission from the authors. The main reference for SWI-Prolog's CHR system is:
  • T. Schrijvers, and B. Demoen, The K.U.Leuven CHR System: Implementation and Application, First Workshop on Constraint Handling Rules: Selected Contributions (Fruwirth, T. and Meister, M., eds.), pp. 1--5, 2004.
@section CHR_Introduction Introduction Constraint Handling Rules (CHR) is a committed-choice bottom-up language embedded in Prolog. It is designed for writing constraint solvers and is particularily useful for providing application-specific constraints. It has been used in many kinds of applications, like scheduling, model checking, abduction, type checking among many others. CHR has previously been implemented in other Prolog systems (SICStus, Eclipse, Yap), Haskell and Java. This CHR system is based on the compilation scheme and runtime environment of CHR in SICStus. In this documentation we restrict ourselves to giving a short overview of CHR in general and mainly focus on elements specific to this implementation. For a more thorough review of CHR we refer the reader to [Freuhwirth:98]. More background on CHR can be found at the CHR web site. @section CHR_Syntax_and_Semantics Syntax and Semantics @subsection CHR_Syntax CHR Syntax The syntax of CHR rules in hProlog is the following: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ rules --> rule, rules. rules --> []. rule --> name, actual_rule, pragma, [atom('.')]. name --> atom, [atom('@')]. name --> []. actual_rule --> simplification_rule. actual_rule --> propagation_rule. actual_rule --> simpagation_rule. simplification_rule --> constraints, [atom('<=>')], guard, body. propagation_rule --> constraints, [atom('==>')], guard, body. simpagation_rule --> constraints, [atom('\')], constraints, [atom('<=>')], guard, body. constraints --> constraint, constraint_id. constraints --> constraint, [atom(',')], constraints. constraint --> compound_term. constraint_id --> []. constraint_id --> [atom('#')], variable. guard --> []. guard --> goal, [atom('|')]. body --> goal. pragma --> []. pragma --> [atom('pragma')], actual_pragmas. actual_pragmas --> actual_pragma. actual_pragmas --> actual_pragma, [atom(',')], actual_pragmas. actual_pragma --> [atom('passive(')], variable, [atom(')')]. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Additional syntax-related terminology:
  • *head:* the constraints in an `actual_rule` before the arrow (either `\<=\>` or `==\>`)
@subsection Semantics Semantics In this subsection the operational semantics of CHR in Prolog are presented informally. They do not differ essentially from other CHR systems. When a constraint is called, it is considered an active constraint and the system will try to apply the rules to it. Rules are tried and executed sequentially in the order they are written. A rule is conceptually tried for an active constraint in the following way. The active constraint is matched with a constraint in the head of the rule. If more constraints appear in the head they are looked for among the suspended constraints, which are called passive constraints in this context. If the necessary passive constraints can be found and all match with the head of the rule and the guard of the rule succeeds, then the rule is committed and the body of the rule executed. If not all the necessary passive constraint can be found, the matching fails or the guard fails, then the body is not executed and the process of trying and executing simply continues with the following rules. If for a rule, there are multiple constraints in the head, the active constraint will try the rule sequentially multiple times, each time trying to match with another constraint. This process ends either when the active constraint disappears, i.e. it is removed by some rule, or after the last rule has been processed. In the latter case the active constraint becomes suspended. A suspended constraint is eligible as a passive constraint for an active constraint. The other way it may interact again with the rules, is when a variable appearing in the constraint becomes bound to either a nonvariable or another variable involved in one or more constraints. In that case the constraint is triggered, i.e. it becomes an active constraint and all the rules are tried. @subsubsection Rule_Types There are three different kinds of rules, each with their specific semantics:
  • simplification The simplification rule removes the constraints in its head and calls its body.
  • propagation The propagation rule calls its body exactly once for the constraints in its head.
  • simpagation The simpagation rule removes the constraints in its head after the `\\` and then calls its body. It is an optimization of simplification rules of the form: \\[constraints_1, constraints_2 \<=\> constraints_1, body \\] Namely, in the simpagation form: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ constraints1 \ constraints2 <=> body ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ _constraints1_ constraints are not called in the body.
@subsubsection Rule_Names Naming a rule is optional and has no semantical meaning. It only functions as documentation for the programmer. @subsubsection Pragmas The semantics of the pragmas are:
  • passive(Identifier) The constraint in the head of a rule _Identifier_ can only act as a passive constraint in that rule.
Additional pragmas may be released in the future. @subsubsection Options It is possible to specify options that apply to all the CHR rules in the module. Options are specified with the `option/2` declaration: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ option(Option,Value). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Available options are:
  • check_guard_bindings This option controls whether guards should be checked for illegal variable bindings or not. Possible values for this option are `on`, to enable the checks, and `off`, to disable the checks.
  • optimize This is an experimental option controlling the degree of optimization. Possible values are `full`, to enable all available optimizations, and `off` (default), to disable all optimizations. The default is derived from the SWI-Prolog flag `optimise`, where `true` is mapped to `full`. Therefore the commandline option `-O` provides full CHR optimization. If optimization is enabled, debugging should be disabled.
  • debug This options enables or disables the possibility to debug the CHR code. Possible values are `on` (default) and `off`. See `debugging` for more details on debugging. The default is derived from the prolog flag `generate_debug_info`, which is `true` by default. See `-nodebug`. If debugging is enabled, optimization should be disabled.
  • mode This option specifies the mode for a particular constraint. The value is a term with functor and arity equal to that of a constraint. The arguments can be one of `-`, `+` or `?`. The latter is the default. The meaning is the following:
    • - The corresponding argument of every occurrence of the constraint is always unbound.
    • + The corresponding argument of every occurrence of the constraint is always ground.
    • ? The corresponding argument of every occurrence of the constraint can have any instantiation, which may change over time. This is the default value.
    The declaration is used by the compiler for various optimizations. Note that it is up to the user the ensure that the mode declaration is correct with respect to the use of the constraint. This option may occur once for each constraint.
  • type_declaration This option specifies the argument types for a particular constraint. The value is a term with functor and arity equal to that of a constraint. The arguments can be a user-defined type or one of the built-in types:
    • int The corresponding argument of every occurrence of the constraint is an integer number.
    • float ...{} a floating point number.
    • number ...{} a number.
    • natural ...{} a positive integer.
    • any The corresponding argument of every occurrence of the constraint can have any type. This is the default value.
    Currently, type declarations are only used to improve certain optimizations (guard simplification, occurrence subsumption, ...{}).
  • type_definition This option defines a new user-defined type which can be used in type declarations. The value is a term of the form `type(` _name_`,` _list_`)`, where _name_ is a term and _list_ is a list of alternatives. Variables can be used to define generic types. Recursive definitions are allowed. Examples are ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ type(bool,[true,false]). type(complex_number,[float + float * i]). type(binary_tree(T),[ leaf(T) | node(binary_tree(T),binary_tree(T)) ]). type(list(T),[ [] | [T | list(T)]). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
The mode, type_declaration and type_definition options are provided for backward compatibility. The new syntax is described below. @section CHR_in_YAP_Programs CHR in YAP Programs @subsection Embedding_in_Prolog_Programs Embedding in Prolog Programs The CHR constraints defined in a particulary chr file are associated with a module. The default module is `user`. One should never load different chr files with the same CHR module name. @subsection Constraint_declaration Constraint declaration Every constraint used in CHR rules has to be declared. There are two ways to do this. The old style is as follows: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ option(type_definition,type(list(T),[ [] , [T|list(T)] ]). option(mode,foo(+,?)). option(type_declaration,foo(list(int),float)). :- constraints foo/2, bar/0. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ The new style is as follows: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ :- chr_type list(T) ---> [] ; [T|list(T)]. :- constraints foo(+list(int),?float), bar. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ @subsection Compilation Compilation The SWI-Prolog CHR compiler exploits term_expansion/2 rules to translate the constraint handling rules to plain Prolog. These rules are loaded from the library chr. They are activated if the compiled file has the chr extension or after finding a declaration of the format below. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ :- constraints ... ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ It is adviced to define CHR rules in a module file, where the module declaration is immediately followed by including the chr library as examplified below: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ :- module(zebra, [ zebra/0 ]). :- use_module(library(chr)). :- constraints ... ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Using this style CHR rules can be defined in ordinary Prolog pl files and the operator definitions required by CHR do not leak into modules where they might cause conflicts. @section CHR_Debugging Debugging The CHR debugging facilities are currently rather limited. Only tracing is currently available. To use the CHR debugging facilities for a CHR file it must be compiled for debugging. Generating debug info is controlled by the CHR option [debug](@ref debug), whose default is derived from the SWI-Prolog flag `generate_debug_info`. Therefore debug info is provided unless the `-nodebug` is used. @subsection Ports Ports For CHR constraints the four standard ports are defined:
  • call A new constraint is called and becomes active.
  • exit An active constraint exits: it has either been inserted in the store after trying all rules or has been removed from the constraint store.
  • fail An active constraint fails.
  • redo An active constraint starts looking for an alternative solution.
In addition to the above ports, CHR constraints have five additional ports:
  • wake A suspended constraint is woken and becomes active.
  • insert An active constraint has tried all rules and is suspended in the constraint store.
  • remove An active or passive constraint is removed from the constraint store, if it had been inserted.
  • try An active constraints tries a rule with possibly some passive constraints. The try port is entered just before committing to the rule.
  • apply An active constraints commits to a rule with possibly some passive constraints. The apply port is entered just after committing to the rule.
@subsection Tracing Tracing Tracing is enabled with the chr_trace/0 predicate and disabled with the chr_notrace/0 predicate. When enabled the tracer will step through the `call`, `exit`, `fail`, `wake` and `apply` ports, accepting debug commands, and simply write out the other ports. The following debug commans are currently supported: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ CHR debug options: creep c creep s skip g ancestors n nodebug b break a abort f fail ? help h help ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Their meaning is:
  • creep Step to the next port.
  • skip Skip to exit port of this call or wake port.
  • ancestors Print list of ancestor call and wake ports.
  • nodebug Disable the tracer.
  • break Enter a recursive Prolog toplevel. See break/0.
  • abort Exit to the toplevel. See abort/0.
  • fail Insert failure in execution.
  • help Print the above available debug options.
@subsection CHR_Debugging_Predicates CHR Debugging Predicates The chr module contains several predicates that allow inspecting and printing the content of the constraint store.
  • chr_trace/0 Activate the CHR tracer. By default the CHR tracer is activated and deactivated automatically by the Prolog predicates trace/0 and notrace/0.
  • chr_notrace/0 De-activate the CHR tracer. By default the CHR tracer is activated and deactivated automatically by the Prolog predicates trace/0 and notrace/0.
  • chr_leash/0 Define the set of CHR ports on which the CHR tracer asks for user intervention (i.e. stops). _Spec_ is either a list of ports or a predefined `alias'. Defined aliases are: `full` to stop at all ports, `none` or `off` to never stop, and `default` to stop at the `call`, `exit`, `fail`, `wake` and `apply` ports. See also leash/1.
  • chr_show_store(+ _Mod_) Prints all suspended constraints of module _Mod_ to the standard output. This predicate is automatically called by the SWI-Prolog toplevel at the end of each query for every CHR module currently loaded. The prolog-flag `chr_toplevel_show_store` controls whether the toplevel shows the constraint stores. The value `true` enables it. Any other value disables it.
@section CHR_Examples Examples Here are two example constraint solvers written in CHR.
  • The program below defines a solver with one constraint, `leq/2`, which is a less-than-or-equal constraint. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ :- module(leq,[cycle/3, leq/2]). :- use_module(library(chr)). :- constraints leq/2. reflexivity @ leq(X,X) <=> true. antisymmetry @ leq(X,Y), leq(Y,X) <=> X = Y. idempotence @ leq(X,Y) \ leq(X,Y) <=> true. transitivity @ leq(X,Y), leq(Y,Z) ==> leq(X,Z). cycle(X,Y,Z):- leq(X,Y), leq(Y,Z), leq(Z,X). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  • The program below implements a simple finite domain constraint solver. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ :- module(dom,[dom/2]). :- use_module(library(chr)). :- constraints dom/2. dom(X,[]) <=> fail. dom(X,[Y]) <=> X = Y. dom(X,L1), dom(X,L2) <=> intersection(L1,L2,L3), dom(X,L3). intersection([],_,[]). intersection([H|T],L2,[H|L3]) :- member(H,L2), !, intersection(T,L2,L3). intersection([_|T],L2,L3) :- intersection(T,L2,L3). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
@section CHR_Compatibility Compatibility with SICStus CHR There are small differences between CHR in SWI-Prolog and newer YAPs and SICStus and older versions of YAP. Besides differences in available options and pragmas, the following differences should be noted:
  • [The handler/1 declaration] In SICStus every CHR module requires a `handler/1` declaration declaring a unique handler name. This declaration is valid syntax in SWI-Prolog, but will have no effect. A warning will be given during compilation.
  • [The rules/1 declaration] In SICStus, for every CHR module it is possible to only enable a subset of the available rules through the `rules/1` declaration. The declaration is valid syntax in SWI-Prolog, but has no effect. A warning is given during compilation.
  • [Sourcefile naming] SICStus uses a two-step compiler, where chr files are first translated into pl files. For SWI-Prolog CHR rules may be defined in a file with any extension.
@section CHR_Guidelines Guidelines In this section we cover several guidelines on how to use CHR to write constraint solvers and how to do so efficiently.
  • [Set semantics] The CHR system allows the presence of identical constraints, i.e. multiple constraints with the same functor, arity and arguments. For most constraint solvers, this is not desirable: it affects efficiency and possibly termination. Hence appropriate simpagation rules should be added of the form: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ {constraint \ constraint <=> true}. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  • [Multi-headed rules] Multi-headed rules are executed more efficiently when the constraints share one or more variables.
  • [Mode and type declarations] Provide mode and type declarations to get more efficient program execution. Make sure to disable debug (`-nodebug`) and enable optimization (`-O`).
@section Logtalk Logtalk The Logtalk object-oriented extension is available after running its standalone installer by using the `yaplgt` command in POSIX systems or by using the `Logtalk - YAP` shortcut in the Logtalk program group in the Start Menu on Windows systems. For more information please see the URL . @section MYDDAS MYDDAS The MYDDAS database project was developed within a FCT project aiming at the development of a highly efficient deductive database system, based on the coupling of the MySQL relational database system with the Yap Prolog system. MYDDAS was later expanded to support the ODBC interface. @section Requirements_and_Installation_Guide Requirements and Installation Guide Next, we describe how to usen of the YAP with the MYDDAS System. The use of this system is entirely depend of the MySQL development libraries or the ODBC development libraries. At least one of the this development libraries must be installed on the computer system, otherwise MYDDAS will not compile. The MySQL development libraries from MySQL 3.23 an above are know to work. We recommend the usage of MySQL versusODBC, but it is possible to have both options installed At the same time, without any problem. The MYDDAS system automatically controls the two options. Currently, MYDDAS is know to compile without problems in Linux. The usage of this system on Windows has not been tested yet. MYDDAS must be enabled at configure time. This can be done with the following options:
  • --enable-myddas This option will detect which development libraries are installed on the computer system, MySQL, ODBC or both, and will compile the Yap system with the support for which libraries it detects;
  • --enable-myddas-stats This option is only available in MySQL. It includes code to get statistics from the MYDDAS system;
  • --enable-top-level This option is only available in MySQL. It enables the option to interact with the MySQL server in two different ways. As if we were on the MySQL Client Shell, and as if we were using Datalog.
@section MYDDAS_Architecture MYDDAS Architecture The system includes four main blocks that are put together through the MYDDAS interface: the Yap Prolog compiler, the MySQL database system, an ODBC layer and a Prolog to SQL compiler. Current effort is put on the MySQL interface rather than on the ODBC interface. If you want to use the full power of the MYDDAS interface we recommend you to use a MySQL database. Other databases, such as Oracle, PostGres or Microsoft SQL Server, can be interfaced through the ODBC layer, but with limited performance and features support. The main structure of the MYDDAS interface is simple. Prolog queries involving database goals are translated to SQL using the Prolog to SQL compiler; then the SQL expression is sent to the database system, which returns the set of tuples satisfying the query; and finally those tuples are made available to the Prolog engine as terms. For recursive queries involving database goals, the YapTab tabling engine provides the necessary support for an efficient evaluation of such queries. An important aspect of the MYDDAS interface is that for the programmer the use of predicates which are defined in database relations is completely transparent. An example of this transparent support is the Prolog cut operator, which has exactly the same behaviour from predicates defined in the Prolog program source code, or from predicates defined in database as relations. @section Loading_MYDDAS Loading MYDDAS Begin by starting YAP and loading the library `use_module(library(myddas))`. This library already includes the Prolog to SQL Compiler described in [2] and [1]. In MYDDAS this compiler has been extended to support further constructs which allow a more efficient SQL translation. @section Connecting_to_and_disconnecting_from_a_Database_Server Connecting to and disconnecting from a Database Server
  • db open(+,+,+,+,+). @anchor db_open
  • db open(+,+,+,+).
  • db close(+). @anchor db_close
Assuming the MySQL server is running and we have an account, we can login to MySQL by invoking [db_open/5](@ref db_open) as one of the following: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ?- db_open(mysql,Connection,Host/Database,User,Password). ?- db_open(mysql,Connection,Host/Database/Port,User,Password). ?- db_open(mysql,Connection,Host/Database/UnixSocket,User,Password). ?- db_open(mysql,Connection,Host/Database/Port/UnixSocket,User,Password). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ If the login is successful, there will be a response of `yes`. For instance: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ?- db_open(mysql,con1,localhost/guest_db,guest,''). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ uses the MySQL native interface, selected by the first argument, to open a connection identified by the `con1` atom, to an instance of a MySQL server running on host `localhost`, using database guest `db` and user `guest` with empty `password`. To disconnect from the `con1` connection we use: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ?- db_close(con1). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Alternatively, we can use `db_open/4` and `db_close/0,` without an argument to identify the connection. In this case the default connection is used, with atom `myddas`. Thus using ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ?- db_open(mysql,localhost/guest_db,guest,''). ?- db_close. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ or ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ?- db_open(mysql,myddas,localhost/guest_db,guest,''). ?- db_close(myddas). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ is exactly the same. MYDDAS also supports ODBC. To connect to a database using an ODBC driver you must have configured on your system a ODBC DSN. If so, the `db_open/4` and [db_open/5](@ref db_open) have the following mode: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ?- db_open(odbc,Connection,ODBC_DSN,User,Password). ?- db_open(odbc,ODBC_DSN,User,Password). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ For instance, if you do `db_open(odbc,odbc_dsn,guest,'')`. it will connect to a database, through ODBC, using the definitions on the `odbc_dsn` DSN configured on the system. The user will be the user `guest` with no password. @section Accessing_a_Relation Accessing a Relation
  • db_import(+Conn,+RelationName,+PredName). @anchor db_import
  • db_import(+RelationName,+PredName).
Assuming you have access permission for the relation you wish to import, you can use [db_import/3](@ref db_import) or `db_import/2` as: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ?- db_import(Conn,RelationName,PredName). ?- db_import(RelationName,PredName). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ where _RelationName_, is the name of relation we wish to access, _PredName_ is the name of the predicate we wish to use to access the relation from YAP. _Conn_, is the connection identifier, which again can be dropped so that the default myddas connection is used. For instance, if we want to access the relation phonebook, using the predicate `phonebook/3` we write: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ?- db_import(con1,phonebook,phonebook). yes ?- phonebook(Letter,Name,Number). Letter = 'D', Name = 'John Doe', Number = 123456789 ? yes ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Backtracking can then be used to retrieve the next row of the relation phonebook. Records with particular field values may be selected in the same way as in Prolog. (In particular, no mode specification for database predicates is required). For instance: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ?- phonebook(Letter,'John Doe',Letter). Letter = 'D', Number = 123456789 ? yes ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ generates the query ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ SELECT A.Letter , 'John Doe' , A.Number FROM 'phonebook' A WHERE A.Name = 'John Doe'; ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ @section View_Level_Interface View Level Interface
  • db view(+,+,+). @anchor db_view
  • db view(+,+).
If we import a database relation, such as an edge relation representing the edges of a directed graph, through ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ?- db_import('Edge',edge). yes ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ and we then write a query to retrieve all the direct cycles in the graph, such as ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ?- edge(A,B), edge(B,A). A = 10, B = 20 ? ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ this is clearly inefficient [3], because of relation-level access. Relation-level access means that a separate SQL query will be generated for every goal in the body of the clause. For the second `edge/2` goal, a SQL query is generated using the variable bindings that result from the first `edge/2` goal execution. If the second `edge/2` goal fails, or if alternative solutions are demanded, backtracking access the next tuple for the first `edge/2` goal and another SQL query will be generated for the second `edge/2` goal. The generation of this large number of queries and the communication overhead with the database system for each of them, makes the relation-level approach inefficient. To solve this problem the view level interface can be used for the definition of rules whose bodies includes only imported database predicates. One can use the view level interface through the predicates [db_view/3](@ref db_view) and `db_view/2`: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ?- db_view(Conn,PredName(Arg_1,...,Arg_n),DbGoal). ?- db_view(PredName(Arg_1,...,Arg_n),DbGoal). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ All arguments are standard Prolog terms. _Arg1_ through _Argn_ define the attributes to be retrieved from the database, while _DbGoal_ defines the selection restrictions and join conditions. _Conn_ is the connection identifier, which again can be dropped. Calling predicate `PredName/n` will retrieve database tuples using a single SQL query generated for the _DbGoal_. We next show an example of a view definition for the direct cycles discussed above. Assuming the declaration: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ?- db_import('Edge',edge). yes ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ we write: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ?- db_view(direct_cycle(A,B),(edge(A,B), edge(B,A))). yes ?- direct_cycle(A,B)). A = 10, B = 20 ? ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ This call generates the SQL statement: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ SELECT A.attr1 , A.attr2 FROM Edge A , Edge B WHERE B.attr1 = A.attr2 AND B.attr2 = A.attr1; ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Backtracking, as in relational level interface, can be used to retrieve the next row of the view. The view interface also supports aggregate function predicates such as `sum`, `avg`, `count`, `min` and `max`. For instance: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ?- db_view(count(X),(X is count(B, B^edge(10,B)))). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ generates the query : ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ SELECT COUNT(A.attr2) FROM Edge A WHERE A.attr1 = 10; ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ To know how to use db `view/3`, please refer to Draxler's Prolog to SQL Compiler Manual. @section Accessing_Tables_in_Data_Sources_Using_SQL Accessing Tables in Data Sources Using SQL
  • db_sql(+,+,?). @anchor db_sql
  • db_sql(+,?).
It is also possible to explicitly send a SQL query to the database server using ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ?- db_sql(Conn,SQL,List). ?- db_sql(SQL,List). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ where _SQL_ is an arbitrary SQL expression, and _List_ is a list holding the first tuple of result set returned by the server. The result set can also be navigated through backtracking. Example: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ?- db_sql('SELECT * FROM phonebook',LA). LA = ['D','John Doe',123456789] ? ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ @section Insertion_of_Rows Insertion of Rows
  • db_assert(+,+). @anchor db_assert
  • db_assert(+).
Assuming you have imported the related base table using `db_import/2` or [db_import/3](@ref db_import), you can insert to that table by using [db_assert/2](@ref db_assert) predicate any given fact. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ?- db_assert(Conn,Fact). ?- db_assert(Fact). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ The second argument must be declared with all of its arguments bound to constants. For example assuming `helloWorld` is imported through `db_import/2`: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ?- db_import('Hello World',helloWorld). yes ?- db_assert(helloWorld('A' ,'Ana',31)). yes ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ This, would generate the following query ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ INSERT INTO helloWorld VALUES ('A','Ana',3) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ which would insert into the helloWorld, the following row: `A,Ana,31`. If we want to insert `NULL` values into the relation, we call [db_assert/2](@ref db_assert) with a uninstantiated variable in the data base imported predicate. For example, the following query on the YAP-prolog system: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ?- db_assert(helloWorld('A',NULL,31)). yes ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Would insert the row: `A,null value,31` into the relation `Hello World`, assuming that the second row allows null values.
  • db insert(+,+,+). @anchor db_insert
  • db insert(+,+).
This predicate would create a new database predicate, which will insert any given tuple into the database. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ?- db_insert(Conn,RelationName,PredName). ?- db_insert(RelationName,PredName). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ This would create a new predicate with name _PredName_, that will insert tuples into the relation _RelationName_. is the connection identifier. For example, if we wanted to insert the new tuple `('A',null,31)` into the relation `Hello World`, we do: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ?- db_insert('Hello World',helloWorldInsert). yes ?- helloWorldInsert('A',NULL,31). yes ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ @section Types_of_Attributes Types of Attributes
  • db_get_attributes_types(+,+,?). @anchor db_get_attributes_types
  • db_get_attributes_types(+,?).
The prototype for this predicate is the following: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ?- db_get_attributes_types(Conn,RelationName,ListOfFields). ?- db_get_attributes_types(RelationName,ListOfFields). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ You can use the predicate `db_get_attributes types/2` or [db_get_attributes_types/3](@ref db_get_attributes_types), to know what are the names and attributes types of the fields of a given relation. For example: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ?- db_get_attributes_types(myddas,'Hello World',LA). LA = ['Number',integer,'Name',string,'Letter',string] ? yes ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ where Hello World is the name of the relation and myddas is the connection identifier. @section Number_of_Fields Number of Fields
  • db_number_of_fields(+,?). @anchor db_number_of_fields
  • db_number_of_fields(+,+,?).
The prototype for this predicate is the following: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ?- db_number_of_fields(Conn,RelationName,Arity). ?- db_number_of_fields(RelationName,Arity). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ You can use the predicate [db_number_of_fields/2](@ref db_number_of_fields) or `db_number_of_fields/3` to know what is the arity of a given relation. Example: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ?- db_number_of_fields(myddas,'Hello World',Arity). Arity = 3 ? yes ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ where `Hello World` is the name of the relation and `myddas` is the connection identifier. @section Describing_a_Relation Describing a Relation
  • db_datalog_describe(+,+). @anchor db_datalog_describe
  • db_datalog_describe(+).
The db `datalog_describe/2` predicate does not really returns any value. It simply prints to the screen the result of the MySQL describe command, the same way as `DESCRIBE` in the MySQL prompt would. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ?- db_datalog_describe(myddas,'Hello World'). +----------+----------+------+-----+---------+-------+ | Field | Type | Null | Key | Default | Extra | +----------+----------+------+-----+---------+-------+ + Number | int(11) | YES | | NULL | | + Name | char(10) | YES | | NULL | | + Letter | char(1) | YES | | NULL | | +----------+----------+------+-----+---------+-------+ yes ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  • db_describe(+,+). @anchor db_describe
  • db_describe(+).
The `db_describe/3` predicate does the same action as [db_datalog_describe/2](@ref db_datalog_describe) predicate but with one major difference. The results are returned by backtracking. For example, the last query: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ?- db_describe(myddas,'Hello World',Term). Term = tableInfo('Number',int(11),'YES','',null(0),'') ? ; Term = tableInfo('Name',char(10),'YES','',null(1),'' ? ; Term = tableInfo('Letter',char(1),'YES','',null(2),'') ? ; no ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ @section Enumerating_Relations Enumeration Relations
  • db_datalog_show_tables(+).
  • db_datalog_show_tables
If we need to know what relations exists in a given MySQL Schema, we can use the `db_datalog_show_tables/1` predicate. As db_datalog_describe/2, it does not returns any value, but instead prints to the screen the result of the `SHOW TABLES` command, the same way as it would be in the MySQL prompt. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ?- db_datalog_show_tables(myddas). +-----------------+ | Tables_in_guest | +-----------------+ | Hello World | +-----------------+ yes ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  • db_show_tables(+, ?). @anchor db_show_tables
  • db_show_tables(?)
The [db_show_tables/2](@ref db_show_tables) predicate does the same action as `db_show_tables/1` predicate but with one major difference. The results are returned by backtracking. For example, given the last query: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ?- db_show_tables(myddas,Table). Table = table('Hello World') ? ; no ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ @section The_MYDDAS_MySQL_Top_Level The MYDDAS MySQL Top Level
  • db_top_level(+,+,+,+,+). @anchor db_top_level
  • db_top_level(+,+,+,+).
Through MYDDAS is also possible to access the MySQL Database Server, in the same wthe mysql client. In this mode, is possible to query the SQL server by just using the standard SQL language. This mode is exactly the same as different from the standard mysql client. We can use this mode, by invoking the db top level/5. as one of the following: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ?- db_top_level(mysql,Connection,Host/Database,User,Password). ?- db_top_level(mysql,Connection,Host/Database/Port,User,Password). ?- db_top_level(mysql,Connection,Host/Database/UnixSocket,User,Password). ?- db_top_level(mysql,Connection,Host/Database/Port/UnixSocket,User,Password). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Usage is similar as the one described for the [db_open/5](@ref db_open) predicate discussed above. If the login is successful, automatically the prompt of the mysql client will be used. For example: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ?- db_top_level(mysql,con1,localhost/guest_db,guest,''). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ opens a connection identified by the `con1` atom, to an instance of a MySQL server running on host `localhost`, using database guest `db` and user `guest` with empty password. After this is possible to use MYDDAS as the mysql client. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ?- db_top_level(mysql,con1,localhost/guest_db,guest,''). Reading table information for completion of table and column names You can turn off this feature to get a quicker startup with -A Welcome to the MySQL monitor. Commands end with ; or \g. Your MySQL connection id is 4468 to server version: 4.0.20 Type 'help;' or '\h' for help. Type '\c' to clear the buffer. mysql> exit Bye yes ?- ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ @section Other_MYDDAS_Properties Other MYDDAS Properties
  • db_verbose(+).
  • db_top_level(+,+,+,+).
When we ask a question to YAP, using a predicate asserted by [db_import/3](@ref db_import), or by [db_view/3](@ref db_view), this will generate a SQL `QUERY`. If we want to see that query, we must to this at a given point in our session on YAP. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ?- db_verbose(1). yes ?- ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ If we want to disable this feature, we must call the `db_verbose/1` predicate with the value 0.
  • db_module(?). @anchor db_module
When we create a new database predicate, by using [db_import/3](@ref db_import), [db_view/3](@ref db_view) or [db_insert/3](@ref db_insert), that predicate will be asserted by default on the `user` module. If we want to change this value, we can use the [db_module/1](@ref db_module) predicate to do so. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ?- db_module(lists). yes ?- ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ By executing this predicate, all of the predicates asserted by the predicates enumerated earlier will created in the lists module. If we want to put back the value on default, we can manually put the value user. Example: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ?- db_module(user). yes ?- ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ We can also see in what module the predicates are being asserted by doing: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ?- db_module(X). X=user yes ?- ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  • db_my_result_set(?). @anchor db_my_result_set
The MySQL C API permits two modes for transferring the data generated by a query to the client, in our case YAP. The first mode, and the default mode used by the MYDDAS-MySQL, is to store the result. This mode copies all the information generated to the client side. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ?- db_my_result_set(X). X=store_result yes ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ The other mode that we can use is use result. This one uses the result set created directly from the server. If we want to use this mode, he simply do ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ?- db_my_result_set(use_result). yes ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ After this command, all of the database predicates will use use result by default. We can change this by doing again `db_my_result_set(store_result)`.
  • db_my_sql_mode(+Conn,?SQL_Mode). @anchor db_my_sql_mode
  • db_my_sql_mode(?SQL_Mode).
The MySQL server allows the user to change the SQL mode. This can be very useful for debugging proposes. For example, if we want MySQL server not to ignore the INSERT statement warnings and instead of taking action, report an error, we could use the following SQL mode. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ?-db_my_sql_mode(traditional). yes ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ You can see the available SQL Modes at the MySQL homepage at . @page Real Real:: Talking to the R language @copydoc real @page Threads Threads YAP implements a SWI-Prolog compatible multithreading library. Like in SWI-Prolog, Prolog threads have their own stacks and only share the Prolog heap: predicates, records, flags and other global non-backtrackable data. The package is based on the POSIX thread standard (Butenhof:1997:PPT) used on most popular systems except for MS-Windows. @section Creating_and_Destroying_Prolog_Threads Creating and Destroying Prolog Threads
  • thread_create(: _Goal_, - _Id_, + _Options_) @anchor thread_create Create a new Prolog thread (and underlying C-thread) and start it by executing _Goal_. If the thread is created successfully, the thread-identifier of the created thread is unified to _Id_. _Options_ is a list of options. Currently defined options are:
    • stack Set the limit in K-Bytes to which the Prolog stacks of this thread may grow. If omitted, the limit of the calling thread is used. See also the commandline `-S` option.
    • trail Set the limit in K-Bytes to which the trail stack of this thread may grow. If omitted, the limit of the calling thread is used. See also the commandline option `-T`.
    • alias Associate an alias-name with the thread. This named may be used to refer to the thread and remains valid until the thread is joined (see [thread_join/2](@ref thread_join)).
    • at_exit Define an exit hook for the thread. This hook is called when the thread terminates, no matter its exit status.
    • detached If `false` (default), the thread can be waited for using [thread_join/2](@ref thread_join). [thread_join/2](@ref thread_join) must be called on this thread to reclaim the all resources associated to the thread. If `true`, the system will reclaim all associated resources automatically after the thread finishes. Please note that thread identifiers are freed for reuse after a detached thread finishes or a normal thread has been joined. See also [thread_join/2](@ref thread_join) and [thread_detach/1](@ref thread_detach).
    The _Goal_ argument is copied to the new Prolog engine. This implies further instantiation of this term in either thread does not have consequences for the other thread: Prolog threads do not share data from their stacks.
  • thread_create(: _Goal_, - _Id_) Create a new Prolog thread using default options. See [thread_create/3](@ref thread_create).
  • thread_create(: _Goal_) Create a new Prolog detached thread using default options. See [thread_create/3](@ref thread_create).
  • thread_self(- _Id_) @anchor thread_self Get the Prolog thread identifier of the running thread. If the thread has an alias, the alias-name is returned.
  • thread_join(+ _Id_, - _Status_) @anchor thread_join Wait for the termination of thread with given _Id_. Then unify the result-status of the thread with _Status_. After this call, _Id_ becomes invalid and all resources associated with the thread are reclaimed. Note that threads with the attribute `detached` `true` cannot be joined. See also [current_thread/2](@ref current_thread). A thread that has been completed without [thread_join/2](@ref thread_join) being called on it is partly reclaimed: the Prolog stacks are released and the C-thread is destroyed. A small data-structure representing the exit-status of the thread is retained until [thread_join/2](@ref thread_join) is called on the thread. Defined values for _Status_ are:
    • true The goal has been proven successfully.
    • false The goal has failed.
    • exception( _Term_) The thread is terminated on an exception. See [print_message/2](@ref print_message) to turn system exceptions into readable messages.
    • exited( _Term_) The thread is terminated on [thread_exit/1](@ref thread_exit) using the argument _Term_.
  • thread_detach(+ _Id_) @anchor thread_detach Switch thread into detached-state (see `detached` option at [thread_create/3](@ref thread_create) at runtime. _Id_ is the identifier of the thread placed in detached state. One of the possible applications is to simplify debugging. Threads that are created as `detached` leave no traces if they crash. For not-detached threads the status can be inspected using [current_thread/2](@ref current_thread). Threads nobody is waiting for may be created normally and detach themselves just before completion. This way they leave no traces on normal completion and their reason for failure can be inspected.
  • thread_yield @anchor thread_yield Voluntarily relinquish the processor.
  • thread_exit(+ _Term_) @anchor thread_exit Terminates the thread immediately, leaving `exited( _Term_)` as result-state for [thread_join/2](@ref thread_join). If the thread has the attribute `detached` `true` it terminates, but its exit status cannot be retrieved using [thread_join/2](@ref thread_join) making the value of _Term_ irrelevant. The Prolog stacks and C-thread are reclaimed.
  • thread_at_exit(: _Term_) @anchor thread_at_exit Run _Goal_ just before releasing the thread resources. This is to be compared to `at_halt/1`, but only for the current thread. These hooks are ran regardless of why the execution of the thread has been completed. As these hooks are run, the return-code is already available through [thread_property/2](@ref thread_property) using the result of [thread_self/1](@ref thread_self) as thread-identifier. If you want to guarantee the execution of an exit hook no matter how the thread terminates (the thread can be aborted before reaching the [thread_at_exit/1](@ref thread_at_exit) call), consider using instead the `at_exit/1` option of [thread_create/3](@ref thread_create).
  • thread_setconcurrency(+ _Old_, - _New_) @anchor thread_setconcurrency Determine the concurrency of the process, which is defined as the maximum number of concurrently active threads. `Active' here means they are using CPU time. This option is provided if the thread-implementation provides `pthread_setconcurrency()`. Solaris is a typical example of this family. On other systems this predicate unifies _Old_ to 0 (zero) and succeeds silently.
  • thread_sleep(+ _Time_) @anchor thread_sleep Make current thread sleep for _Time_ seconds. _Time_ may be an integer or a floating point number. When time is zero or a negative value the call succeeds and returns immediately. This call should not be used if alarms are also being used.
@section Monitoring_Threads Monitoring Threads Normal multi-threaded applications should not need these the predicates from this section because almost any usage of these predicates is unsafe. For example checking the existence of a thread before signalling it is of no use as it may vanish between the two calls. Catching exceptions using [catch/3](@ref catch) is the only safe way to deal with thread-existence errors. These predicates are provided for diagnosis and monitoring tasks.
  • thread_property(? _Id_, ? _Property_) @anchor thread_property Enumerates the properties of the specified thread. Calling [thread_property/2](@ref thread_property) does not influence any thread. See also [thread_join/2](@ref thread_join). For threads that have an alias-name, this name can be used in _Id_ instead of the numerical thread identifier. _Property_ is one of:
    • status( _Status_) The thread status of a thread (see below).
    • alias( _Alias_) The thread alias, if it exists.
    • at_exit( _AtExit_) The thread exit hook, if defined (not available if the thread is already terminated).
    • detached( _Boolean_) The detached state of the thread.
    • stack( _Size_) The thread stack data-area size.
    • trail( _Size_) The thread trail data-area size.
    • system( _Size_) The thread system data-area size.
  • current_thread(+ _Id_, - _Status_) @anchor current_thread Enumerates identifiers and status of all currently known threads. Calling [current_thread/2](@ref current_thread) does not influence any thread. See also [thread_join/2](@ref thread_join). For threads that have an alias-name, this name is returned in _Id_ instead of the numerical thread identifier. _Status_ is one of:
    • running The thread is running. This is the initial status of a thread. Please note that threads waiting for something are considered running too.
    • false The _Goal_ of the thread has been completed and failed.
    • true The _Goal_ of the thread has been completed and succeeded.
    • exited( _Term_) The _Goal_ of the thread has been terminated using [thread_exit/1](@ref thread_exit) with _Term_ as argument. If the underlying native thread has exited (using pthread_exit()) _Term_ is unbound.
    • exception( _Term_) The _Goal_ of the thread has been terminated due to an uncaught exception (see [throw/1](@ref throw) and [catch/3](@ref catch)).
  • thread_statistics(+ _Id_, + _Key_, - _Value_) @anchor thread_statistics Obtains statistical information on thread _Id_ as `statistics/2` does in single-threaded applications. This call returns all keys of `statistics/2`, although only information statistics about the stacks and CPU time yield different values for each thread.
  • mutex_statistics @anchor mutex_statistics Print usage statistics on internal mutexes and mutexes associated with dynamic predicates. For each mutex two numbers are printed: the number of times the mutex was acquired and the number of collisions: the number times the calling thread has to wait for the mutex. The collision-count is not available on Windows as this would break portability to Windows-95/98/ME or significantly harm performance. Generally collision count is close to zero on single-CPU hardware.
  • threads @anchor threads Prints a table of current threads and their status.
@section Thread_Communication Thread communication @subsection Message_Queues Message Queues Prolog threads can exchange data using dynamic predicates, database records, and other globally shared data. These provide no suitable means to wait for data or a condition as they can only be checked in an expensive polling loop. Message queues provide a means for threads to wait for data or conditions without using the CPU. Each thread has a message-queue attached to it that is identified by the thread. Additional queues are created using `message_queue_create/2`.
  • thread_send_message(+ _Term_) @anchor thread_send_message Places _Term_ in the message-queue of the thread running the goal. Any term can be placed in a message queue, but note that the term is copied to the receiving thread and variable-bindings are thus lost. This call returns immediately.
  • thread_send_message(+ _QueueOrThreadId_, + _Term_) Place _Term_ in the given queue or default queue of the indicated thread (which can even be the message queue of itself (see [thread_self/1](@ref thread_self)). Any term can be placed in a message queue, but note that the term is copied to the receiving thread and variable-bindings are thus lost. This call returns immediately. If more than one thread is waiting for messages on the given queue and at least one of these is waiting with a partially instantiated _Term_, the waiting threads are all sent a wakeup signal, starting a rush for the available messages in the queue. This behaviour can seriously harm performance with many threads waiting on the same queue as all-but-the-winner perform a useless scan of the queue. If there is only one waiting thread or all waiting threads wait with an unbound variable an arbitrary thread is restarted to scan the queue.
  • thread_get_message(? _Term_) @anchor thread_get_message Examines the thread message-queue and if necessary blocks execution until a term that unifies to _Term_ arrives in the queue. After a term from the queue has been unified unified to _Term_, the term is deleted from the queue and this predicate returns. Please note that not-unifying messages remain in the queue. After the following has been executed, thread 1 has the term `gnu` in its queue and continues execution using _A_ is `gnat`. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ thread_get_message(a(A)), thread_send_message(b(gnu)), thread_send_message(a(gnat)), ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ See also [thread_peek_message/1](@ref thread_peek_message).
  • message_queue_create(? _Queue_) @anchor message_queue_create If _Queue_ is an atom, create a named queue. To avoid ambiguity on `thread_send_message/2`, the name of a queue may not be in use as a thread-name. If _Queue_ is unbound an anonymous queue is created and _Queue_ is unified to its identifier.
  • message_queue_destroy(+ _Queue_) @anchor message_queue_destroy Destroy a message queue created with [message_queue_create/1](@ref message_queue_create). It is not allows to destroy the queue of a thread. Neither is it allowed to destroy a queue other threads are waiting for or, for anonymous message queues, may try to wait for later.
  • thread_get_message(+ _Queue_, ? _Term_) As [thread_get_message/1](@ref thread_get_message), operating on a given queue. It is allowed to peek into another thread's message queue, an operation that can be used to check whether a thread has swallowed a message sent to it.
  • thread_peek_message(? _Term_) @anchor thread_peek_message Examines the thread message-queue and compares the queued terms with _Term_ until one unifies or the end of the queue has been reached. In the first case the call succeeds (possibly instantiating _Term_. If no term from the queue unifies this call fails.
  • thread_peek_message(+ _Queue_, ? _Term_) As [thread_peek_message/1](@ref thread_peek_message), operating on a given queue. It is allowed to peek into another thread's message queue, an operation that can be used to check whether a thread has swallowed a message sent to it.
Explicit message queues are designed with the worker-pool model in mind, where multiple threads wait on a single queue and pick up the first goal to execute. Below is a simple implementation where the workers execute arbitrary Prolog goals. Note that this example provides no means to tell when all work is done. This must be realised using additional synchronisation. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ % create_workers(+Id, +N) % % Create a pool with given Id and number of workers. create_workers(Id, N) :- message_queue_create(Id), forall(between(1, N, _), thread_create(do_work(Id), _, [])). do_work(Id) :- repeat, thread_get_message(Id, Goal), ( catch(Goal, E, print_message(error, E)) -> true ; print_message(error, goal_failed(Goal, worker(Id))) ), fail. % work(+Id, +Goal) % % Post work to be done by the pool work(Id, Goal) :- thread_send_message(Id, Goal). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ @subsection Signalling_Threads Signalling Threads These predicates provide a mechanism to make another thread execute some goal as an interrupt. Signalling threads is safe as these interrupts are only checked at safe points in the virtual machine. Nevertheless, signalling in multi-threaded environments should be handled with care as the receiving thread may hold a mutex (see [with_mutex/2](@ref with_mutex)). Signalling probably only makes sense to start debugging threads and to cancel no-longer-needed threads with [throw/1](@ref throw), where the receiving thread should be designed carefully do handle exceptions at any point.
  • thread_signal(+ _ThreadId_, : _Goal_) @anchor thread_signal Make thread _ThreadId_ execute _Goal_ at the first opportunity. In the current implementation, this implies at the first pass through the Call-port. The predicate [thread_signal/2](@ref thread_signal) itself places _Goal_ into the signalled-thread's signal queue and returns immediately. Signals (interrupts) do not cooperate well with the world of multi-threading, mainly because the status of mutexes cannot be guaranteed easily. At the call-port, the Prolog virtual machine holds no locks and therefore the asynchronous execution is safe. _Goal_ can be any valid Prolog goal, including [throw/1](@ref throw) to make the receiving thread generate an exception and [trace/0](@ref trace) to start tracing the receiving thread.
@subsection Threads_and_Dynamic_Predicates Threads and Dynamic Predicates Besides queues threads can share and exchange data using dynamic predicates. The multi-threaded version knows about two types of dynamic predicates. By default, a predicate declared dynamic (see [dynamic/1](@ref dynamic)) is shared by all threads. Each thread may assert, retract and run the dynamic predicate. Synchronisation inside Prolog guarantees the consistency of the predicate. Updates are logical: visible clauses are not affected by assert/retract after a query started on the predicate. In many cases primitive from thread synchronisation should be used to ensure application invariants on the predicate are maintained. Besides shared predicates, dynamic predicates can be declared with the [thread_local/1](@ref thread_local) directive. Such predicates share their attributes, but the clause-list is different in each thread.
  • thread_local( _+Functor/Arity_) @anchor thread_local related to the dynamic/1 directive. It tells the system that the predicate may be modified using [assert/1](@ref assert), [retract/1](@ref retract), etc, during execution of the program. Unlike normal shared dynamic data however each thread has its own clause-list for the predicate. As a thread starts, this clause list is empty. If there are still clauses as the thread terminates these are automatically reclaimed by the system. The `thread_local` property implies the property `dynamic`. Thread-local dynamic predicates are intended for maintaining thread-specific state or intermediate results of a computation. It is not recommended to put clauses for a thread-local predicate into a file as in the example below as the clause is only visible from the thread that loaded the source-file. All other threads start with an empty clause-list. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ :- thread_local foo/1. foo(gnat). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
@section Thread_Synchronisation Thread Synchronisation All internal Prolog operations are thread-safe. This implies two Prolog threads can operate on the same dynamic predicate without corrupting the consistency of the predicate. This section deals with user-level mutexes (called monitors in ADA or critical-sections by Microsoft). A mutex is a MUTual EXclusive device, which implies at most one thread can hold a mutex. Mutexes are used to realise related updates to the Prolog database. With `related', we refer to the situation where a `transaction' implies two or more changes to the Prolog database. For example, we have a predicate `address/2`, representing the address of a person and we want to change the address by retracting the old and asserting the new address. Between these two operations the database is invalid: this person has either no address or two addresses, depending on the assert/retract order. Here is how to realise a correct update: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ :- initialization mutex_create(addressbook). change_address(Id, Address) :- mutex_lock(addressbook), retractall(address(Id, _)), asserta(address(Id, Address)), mutex_unlock(addressbook). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  • mutex_create(? _MutexId_) @anchor mutex_create Create a mutex. if _MutexId_ is an atom, a named mutex is created. If it is a variable, an anonymous mutex reference is returned. There is no limit to the number of mutexes that can be created.
  • mutex_destroy(+ _MutexId_) @anchor mutex_destroy Destroy a mutex. After this call, _MutexId_ becomes invalid and further references yield an `existence_error` exception.
  • with_mutex(+ _MutexId_, : _Goal_) @anchor with_mutex Execute _Goal_ while holding _MutexId_. If _Goal_ leaves choicepoints, these are destroyed (as in [once/1](@ref once)). The mutex is unlocked regardless of whether _Goal_ succeeds, fails or raises an exception. An exception thrown by _Goal_ is re-thrown after the mutex has been successfully unlocked. See also `mutex_create/2`. Although described in the thread-section, this predicate is also available in the single-threaded version, where it behaves simply as [once/1](@ref once).
  • mutex_lock(+ _MutexId_) @anchor mutex_lock Lock the mutex. Prolog mutexes are recursive mutexes: they can be locked multiple times by the same thread. Only after unlocking it as many times as it is locked, the mutex becomes available for locking by other threads. If another thread has locked the mutex the calling thread is suspended until to mutex is unlocked. If _MutexId_ is an atom, and there is no current mutex with that name, the mutex is created automatically using [mutex_create/1](@ref mutex_create). This implies named mutexes need not be declared explicitly. Please note that locking and unlocking mutexes should be paired carefully. Especially make sure to unlock mutexes even if the protected code fails or raises an exception. For most common cases use [with_mutex/2](@ref with_mutex), which provides a safer way for handling Prolog-level mutexes.
  • mutex_trylock(+ _MutexId_) @anchor mutex_trylock As mutex_lock/1, but if the mutex is held by another thread, this predicates fails immediately.
  • mutex_unlock(+ _MutexId_) @anchor mutex_unlock Unlock the mutex. This can only be called if the mutex is held by the calling thread. If this is not the case, a `permission_error` exception is raised.
  • mutex_unlock_all @anchor mutex_unlock_all Unlock all mutexes held by the current thread. This call is especially useful to handle thread-termination using [abort/0](@ref abort) or exceptions. See also [thread_signal/2](@ref thread_signal).
  • current_mutex(? _MutexId_, ? _ThreadId_, ? _Count_) @anchor current_mutex Enumerates all existing mutexes. If the mutex is held by some thread, _ThreadId_ is unified with the identifier of the holding thread and _Count_ with the recursive count of the mutex. Otherwise, _ThreadId_ is `[]` and _Count_ is 0.
@section Parallelism Parallelism There has been a sizeable amount of work on an or-parallel implementation for YAP, called *YAPOr*. Most of this work has been performed by Ricardo Rocha. In this system parallelism is exploited implicitly by running several alternatives in or-parallel. This option can be enabled from the `configure` script or by checking the system's `Makefile`. *YAPOr* is still a very experimental system, going through rapid development. The following restrictions are of note:
  • *YAPOr* currently only supports the Linux/X86 and SPARC/Solaris platforms. Porting to other Unix-like platforms should be straightforward.
  • *YAPOr* does not support parallel updates to the data-base.
  • *YAPOr* does not support opening or closing of streams during parallel execution.
  • Garbage collection and stack shifting are not supported in *YAPOr*.
  • Built-ins that cause side-effects can only be executed when left-most in the search-tree. There are no primitives to provide asynchronous or cavalier execution of these built-ins, as in Aurora or Muse.
  • YAP does not support voluntary suspension of work.
We expect that some of these restrictions will be removed in future releases. @section Tabling Tabling *YAPTab* is the tabling engine that extends YAP's execution model to support tabled evaluation for definite programs. YAPTab was implemented by Ricardo Rocha and its implementation is largely based on the ground-breaking design of the XSB Prolog system, which implements the SLG-WAM. Tables are implemented using tries and YAPTab supports the dynamic intermixing of batched scheduling and local scheduling at the subgoal level. Currently, the following restrictions are of note:
  • YAPTab does not handle tabled predicates with loops through negation (undefined behaviour).
  • YAPTab does not handle tabled predicates with cuts (undefined behaviour).
  • YAPTab does not support coroutining (configure error).
  • YAPTab does not support tabling dynamic predicates (permission error).
To experiment with YAPTab use `--enable-tabling` in the configure script or add `-DTABLING` to `YAP_EXTRAS` in the system's `Makefile`. We next describe the set of built-ins predicates designed to interact with YAPTab and control tabled execution:
  • table + _P_ @anchor table Declares predicate _P_ (or a list of predicates _P1_,..., _Pn_ or [ _P1_,..., _Pn_]) as a tabled predicate. _P_ must be written in the form _name/arity_. Examples: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ :- table son/3. :- table father/2. :- table mother/2. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ or ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ :- table son/3, father/2, mother/2. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ or ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ :- table [son/3, father/2, mother/2]. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  • is_tabled(+ _P_) @anchor is_tabled Succeeds if the predicate _P_ (or a list of predicates _P1_,..., _Pn_ or [ _P1_,..., _Pn_]), of the form _name/arity_, is a tabled predicate.
  • tabling_mode(+ _P_,? _Mode_) @anchor tabling_mode Sets or reads the default tabling mode for a tabled predicate _P_ (or a list of predicates _P1_,..., _Pn_ or [ _P1_,..., _Pn_]). The list of _Mode_ options includes:
    • batched Defines that, by default, batched scheduling is the scheduling strategy to be used to evaluated calls to predicate _P_.
    • local Defines that, by default, local scheduling is the scheduling strategy to be used to evaluated calls to predicate _P_.
    • exec_answers Defines that, by default, when a call to predicate _P_ is already evaluated (completed), answers are obtained by executing compiled WAM-like code directly from the trie data structure. This reduces the loading time when backtracking, but the order in which answers are obtained is undefined.
    • load_answers Defines that, by default, when a call to predicate _P_ is already evaluated (completed), answers are obtained (as a consumer) by loading them from the trie data structure. This guarantees that answers are obtained in the same order as they were found. Somewhat less efficient but creates less choice-points.
    The default tabling mode for a new tabled predicate is `batched` and `exec_answers`. To set the tabling mode for all predicates at once you can use the [yap_flag/2](@ref yap_flag) predicate as described next.
  • yap_flag(tabling_mode,? _Mode_) Sets or reads the tabling mode for all tabled predicates. The list of _Mode_ options includes:
    • default Defines that (i) all calls to tabled predicates are evaluated using the predicate default mode, and that (ii) answers for all completed calls are obtained by using the predicate default mode.
    • batched Defines that all calls to tabled predicates are evaluated using batched scheduling. This option ignores the default tabling mode of each predicate.
    • local Defines that all calls to tabled predicates are evaluated using local scheduling. This option ignores the default tabling mode of each predicate.
    • exec_answers Defines that answers for all completed calls are obtained by executing compiled WAM-like code directly from the trie data structure. This option ignores the default tabling mode of each predicate.
    • load_answers Defines that answers for all completed calls are obtained by loading them from the trie data structure. This option ignores the default tabling mode of each predicate.
  • abolish_table(+ _P_) @anchor abolish_table Removes all the entries from the table space for predicate _P_ (or a list of predicates _P1_,..., _Pn_ or [ _P1_,..., _Pn_]). The predicate remains as a tabled predicate.
  • abolish_all_tables/0 @anchor abolish_all_tables Removes all the entries from the table space for all tabled predicates. The predicates remain as tabled predicates.
  • show_table(+ _P_) @anchor show_table Prints table contents (subgoals and answers) for predicate _P_ (or a list of predicates _P1_,..., _Pn_ or [ _P1_,..., _Pn_]).
  • table_statistics(+ _P_) @anchor table_statistics Prints table statistics (subgoals and answers) for predicate _P_ (or a list of predicates _P1_,..., _Pn_ or [ _P1_,..., _Pn_]).
  • tabling_statistics/0 @anchor tabling_statistics Prints statistics on space used by all tables.
@section Low_Level_Tracing Tracing at Low Level It is possible to follow the flow at abstract machine level if YAP is compiled with the flag `LOW_LEVEL_TRACER`. Note that this option is of most interest to implementers, as it quickly generates an huge amount of information. Low level tracing can be toggled from an interrupt handler by using the option `T`. There are also two built-ins that activate and deactivate low level tracing:
  • start_low_level_trace @anchor start_low_level_trace Begin display of messages at procedure entry and retry.
  • stop_low_level_trace @anchor stop_low_level_trace Stop display of messages at procedure entry and retry.
Note that this compile-time option will slow down execution. @section Low_Level_Profiling Profiling the Abstract Machine Implementors may be interested in detecting on which abstract machine instructions are executed by a program. The `ANALYST` flag can give WAM level information. Note that this option slows down execution very substantially, and is only of interest to developers of the system internals, or to system debuggers.
  • reset_op_counters @anchor reset_op_counters Reinitialize all counters.
  • show_op_counters(+ _A_) @anchor show_op_counters Display the current value for the counters, using label _A_. The label must be an atom.
  • show_ops_by_group(+ _A_) @anchor show_ops_by_group Display the current value for the counters, organized by groups, using label _A_. The label must be an atom.
@section Debugging Debugging @section Deb_Preds Debugging Predicates The following predicates are available to control the debugging of programs:
  • debug Switches the debugger on.
  • debugging @anchor debugging Outputs status information about the debugger which includes the leash mode and the existing spy-points, when the debugger is on.
  • nodebug @anchor nodebug Switches the debugger off.
  • spy + _P_ @anchor spy Sets spy-points on all the predicates represented by _P_. _P_ can either be a single specification or a list of specifications. Each one must be of the form _Name/Arity_ or _Name_. In the last case all predicates with the name _Name_ will be spied. As in C-Prolog, system predicates and predicates written in C, cannot be spied.
  • nospy + _P_ @anchor nospy Removes spy-points from all predicates specified by _P_. The possible forms for _P_ are the same as in `spy P`.
  • nospyall @anchor nospyall Removes all existing spy-points.
  • leash(+ _M_) @anchor leash Sets leashing mode to _M_. The mode can be specified as:
    • full prompt on Call, Exit, Redo and Fail
    • tight prompt on Call, Redo and Fail
    • half prompt on Call and Redo
    • loose prompt on Call
    • off never prompt
    • none never prompt, same as `off`
    The initial leashing mode is `full`. The user may also specify directly the debugger ports where he wants to be prompted. If the argument for leash is a number _N_, each of lower four bits of the number is used to control prompting at one the ports of the box model. The debugger will prompt according to the following conditions:
    • if `N/\\ 1 =\\= 0` prompt on fail
    • if `N/\\ 2 =\\= 0` prompt on redo
    • if `N/\\ 4 =\\= 0` prompt on exit
    • if `N/\\ 8 =\\= 0` prompt on call
    Therefore, `leash(15)` is equivalent to `leash(full)` and `leash(0)` is equivalent to `leash(off)`. Another way of using `leash` is to give it a list with the names of the ports where the debugger should stop. For example, `leash([call,exit,redo,fail])` is the same as `leash(full)` or `leash(15)` and `leash([fail])` might be used instead of `leash(1)`.
  • spy_write(+ _Stream_,Term) @anchor spy_write If defined by the user, this predicate will be used to print goals by the debugger instead of `write/2`.
  • trace @anchor trace Switches on the debugger and starts tracing.
  • notrace @anchor notrace Ends tracing and exits the debugger. This is the same as [nodebug/0](@ref nodebug).
@section Deb_Interaction Interacting with the debugger Debugging with YAP is similar to debugging with C-Prolog. Both systems include a procedural debugger, based on Byrd's four port model. In this model, execution is seen at the procedure level: each activation of a procedure is seen as a box with control flowing into and out of that box. In the four port model control is caught at four key points: before entering the procedure, after exiting the procedure (meaning successful evaluation of all queries activated by the procedure), after backtracking but before trying new alternative to the procedure and after failing the procedure. Each one of these points is named a port: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ @group *--------------------------------------* Call | | Exit ---------> + descendant(X,Y) :- offspring(X,Y). + ---------> | | | descendant(X,Z) :- | <--------- + offspring(X,Y), descendant(Y,Z). + <--------- Fail | | Redo *--------------------------------------* ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  • Call The call port is activated before initial invocation of procedure. Afterwards, execution will try to match the goal with the head of existing clauses for the procedure.
  • Exit This port is activated if the procedure succeeds. Control will now leave the procedure and return to its ancestor.
  • Redo if the goal, or goals, activated after the call port fail then backtracking will eventually return control to this procedure through the redo port.
  • Fail If all clauses for this predicate fail, then the invocation fails, and control will try to redo the ancestor of this invocation.
To start debugging, the user will either call `trace` or spy the relevant procedures, entering debug mode, and start execution of the program. When finding the first spy-point, YAP's debugger will take control and show a message of the form: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ * (1) call: quicksort([1,2,3],_38) ? ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ The debugger message will be shown while creeping, or at spy-points, and it includes four or five fields:
  • The first three characters are used to point out special states of the debugger. If the port is exit and the first character is '?', the current call is non-deterministic, that is, it still has alternatives to be tried. If the second character is a `\*`, execution is at a spy-point. If the third character is a `\>`, execution has returned either from a skip, a fail or a redo command.
  • The second field is the activation number, and uniquely identifies the activation. The number will start from 1 and will be incremented for each activation found by the debugger.
  • In the third field, the debugger shows the active port.
  • The fourth field is the goal. The goal is written by `write_term/3` on the standard error stream, using the options given by [debugger_print_options](@ref debugger_print_options).
If the active port is leashed, the debugger will prompt the user with a `?`, and wait for a command. A debugger command is just a character, followed by a return. By default, only the call and redo entries are leashed, but the [leash/1](@ref leash) predicate can be used in order to make the debugger stop where needed. There are several commands available, but the user only needs to remember the help command, which is `h`. This command shows all the available options, which are:
  • c - creep this command makes YAP continue execution and stop at the next leashed port.
  • return - creep the same as c
  • l - leap YAP will execute until it meets a port for a spied predicate; this mode keeps all computation history for debugging purposes, so it is more expensive than standard execution. Use k or z for fast execution.
  • k - quasi-leap similar to leap but faster since the computation history is not kept; useful when leap becomes too slow.
  • z - zip same as k
  • s - skip YAP will continue execution without showing any messages until returning to the current activation. Spy-points will be ignored in this mode. Note that this command keeps all debugging history, use t for fast execution. This command is meaningless, and therefore illegal, in the fail and exit ports.
  • t - fast-skip similar to skip but faster since computation history is not kept; useful if skip becomes slow.
  • f [ _GoalId_] - fail If given no argument, forces YAP to fail the goal, skipping the fail port and backtracking to the parent. If f receives a goal number as the argument, the command fails all the way to the goal. If goal _GoalId_ has completed execution, YAP fails until meeting the first active ancestor.
  • r [ _GoalId_] - retry This command forces YAP to jump back call to the port. Note that any side effects of the goal cannot be undone. This command is not available at the call port. If f receives a goal number as the argument, the command retries goal _GoalId_ instead. If goal _GoalId_ has completed execution, YAP fails until meeting the first active ancestor.
  • a - abort execution will be aborted, and the interpreter will return to the top-level. YAP disactivates debug mode, but spypoints are not removed.
  • n - nodebug stop debugging and continue execution. The command will not clear active spy-points.
  • e - exit leave YAP.
  • h - help show the debugger commands.
  • ! Query execute a query. YAP will not show the result of the query.
  • b - break break active execution and launch a break level. This is the same as `!break`.
  • + - spy this goal start spying the active goal. The same as `! spy G` where _G_ is the active goal.
  • - - nospy this goal stop spying the active goal. The same as `! nospy G` where _G_ is the active goal.
  • p - print shows the active goal using print/1
  • d - display shows the active goal using display/1
  • \
  • \< - full term resets to the default of ten the debugger's maximum write depth. For more information about `write_depth/2` ( (see [Input/Output Control](@ref InputOutput_Control))).
  • A - alternatives show the list of backtrack points in the current execution.
  • g [ _N_] show the list of ancestors in the current debugging environment. If it receives _N_, show the first _N_ ancestors.
The debugging information, when fast-skip `quasi-leap` is used, will be lost. @page Efficiency Efficiency Considerations We next discuss several issues on trying to make Prolog programs run fast in YAP. We assume two different programming styles:
  • Execution of deterministic programs often boils down to a recursive loop of the form: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ loop(Env) :- do_something(Env,NewEnv), loop(NewEnv). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
@section Indexing Indexing The indexation mechanism restricts the set of clauses to be tried in a procedure by using information about the status of the instantiated arguments of the goal. These arguments are then used as a key, selecting a restricted set of a clauses from all the clauses forming the procedure. As an example, the two clauses for concatenate: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ concatenate([],L,L). concatenate([H|T],A,[H|NT]) :- concatenate(T,A,NT). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ If the first argument for the goal is a list, then only the second clause is of interest. If the first argument is the nil atom, the system needs to look only for the first clause. The indexation generates instructions that test the value of the first argument, and then proceed to a selected clause, or group of clauses. Note that if the first argument was a free variable, then both clauses should be tried. In general, indexation will not be useful if the first argument is a free variable. When activating a predicate, a Prolog system needs to store state information. This information, stored in a structure known as choice point or fail point, is necessary when backtracking to other clauses for the predicate. The operations of creating and using a choice point are very expensive, both in the terms of space used and time spent. Creating a choice point is not necessary if there is only a clause for the predicate as there are no clauses to backtrack to. With indexation, this situation is extended: in the example, if the first argument was the atom nil, then only one clause would really be of interest, and it is pointless to create a choice point. This feature is even more useful if the first argument is a list: without indexation, execution would try the first clause, creating a choice point. The clause would fail, the choice point would then be used to restore the previous state of the computation and the second clause would be tried. The code generated by the indexation mechanism would behave much more efficiently: it would test the first argument and see whether it is a list, and then proceed directly to the second clause. An important side effect concerns the use of "cut". In the above example, some programmers would use a "cut" in the first clause just to inform the system that the predicate is not backtrackable and force the removal the choice point just created. As a result, less space is needed but with a great loss in expressive power: the "cut" would prevent some uses of the procedure, like generating lists through backtracking. Of course, with indexation the "cut" becomes useless: the choice point is not even created. Indexation is also very important for predicates with a large number of clauses that are used like tables: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ logician(aristoteles,greek). logician(frege,german). logician(russel,english). logician(godel,german). logician(whitehead,english). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ An interpreter like C-Prolog, trying to answer the query: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ?- logician(godel,X). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ would blindly follow the standard Prolog strategy, trying first the first clause, then the second, the third and finally finding the relevant clause. Also, as there are some more clauses after the important one, a choice point has to be created, even if we know the next clauses will certainly fail. A "cut" would be needed to prevent some possible uses for the procedure, like generating all logicians. In this situation, the indexing mechanism generates instructions that implement a search table. In this table, the value of the first argument would be used as a key for fast search of possibly matching clauses. For the query of the last example, the result of the search would be just the fourth clause, and again there would be no need for a choice point. If the first argument is a complex term, indexation will select clauses just by testing its main functor. However, there is an important exception: if the first argument of a clause is a list, the algorithm also uses the list's head if not a variable. For instance, with the following clauses, ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ rules([],B,B). rules([n(N)|T],I,O) :- rules_for_noun(N,I,N), rules(T,N,O). rules([v(V)|T],I,O) :- rules_for_verb(V,I,N), rules(T,N,O). rules([q(Q)|T],I,O) :- rules_for_qualifier(Q,I,N), rules(T,N,O). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ if the first argument of the goal is a list, its head will be tested, and only the clauses matching it will be tried during execution. Some advice on how to take a good advantage of this mechanism:
  • Try to make the first argument an input argument.
  • Try to keep together all clauses whose first argument is not a variable, that will decrease the number of tests since the other clauses are always tried.
  • Try to avoid predicates having a lot of clauses with the same key. For instance, the procedure:
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ type(n(mary),person). type(n(john), person). type(n(chair),object). type(v(eat),active). type(v(rest),passive). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ becomes more efficient with: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ type(n(N),T) :- type_of_noun(N,T). type(v(V),T) :- type_of_verb(V,T). type_of_noun(mary,person). type_of_noun(john,person). type_of_noun(chair,object). type_of_verb(eat,active). type_of_verb(rest,passive). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ @page ChYInterface C Language interface to YAP YAP provides the user with three facilities for writing predicates in a language other than Prolog. Under Unix systems, most language implementations were linkable to `C`, and the first interface exported the YAP machinery to the C language. YAP also implements most of the SWI-Prolog foreign language interface. This gives portability with a number of SWI-Prolog packages. Last, a new C++ based interface is being designed to work with the swig (@url(www.swig.org}) interface compiler.
  • The original YAP C-interface exports the YAP engine.
  • The @ref swi-c-interface emulates Jan Wielemaker's SWI foreign language interface.
  • The @ref yap-cplus-interface is desiged to interface with Object-Oriented systems.
Before describing in full detail how to interface to C code, we will examine a brief example. Assume the user requires a predicate `my_process_id(Id)` which succeeds when _Id_ unifies with the number of the process under which YAP is running. In this case we will create a `my_process.c` file containing the C-code described below. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~{.c} #include "YAP/YapInterface.h" static int my_process_id(void) { YAP_Term pid = YAP_MkIntTerm(getpid()); YAP_Term out = YAP_ARG1; return(YAP_Unify(out,pid)); } void init_my_predicates() { YAP_UserCPredicate("my_process_id",my_process_id,1); } ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ The commands to compile the above file depend on the operating system. Under Linux (i386 and Alpha) you should use: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ gcc -c -shared -fPIC my_process.c ld -shared -o my_process.so my_process.o ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Under WIN32 in a MINGW/CYGWIN environment, using the standard installation path you should use: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ gcc -mno-cygwin -I "c:/Yap/include" -c my_process.c gcc -mno-cygwin "c:/Yap/bin/yap.dll" --shared -o my_process.dll my_process.o ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Under WIN32 in a pure CYGWIN environment, using the standard installation path, you should use: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ gcc -I/usr/local -c my_process.c gcc -shared -o my_process.dll my_process.o /usr/local/bin/yap.dll ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Under Solaris2 it is sufficient to use: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ gcc -fPIC -c my_process.c ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Under SunOS it is sufficient to use: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ gcc -c my_process.c ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Under Digital Unix you need to create a `so` file. Use: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ gcc tst.c -c -fpic ld my_process.o -o my_process.so -shared -expect_unresolved '*' ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ and replace my `process.so` for my `process.o` in the remainder of the example. And could be loaded, under YAP, by executing the following Prolog goal ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ load_foreign_files(['my_process'],[],init_my_predicates). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Note that since YAP4.3.3 you should not give the suffix for object files. YAP will deduce the correct suffix from the operating system it is running under. After loading that file the following Prolog goal ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ my_process_id(N) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ would unify N with the number of the process under which YAP is running. Having presented a full example, we will now examine in more detail the contents of the C source code file presented above. The include statement is used to make available to the C source code the macros for the handling of Prolog terms and also some YAP public definitions. The function `my_process_id` is the implementation, in C, of the desired predicate. Note that it returns an integer denoting the success of failure of the goal and also that it has no arguments even though the predicate being defined has one. In fact the arguments of a Prolog predicate written in C are accessed through macros, defined in the include file, with names _YAP_ARG1_, _YAP_ARG2_, ..., _YAP_ARG16_ or with _YAP_A_( _N_) where _N_ is the argument number (starting with 1). In the present case the function uses just one local variable of type `YAP_Term`, the type used for holding YAP terms, where the integer returned by the standard unix function `getpid()` is stored as an integer term (the conversion is done by `YAP_MkIntTerm(Int))`. Then it calls the pre-defined routine `YAP_Unify(YAP_Term, YAP_Term)` which in turn returns an integer denoting success or failure of the unification. The role of the procedure `init_my_predicates` is to make known to YAP, by calling [YAP_UserCPredicate](@ref YAP_UserCPredicate), the predicates being defined in the file. This is in fact why, in the example above, `init_my_predicates` was passed as the third argument to `load_foreign_files/3`. The rest of this appendix describes exhaustively how to interface C to YAP. @section Manipulating_Terms Terms This section provides information about the primitives available to the C programmer for manipulating Prolog terms. Several C typedefs are included in the header file `yap/YAPInterface.h` to describe, in a portable way, the C representation of Prolog terms. The user should write is programs using this macros to ensure portability of code across different versions of YAP. The more important typedef is _YAP_Term_ which is used to denote the type of a Prolog term. Terms, from a point of view of the C-programmer, can be classified as follows
  • uninstantiated variables
  • instantiated variables
  • integers
  • floating-point numbers
  • database references
  • atoms
  • pairs (lists)
  • compound terms
The primitive
  • YAP_Bool YAP_IsVarTerm(YAP_Term _t_) @anchor YAP_IsVarTerm returns true iff its argument is an uninstantiated variable. Conversely the primitive
  • YAP_Bool YAP_NonVarTerm(YAP_Term _t_) @anchor YAP_IsNonVarTerm returns true iff its argument is not a variable.
The user can create a new uninstantiated variable using the primitive
  • YAP_Term YAP_MkVarTerm()
The following primitives can be used to discriminate among the different types of non-variable terms:
  • YAP_Bool YAP_IsIntTerm(YAP_Term _t_) @anchor YAP_IsIntTerm
  • YAP_Bool YAP_IsFloatTerm(YAP_Term _t_) @anchor YAP_IsFloatTerm
  • YAP_Bool YAP_IsDbRefTerm(YAP_Term _t_) @anchor YAP_IsDBRefTerm
  • YAP_Bool YAP_IsAtomTerm(YAP_Term _t_) @anchor YAP_IsAtomTerm
  • YAP_Bool YAP_IsPairTerm(YAP_Term _t_) @anchor YAP_IsPairTerm
  • YAP_Bool YAP_IsApplTerm(YAP_Term _t_) @anchor YAP_IsApplTerm
  • YAP_Bool YAP_IsCompoundTerm(YAP_Term _t_) @anchor YAP_IsCompoundTerm
The next primitive gives the type of a Prolog term:
  • YAP_tag_t YAP_TagOfTerm(YAP_Term _t_)
The set of possible values is an enumerated type, with the following values:
  • `YAP_TAG_ATT`: an attributed variable
  • `YAP_TAG_UNBOUND`: an unbound variable
  • `YAP_TAG_REF`: a reference to a term
  • `YAP_TAG_PAIR`: a list
  • `YAP_TAG_ATOM`: an atom
  • `YAP_TAG_INT`: a small integer
  • `YAP_TAG_LONG_INT`: a word sized integer
  • `YAP_TAG_BIG_INT`: a very large integer
  • `YAP_TAG_RATIONAL`: a rational number
  • `YAP_TAG_FLOAT`: a floating point number
  • `YAP_TAG_OPAQUE`: an opaque term
  • `YAP_TAG_APPL`: a compound term
Next, we mention the primitives that allow one to destruct and construct terms. All the above primitives ensure that their result is \a dereferenced, i.e. that it is not a pointer to another term. The following primitives are provided for creating an integer term from an integer and to access the value of an integer term.
  • YAP_Term YAP_MkIntTerm(YAP_Int _i_) @anchor YAP_MkIntTerm
  • YAP_Int YAP_IntOfTerm(YAP_Term _t_) @anchor YAP_IntOfTerm
where `YAP_Int` is a typedef for the C integer type appropriate for the machine or compiler in question (normally a long integer). The size of the allowed integers is implementation dependent but is always greater or equal to 24 bits: usually 32 bits on 32 bit machines, and 64 on 64 bit machines. The two following primitives play a similar role for floating-point terms
  • YAP_Term YAP_MkFloatTerm(YAP_flt _double_) @anchor YAP_MkFloatTerm
  • YAP_flt YAP_FloatOfTerm(YAP_Term _t_) @anchor YAP_FloatOfTerm
where `flt` is a typedef for the appropriate C floating point type, nowadays a `double` The following primitives are provided for verifying whether a term is a big int, creating a term from a big integer and to access the value of a big int from a term.
  • YAP_Bool YAP_IsBigNumTerm(YAP_Term _t_) @anchor YAP_IsBigNumTerm
  • YAP_Term YAP_MkBigNumTerm(void \* _b_) @anchor YAP_MkBigNumTerm
  • void \*YAP_BigNumOfTerm(YAP_Term _t_, void \* _b_) @anchor YAP_BigNumOfTerm
YAP must support bignum for the configuration you are using (check the YAP configuration and setup). For now, YAP only supports the GNU GMP library, and `void \*` will be a cast for `mpz_t`. Notice that [YAP_BigNumOfTerm](@ref YAP_BigNumOfTerm) requires the number to be already initialised. As an example, we show how to print a bignum: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ static int p_print_bignum(void) { mpz_t mz; if (!YAP_IsBigNumTerm(YAP_ARG1)) return FALSE; mpz_init(mz); YAP_BigNumOfTerm(YAP_ARG1, mz); gmp_printf("Shows up as %Zd\n", mz); mpz_clear(mz); return TRUE; } ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Currently, no primitives are supplied to users for manipulating data base references. A special typedef `YAP_Atom` is provided to describe Prolog \a atoms (symbolic constants). The two following primitives can be used to manipulate atom terms
  • YAP_Term YAP_MkAtomTerm(YAP_Atom at) @anchor YAP_MkAtomTerm
  • YAP_Atom YAP_AtomOfTerm(YAP_Term _t_) @anchor YAP_AtomOfTerm
The following primitives are available for associating atoms with their names
  • YAP_Atom YAP_LookupAtom(char \* _s_) @anchor YAP_LookupAtom
  • YAP_Atom YAP_FullLookupAtom(char \* _s_) @anchor YAP_FullLookupAtom
  • char \*YAP_AtomName(YAP_Atom _t_) @anchor YAP_AtomName
The function [YAP_LookupAtom](@ref YAP_LookupAtom) looks up an atom in the standard hash table. The function [YAP_FullLookupAtom](@ref YAP_FullLookupAtom) will also search if the atom had been "hidden": this is useful for system maintenance from C code. The functor [YAP_AtomName](@ref YAP_AtomName) returns a pointer to the string for the atom. The following primitives handle constructing atoms from strings with wide characters, and vice-versa:
  • YAP_Atom YAP_LookupWideAtom(wchar_t \* _s_) @anchor YAP_LookupWideAtom
  • wchar_t \*YAP_WideAtomName(YAP_Atom _t_) @anchor YAP_WideAtomName
The following primitive tells whether an atom needs wide atoms in its representation:
  • int YAP_IsWideAtom(YAP_Atom _t_) @anchor YAP_IsIsWideAtom
The following primitive can be used to obtain the size of an atom in a representation-independent way:
  • int YAP_AtomNameLength(YAP_Atom _t_) @anchor YAP_AtomNameLength
The next routines give users some control over the atom garbage collector. They allow the user to guarantee that an atom is not to be garbage collected (this is important if the atom is hold externally to the Prolog engine, allow it to be collected, and call a hook on garbage collection:
  • int YAP_AtomGetHold(YAP_Atom _at_) @anchor YAP_AtomGetHold
  • int YAP_AtomReleaseHold(YAP_Atom _at_) @anchor YAP_AtomReleaseHold
  • int YAP_AGCRegisterHook(YAP_AGC_hook _f_) @anchor YAP_AGCHook
A \a pair is a Prolog term which consists of a tuple of two Prolog terms designated as the \a head and the \a tail of the term. Pairs are most often used to build lists. The following primitives can be used to manipulate pairs:
  • YAP_Term YAP_MkPairTerm(YAP_Term _Head_, YAP_Term _Tail_) @anchor YAP_MkPairTerm
  • YAP_Term YAP_MkNewPairTerm(void) @anchor YAP_MkNewPairTerm
  • YAP_Term YAP_HeadOfTerm(YAP_Term _t_) @anchor YAP_HeadOfTerm
  • YAP_Term YAP_TailOfTerm(YAP_Term _t_) @anchor YAP_TailOfTerm
  • YAP_Term YAP_MkListFromTerms(YAP_Term \* _pt_, YAP_Int \* _sz_) @anchor YAP_MkListFromTerms
One can construct a new pair from two terms, or one can just build a pair whose head and tail are new unbound variables. Finally, one can fetch the head or the tail. The last function supports the common operation of constructing a list from an array of terms of size _sz_ in a simple sweep. Notice that the list constructors can call the garbage collector if there is not enough space in the global stack. A \a compound term consists of a \a functor and a sequence of terms with length equal to the \a arity of the functor. A functor, described in C by the typedef `Functor`, consists of an atom and of an integer. The following primitives were designed to manipulate compound terms and functors
  • YAP_Term YAP_MkApplTerm(YAP_Functor _f_, unsigned long int _n_, YAP_Term[] _args_) @anchor YAP_MkApplTerm
  • YAP_Term YAP_MkNewApplTerm(YAP_Functor _f_, int _n_) @anchor YAP_MkNewApplTerm
  • YAP_Term YAP_ArgOfTerm(int argno,YAP_Term _ts_) @anchor YAP_ArgOfTerm
  • YAP_Term \*YAP_ArgsOfTerm(YAP_Term _ts_) @anchor YAP_ArgsOfTerm
  • YAP_Functor YAP_FunctorOfTerm(YAP_Term _ts_) @anchor YAP_FunctorOfTerm
The [YAP_MkApplTerm](@ref YAP_MkApplTerm) function constructs a new term, with functor _f_ (of arity _n_), and using an array _args_ of _n_ terms with _n_ equal to the arity of the functor. [YAP_MkNewApplTerm](@ref YAP_MkNewApplTerm) builds up a compound term whose arguments are unbound variables. [YAP_ArgOfTerm](@ref YAP_ArgOfTerm) gives an argument to a compound term. `argno` should be greater or equal to 1 and less or equal to the arity of the functor. [YAP_ArgsOfTerm](@ref YAP_ArgsOfTerm) returns a pointer to an array of arguments. Notice that the compound term constructors can call the garbage collector if there is not enough space in the global stack. YAP allows one to manipulate the functors of compound term. The function [YAP_FunctorOfTerm](@ref YAP_FunctorOfTerm) allows one to obtain a variable of type `YAP_Functor` with the functor to a term. The following functions then allow one to construct functors, and to obtain their name and arity.
  • YAP_Functor YAP_MkFunctor(YAP_Atom _a_,unsigned long int _arity_)
  • YAP_Atom YAP_NameOfFunctor(YAP_Functor _f_)
  • YAP_Int YAP_ArityOfFunctor(YAP_Functor _f_)
Note that the functor is essentially a pair formed by an atom, and arity. Constructing terms in the stack may lead to overflow. The routine
  • int YAP_RequiresExtraStack(size_t _min_) @anchor YAP_Unify
verifies whether you have at least _min_ cells free in the stack, and it returns true if it has to ensure enough memory by calling the garbage collector and or stack shifter. The routine returns false if no memory is needed, and a negative number if it cannot provide enough memory. You can set _min_ to zero if you do not know how much room you need but you do know you do not need a big chunk at a single go. Usually, the routine would usually be called together with a long-jump to restart the code. Slots can also be used if there is small state. @section Unifying_Terms Unification YAP provides a single routine to attempt the unification of two Prolog terms. The routine may succeed or fail:
  • Int YAP_Unify(YAP_Term _a_, YAP_Term _b_) @anchor YAP_StringToBuffer
The routine attempts to unify the terms _a_ and _b_ returning `TRUE` if the unification succeeds and `FALSE` otherwise. @section Manipulating_Strings Strings The YAP C-interface now includes an utility routine to copy a string represented as a list of a character codes to a previously allocated buffer
  • int YAP_StringToBuffer(YAP_Term _String_, char \* _buf_, unsigned int _bufsize_) @anchor YAP_BufferToString
The routine copies the list of character codes _String_ to a previously allocated buffer _buf_. The string including a terminating null character must fit in _bufsize_ characters, otherwise the routine will simply fail. The _StringToBuffer_ routine fails and generates an exception if _String_ is not a valid string. The C-interface also includes utility routines to do the reverse, that is, to copy a from a buffer to a list of character codes, to a difference list, or to a list of character atoms. The routines work either on strings of characters or strings of wide characters:
  • YAP_Term YAP_BufferToString(char \* _buf_)
  • YAP_Term YAP_NBufferToString(char \* _buf_, size_t _len_)
  • YAP_Term YAP_WideBufferToString(wchar_t \* _buf_)
  • YAP_Term YAP_NWideBufferToString(wchar_t \* _buf_, size_t _len_)
  • YAP_Term YAP_BufferToAtomList(char \* _buf_)
  • YAP_Term YAP_NBufferToAtomList(char \* _buf_, size_t _len_)
  • YAP_Term YAP_WideBufferToAtomList(wchar_t \* _buf_)
  • YAP_Term YAP_NWideBufferToAtomList(wchar_t \* _buf_, size_t _len_) @anchor YAP_ReadBuffer
Users are advised to use the _N_ version of the routines. Otherwise, the user-provided string must include a terminating null character. The C-interface function calls the parser on a sequence of characters stored at _buf_ and returns the resulting term.
  • YAP_Term YAP_ReadBuffer(char \* _buf_,YAP_Term \* _error_) @anchor YAP_IntsToList
The user-provided string must include a terminating null character. Syntax errors will cause returning `FALSE` and binding _error_ to a Prolog term. These C-interface functions are useful when converting chunks of data to Prolog:
  • YAP_Term YAP_FloatsToList(double \* _buf_,size_t _sz_)
  • YAP_Term YAP_IntsToList(YAP_Int \* _buf_,size_t _sz_) @anchor YAP_ListToInts
Notice that they are unsafe, and may call the garbage collector. They return 0 on error. These C-interface functions are useful when converting Prolog lists to arrays:
  • YAP_Int YAP_IntsToList(YAP_Term t, YAP_Int \* _buf_,size_t _sz_)
  • YAP_Int YAP_FloatsToList(YAP_Term t, double \* _buf_,size_t _sz_) @anchor YAP_AllocSpaceFromYAP
They return the number of integers scanned, up to a maximum of sz, and -1 on error. @section Memory_Allocation Memory Allocation The next routine can be used to ask space from the Prolog data-base:
  • void \*YAP_AllocSpaceFromYAP(int _size_) @anchor YAP_FreeSpaceFromYAP
The routine returns a pointer to a buffer allocated from the code area, or `NULL` if sufficient space was not available. The space allocated with [YAP_AllocSpaceFromYAP](@ref YAP_AllocSpaceFromYAP) can be released back to YAP by using:
  • void YAP_FreeSpaceFromYAP(void \* _buf_) @anchor YAP_StreamToFileNo
The routine releases a buffer allocated from the code area. The system may crash if `buf` is not a valid pointer to a buffer in the code area. @section Controlling_Streams Controlling YAP Streams from `C` The C-Interface also provides the C-application with a measure of control over the YAP Input/Output system. The first routine allows one to find a file number given a current stream:
  • int YAP_StreamToFileNo(YAP_Term _stream_) @anchor YAP_CloseAllOpenStreams
This function gives the file descriptor for a currently available stream. Note that null streams and in memory streams do not have corresponding open streams, so the routine will return a negative. Moreover, YAP will not be aware of any direct operations on this stream, so information on, say, current stream position, may become stale. A second routine that is sometimes useful is:
  • void YAP_CloseAllOpenStreams(void) @anchor YAP_FlushAllStreams
This routine closes the YAP Input/Output system except for the first three streams, that are always associated with the three standard Unix streams. It is most useful if you are doing `fork()`. Last, one may sometimes need to flush all streams:
  • void YAP_CloseAllOpenStreams(void) @anchor YAP_OpenStream
It is also useful before you do a `fork()`, or otherwise you may have trouble with unflushed output. The next routine allows a currently open file to become a stream. The routine receives as arguments a file descriptor, the true file name as a string, an atom with the user name, and a set of flags:
  • void YAP_OpenStream(void \* _FD_, char \* _name_, YAP_Term _t_, int _flags_) @anchor YAP_Record
The available flags are `YAP_INPUT_STREAM`, `YAP_OUTPUT_STREAM`, `YAP_APPEND_STREAM`, `YAP_PIPE_STREAM`, `YAP_TTY_STREAM`, `YAP_POPEN_STREAM`, `YAP_BINARY_STREAM`, and `YAP_SEEKABLE_STREAM`. By default, the stream is supposed to be at position 0. The argument _name_ gives the name by which YAP should know the new stream. @section Utility_Functions Utility Functions in `C` The C-Interface provides the C-application with a a number of utility functions that are useful. The first provides a way to insert a term into the data-base
  • void \*YAP_Record(YAP_Term _t_) @anchor YAP_Recorded
This function returns a pointer to a copy of the term in the database (or to NULL if the operation fails. The next functions provides a way to recover the term from the data-base:
  • YAP_Term YAP_Recorded(void \* _handle_) @anchor YAP_Erase
Notice that the semantics are the same as for [recorded/3](@ref recorded): this function creates a new copy of the term in the stack, with fresh variables. The function returns 0L if it cannot create a new term. Last, the next function allows one to recover space:
  • int YAP_Erase(void \* _handle_) @anchor YAP_ExactlyEqual
Notice that any accesses using _handle_ after this operation may lead to a crash. The following functions are often required to compare terms. Succeed if two terms are actually the same term, as in [==/2](@ref qQqQ):
  • int YAP_ExactlyEqual(YAP_Term t1, YAP_Term t2)
The next function succeeds if two terms are variant terms, and returns 0 otherwise, as [=@=/2](@ref qQaAqQ):
  • int YAP_Variant(YAP_Term t1, YAP_Term t2)
The next functions deal with numbering variables in terms:
  • int YAP_NumberVars(YAP_Term t, YAP_Int first_number)
  • YAP_Term YAP_UnNumberVars(YAP_Term t)
  • int YAP_IsNumberedVariable(YAP_Term t)
The next one returns the length of a well-formed list _t_, or `-1` otherwise:
  • Int YAP_ListLength(YAP_Term t)
Last, this function succeeds if two terms are unifiable: [=@=/2](@ref qQaAqQ):
  • int YAP_Unifiable(YAP_Term t1, YAP_Term t2)
The second function computes a hash function for a term, as in `term_hash/4`.
  • YAP_Int YAP_TermHash(YAP_Term t, YAP_Int range, YAP_Int depth, int ignore_variables)); @anchor YAP_RunGoal
The first three arguments follow `term_has/4`. The last argument indicates what to do if we find a variable: if `0` fail, otherwise ignore the variable. @section Calling_YAP_From_C From `C` back to Prolog There are several ways to call Prolog code from C-code. By default, the `YAP_RunGoal()` should be used for this task. It assumes the engine has been initialised before:
  • YAP_Int YAP_RunGoal(YAP_Term Goal)
Execute query _Goal_ and return 1 if the query succeeds, and 0 otherwise. The predicate returns 0 if failure, otherwise it will return an _YAP_Term_. Quite often, one wants to run a query once. In this case you should use _Goal_:
  • YAP_Int YAP_RunGoalOnce(YAP_Term Goal)
The `YAP_RunGoal()` function makes sure to recover stack space at the end of execution. Prolog terms are pointers: a problem users often find is that the term _Goal_ may actually be moved around during the execution of `YAP_RunGoal()`, due to garbage collection or stack shifting. If this is possible, _Goal_ will become invalid after executing `YAP_RunGoal()`. In this case, it is a good idea to save _Goal_ slots, as shown next: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ long sl = YAP_InitSlot(scoreTerm); out = YAP_RunGoal(t); t = YAP_GetFromSlot(sl); YAP_RecoverSlots(1); if (out == 0) return FALSE; ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ @copydoc real The following functions complement _YAP_RunGoal_:
  • `int` YAP_RestartGoal(`void`) @anchor YAP_RestartGoal Look for the next solution to the current query by forcing YAP to backtrack to the latest goal. Notice that slots allocated since the last [YAP_RunGoal](@ref YAP_RunGoal) will become invalid. @Item `int` YAP_Reset(`void`) Reset execution environment (similar to the [abort/0](@ref abort) built-in). This is useful when you want to start a new query before asking all solutions to the previous query.
  • `int` YAP_ShutdownGoal(`int backtrack`) @anchor YAP_ShutdownGoal Clean up the current goal. If `backtrack` is true, stack space will be recovered and bindings will be undone. In both cases, any slots allocated since the goal was created will become invalid.
  • `YAP_Bool` YAP_GoalHasException(`YAP_Term \*tp`) @anchor YAP_GoalHasException Check if the last goal generated an exception, and if so copy it to the space pointed to by _tp_
  • `void` YAP_ClearExceptions(`void`) @anchor YAP_ClearExceptions Reset any exceptions left over by the system.
The _YAP_RunGoal_ interface is designed to be very robust, but may not be the most efficient when repeated calls to the same goal are made and when there is no interest in processing exception. The _YAP_EnterGoal_ interface should have lower-overhead:
  • `YAP_PredEntryPtr` YAP_FunctorToPred(`YAP_Functor` _f_, @anchor YAP_FunctorToPred Return the predicate whose main functor is _f_.
  • `YAP_PredEntryPtr` YAP_AtomToPred(`YAP_Atom` _at_ @anchor YAP_AtomToPred Return the arity 0 predicate whose name is _at_.
  • `YAP_PredEntryPtr` @anchor YAP_FunctorToPredInModule YAP_FunctorToPredInModule(`YAP_Functor` _f_, `YAP_Module` _m_), Return the predicate in module _m_ whose main functor is _f_.
  • `YAP_PredEntryPtr` YAP_AtomToPred(`YAP_Atom` _at_, `YAP_Module` _m_), @anchor YAP_AtomToPredInModule Return the arity 0 predicate in module _m_ whose name is _at_.
  • `YAP_Bool` YAP_EnterGoal(`YAP_PredEntryPtr` _pe_, @anchor YAP_EnterGoal `YAP_Term \*` _array_, `YAP_dogoalinfo \*` _infop_) Execute a query for predicate _pe_. The query is given as an array of terms _Array_. _infop_ is the address of a goal handle that can be used to backtrack and to recover space. Succeeds if a solution was found. Notice that you cannot create new slots if an YAP_EnterGoal goal is open.
  • `YAP_Bool` YAP_RetryGoal(`YAP_dogoalinfo \*` _infop_) @anchor YAP_RetryGoal Backtrack to a query created by [YAP_EnterGoal](@ref YAP_EnterGoal). The query is given by the handle _infop_. Returns whether a new solution could be be found.
  • `YAP_Bool` YAP_LeaveGoal(`YAP_Bool` _backtrack_, @anchor YAP_LeaveGoal `YAP_dogoalinfo \*` _infop_) Exit a query query created by [YAP_EnterGoal](@ref YAP_EnterGoal). If `backtrack` is `TRUE`, variable bindings are undone and Heap space is recovered. Otherwise, only stack space is recovered, ie, `LeaveGoal` executes a cut.
Next, follows an example of how to use [YAP_EnterGoal](@ref YAP_EnterGoal): ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ void runall(YAP_Term g) { YAP_dogoalinfo goalInfo; YAP_Term *goalArgs = YAP_ArraysOfTerm(g); YAP_Functor *goalFunctor = YAP_FunctorOfTerm(g); YAP_PredEntryPtr goalPred = YAP_FunctorToPred(goalFunctor); result = YAP_EnterGoal( goalPred, goalArgs, &goalInfo ); while (result) result = YAP_RetryGoal( &goalInfo ); YAP_LeaveGoal(TRUE, &goalInfo); } ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ YAP allows calling a *new* Prolog interpreter from `C`. One way is to first construct a goal `G`, and then it is sufficient to perform:
  • YAP_Bool YAP_CallProlog(YAP_Term _G_)
the result will be `FALSE`, if the goal failed, or `TRUE`, if the goal succeeded. In this case, the variables in _G_ will store the values they have been unified with. Execution only proceeds until finding the first solution to the goal, but you can call [findall/3](@ref findall) or friends if you need all the solutions. Notice that during execution, garbage collection or stack shifting may have moved the terms @section Module_Manipulation_in_C Module Manipulation in C YAP allows one to create a new module from C-code. To create the new code it is sufficient to call:
  • YAP_Module YAP_CreateModule(YAP_Atom _ModuleName_)
Notice that the new module does not have any predicates associated and that it is not the current module. To find the current module, you can call:
  • YAP_Module YAP_CurrentModule()
Given a module, you may want to obtain the corresponding name. This is possible by using:
  • YAP_Term YAP_ModuleName(YAP_Module mod)
Notice that this function returns a term, and not an atom. You can [YAP_AtomOfTerm](@ref YAP_AtomOfTerm) to extract the corresponding Prolog atom. @section Miscellaneous_ChYFunctions Miscellaneous C Functions
  • `void` YAP_Throw(`YAP_Term exception`)
  • `void` YAP_AsyncThrow(`YAP_Term exception`) @anchor YAP_Throw Throw an exception with term _exception_, just like if you called `throw/2`. The function YAP_AsyncThrow is supposed to be used from interrupt handlers.
  • `int` YAP_SetYAPFlag(`yap_flag_t flag, int value`) @anchor YAP_SetYAPFlag This function allows setting some YAP flags from `C` .Currently, only two boolean flags are accepted: `YAPC_ENABLE_GC` and `YAPC_ENABLE_AGC`. The first enables/disables the standard garbage collector, the second does the same for the atom garbage collector.`
  • `YAP_TERM` YAP_AllocExternalDataInStack(`size_t bytes`)
  • `void \*` YAP_ExternalDataInStackFromTerm(`YAP_Term t`)
  • `YAP_Bool` YAP_IsExternalDataInStackTerm(`YAP_Term t`) @anchor YAP_AllocExternalDataInStack The next routines allow one to store external data in the Prolog execution stack. The first routine reserves space for _sz_ bytes and returns an opaque handle. The second routines receives the handle and returns a pointer to the data. The last routine checks if a term is an opaque handle. Data will be automatically reclaimed during backtracking. Also, this storage is opaque to the Prolog garbage compiler, so it should not be used to store Prolog terms. On the other hand, it may be useful to store arrays in a compact way, or pointers to external objects.
  • `int` YAP_HaltRegisterHook(`YAP_halt_hook f, void \*closure`) @anchor YAP_HaltRegisterHook Register the function _f_ to be called if YAP is halted. The function is called with two arguments: the exit code of the process (`0` if this cannot be determined on your operating system) and the closure argument _closure_.
  • `int` YAP_Argv(`char \*\*\*argvp`) @anchor YAP_Argv Return the number of arguments to YAP and instantiate argvp to point to the list of such arguments.
@section Writing_C Writing predicates in C We will distinguish two kinds of predicates:
  • \a deterministic predicates which either fail or succeed but are not backtrackable, like the one in the introduction;
  • \a backtrackable predicates which can succeed more than once.
The first kind of predicates should be implemented as a C function with no arguments which should return zero if the predicate fails and a non-zero value otherwise. The predicate should be declared to YAP, in the initialization routine, with a call to
  • void YAP_UserCPredicate(char \* _name_, YAP_Bool \* _fn_(), unsigned long int _arity_); where _name_ is a string with the name of the predicate, _init_, _cont_, _cut_ are the C functions used to start, continue and when pruning the execution of the predicate, _arity_ is the predicate arity, and _sizeof_ is the size of the data to be preserved in the stack. For the second kind of predicates we need three C functions. The first one is called when the predicate is first activated; the second one is called on backtracking to provide (possibly) other solutions; the last one is called on pruning. Note also that we normally also need to preserve some information to find out the next solution. In fact the role of the two functions can be better understood from the following Prolog definition ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ p :- start. p :- repeat, continue. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ where `start` and `continue` correspond to the two C functions described above. The interface works as follows:
    • void YAP_UserBackCutCPredicate(char \* _name_, int \* _init_(), int \* _cont_(), int \* _cut_(), unsigned long int _arity_, unsigned int _sizeof_) @anchor YAP_UserBackCutCPredicate describes a new predicate where _name_ is the name of the predicate, _init_, _cont_, and _cut_ are the C functions that implement the predicate and _arity_ is the predicate's arity.
    • void YAP_UserBackCPredicate(char \* _name_, int \* _init_(), int \* _cont_(), unsigned long int _arity_, unsigned int _sizeof_) @anchor YAP_UserBackCPredicate describes a new predicate where _name_ is the name of the predicate, _init_, and _cont_ are the C functions that implement the predicate and _arity_ is the predicate's arity.
    • void YAP_PRESERVE_DATA( _ptr_, _type_); @anchor YAP_PRESERVE_DATA
    • void YAP_PRESERVED_DATA( _ptr_, _type_); @anchor YAP_PRESERVED_DATA
    • void YAP_PRESERVED_DATA_CUT( _ptr_, _type_); @anchor YAP_PRESERVED_DATA_CUT
    • void YAP_cut_succeed( void ); @anchor YAP_cut_succeed
    • void YAP_cut_fail( void ); @anchor YAP_cut_fail
    As an example we will consider implementing in C a predicate `n100(N)` which, when called with an instantiated argument should succeed if that argument is a numeral less or equal to 100, and, when called with an uninstantiated argument, should provide, by backtracking, all the positive integers less or equal to 100. To do that we first declare a structure, which can only consist of Prolog terms, containing the information to be preserved on backtracking and a pointer variable to a structure of that type. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ #include "YAPInterface.h" static int start_n100(void); static int continue_n100(void); typedef struct { YAP_Term next_solution; } n100_data_type; n100_data_type *n100_data; ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ We now write the `C` function to handle the first call: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ static int start_n100(void) { YAP_Term t = YAP_ARG1; YAP_PRESERVE_DATA(n100_data,n100_data_type); if(YAP_IsVarTerm(t)) { n100_data->next_solution = YAP_MkIntTerm(0); return continue_n100(); } if(!YAP_IsIntTerm(t) || YAP_IntOfTerm(t)<0 || YAP_IntOfTerm(t)>100) { YAP_cut_fail(); } else { YAP_cut_succeed(); } } ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ The routine starts by getting the dereference value of the argument. The call to [YAP_PRESERVE_DATA](@ref YAP_PRESERVE_DATA) is used to initialize the memory which will hold the information to be preserved across backtracking. The first argument is the variable we shall use, and the second its type. Note that we can only use [YAP_PRESERVE_DATA](@ref YAP_PRESERVE_DATA) once, so often we will want the variable to be a structure. This data is visible to the garbage collector, so it should consist of Prolog terms, as in the example. It is also correct to store pointers to objects external to YAP stacks, as the garbage collector will ignore such references. If the argument of the predicate is a variable, the routine initializes the structure to be preserved across backtracking with the information required to provide the next solution, and exits by calling `continue_n100` to provide that solution. If the argument was not a variable, the routine then checks if it was an integer, and if so, if its value is positive and less than 100. In that case it exits, denoting success, with [YAP_cut_succeed](@ref YAP_cut_succeed), or otherwise exits with [YAP_cut_fail](@ref YAP_cut_fail) denoting failure. The reason for using for using the functions [YAP_cut_succeed](@ref YAP_cut_succeed) and [YAP_cut_fail](@ref YAP_cut_fail) instead of just returning a non-zero value in the first case, and zero in the second case, is that otherwise, if backtracking occurred later, the routine `continue_n100` would be called to provide additional solutions. The code required for the second function is ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ static int continue_n100(void) { int n; YAP_Term t; YAP_Term sol = YAP_ARG1; YAP_PRESERVED_DATA(n100_data,n100_data_type); n = YAP_IntOfTerm(n100_data->next_solution); if( n == 100) { t = YAP_MkIntTerm(n); YAP_Unify(sol,t); YAP_cut_succeed(); } else { YAP_Unify(sol,n100_data->next_solution); n100_data->next_solution = YAP_MkIntTerm(n+1); return(TRUE); } } ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Note that again the macro [YAP_PRESERVED_DATA](@ref YAP_PRESERVED_DATA) is used at the beginning of the function to access the data preserved from the previous solution. Then it checks if the last solution was found and in that case exits with [YAP_cut_succeed](@ref YAP_cut_succeed) in order to cut any further backtracking. If this is not the last solution then we save the value for the next solution in the data structure and exit normally with 1 denoting success. Note also that in any of the two cases we use the function `YAP_unify` to bind the argument of the call to the value saved in ` n100_state-\>next_solution`. Note also that the only correct way to signal failure in a backtrackable predicate is to use the [YAP_cut_fail](@ref YAP_cut_fail) macro. Backtrackable predicates should be declared to YAP, in a way similar to what happened with deterministic ones, but using instead a call to ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ In this example, we would have something like ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ void init_n100(void) { YAP_UserBackCutCPredicate("n100", start_n100, continue_n100, cut_n100, 1, 1); } ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ The argument before last is the predicate's arity. Notice again the last argument to the call. function argument gives the extra space we want to use for `PRESERVED_DATA`. Space is given in cells, where a cell is the same size as a pointer. The garbage collector has access to this space, hence users should use it either to store terms or to store pointers to objects outside the stacks. The code for `cut_n100` could be: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ static int cut_n100(void) { YAP_PRESERVED_DATA_CUT(n100_data,n100_data_type*); fprintf("n100 cut with counter %ld\n", YAP_IntOfTerm(n100_data->next_solution)); return TRUE; } ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Notice that we have to use [YAP_PRESERVED_DATA_CUT](@ref YAP_PRESERVED_DATA_CUT): this is because the Prolog engine is at a different state during cut. If no work is required at cut, we can use: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ void init_n100(void) { YAP_UserBackCutCPredicate("n100", start_n100, continue_n100, NULL, 1, 1); } ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ in this case no code is executed at cut time. @section Loading_Objects Loading Object Files The primitive predicate
    • load_foreign_files( _Files_, _Libs_, _InitRoutine_)
    should be used, from inside YAP, to load object files produced by the C compiler. The argument _ObjectFiles_ should be a list of atoms specifying the object files to load, _Libs_ is a list (possibly empty) of libraries to be passed to the unix loader (`ld`) and InitRoutine is the name of the C routine (to be called after the files are loaded) to perform the necessary declarations to YAP of the predicates defined in the files. YAP will search for _ObjectFiles_ in the current directory first. If it cannot find them it will search for the files using the environment variable:
    • YAPLIBDIR
    if defined, or in the default library. YAP also supports the SWI-Prolog interface to loading foreign code:
    • open_shared_object(+ _File_, - _Handle_) File is the name of a shared object file (called dynamic load library in MS-Windows). This file is attached to the current process and _Handle_ is unified with a handle to the library. Equivalent to `open_shared_object(File, [], Handle)`. See also [load_foreign_library/1](@ref load_foreign_library) and `load_foreign_library/2`. On errors, an exception `shared_object`( _Action_, _Message_) is raised. _Message_ is the return value from dlerror().
    • open_shared_object(+ _File_, - _Handle_, + _Options_) As `open_shared_object/2`, but allows for additional flags to be passed. _Options_ is a list of atoms. `now` implies the symbols are resolved immediately rather than lazily (default). `global` implies symbols of the loaded object are visible while loading other shared objects (by default they are local). Note that these flags may not be supported by your operating system. Check the documentation of `dlopen()` or equivalent on your operating system. Unsupported flags are silently ignored.
    • close_shared_object(+ _Handle_) @anchor close_shared_object Detach the shared object identified by _Handle_.
    • call_shared_object_function(+ _Handle_, + _Function_) @anchor call_shared_object_function Call the named function in the loaded shared library. The function is called without arguments and the return-value is ignored. In SWI-Prolog, normally this function installs foreign language predicates using calls to `PL_register_foreign()`.
    @section SavebQeERest Saving and Restoring YAP4 currently does not support `save` and `restore` for object code loaded with `load_foreign_files/3`. We plan to support save and restore in future releases of YAP. @section YAP4_Notes Changes to the C-Interface in YAP4 YAP4 includes several changes over the previous `load_foreign_files/3` interface. These changes were required to support the new binary code formats, such as ELF used in Solaris2 and Linux.
    • All Names of YAP objects now start with _YAP__. This is designed to avoid clashes with other code. Use `YAPInterface.h` to take advantage of the new interface. `c_interface.h` is still available if you cannot port the code to the new interface.
    • Access to elements in the new interface always goes through functions. This includes access to the argument registers, `YAP_ARG1` to `YAP_ARG16`. This change breaks code such as `unify(\&ARG1,\&t)`, which is nowadays: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ { YAP_Unify(ARG1, t); } ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
    • `cut_fail()` and `cut_succeed()` are now functions.
    • The use of `Deref` is deprecated. All functions that return Prolog terms, including the ones that access arguments, already dereference their arguments.
    • Space allocated with PRESERVE_DATA is ignored by garbage collection and stack shifting. As a result, any pointers to a Prolog stack object, including some terms, may be corrupted after garbage collection or stack shifting. Prolog terms should instead be stored as arguments to the backtrackable procedure.
    @section YAPLibrary Using YAP as a Library YAP can be used as a library to be called from other programs. To do so, you must first create the YAP library: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ make library make install_library ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ This will install a file `libyap.a` in _LIBDIR_ and the Prolog headers in _INCLUDEDIR_. The library contains all the functionality available in YAP, except the foreign function loader and for `YAP`'s startup routines. To actually use this library you must follow a five step process:
    1. You must initialize the YAP environment. A single function, `YAP_FastInit` asks for a contiguous chunk in your memory space, fills it in with the data-base, and sets up YAP's stacks and execution registers. You can use a saved space from a standard system by calling [save_program/1](@ref save_program).
    2. You then have to prepare a query to give to YAP. A query is a Prolog term, and you just have to use the same functions that are available in the C-interface.
    3. You can then use `YAP_RunGoal(query)` to actually evaluate your query. The argument is the query term `query`, and the result is 1 if the query succeeded, and 0 if it failed.
    4. You can use the term destructor functions to check how arguments were instantiated.
    5. If you want extra solutions, you can use `YAP_RestartGoal()` to obtain the next solution.
    The next program shows how to use this system. We assume the saved program contains two facts for the procedure b: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ #include #include "YAP/YAPInterface.h" int main(int argc, char *argv[]) { if (YAP_FastInit("saved_state") == YAP_BOOT_ERROR) exit(1); if (YAP_RunGoal(YAP_MkAtomTerm(YAP_LookupAtom("do")))) { printf("Success\n"); while (YAP_RestartGoal()) printf("Success\n"); } printf("NO\n"); } ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ The program first initializes YAP, calls the query for the first time and succeeds, and then backtracks twice. The first time backtracking succeeds, the second it fails and exits. To compile this program it should be sufficient to do: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ cc -o exem -I../YAP4.3.0 test.c -lYAP -lreadline -lm ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ You may need to adjust the libraries and library paths depending on the Operating System and your installation of YAP. Note that YAP4.3.0 provides the first version of the interface. The interface may change and improve in the future. The following C-functions are available from YAP:
    • YAP_CompileClause(`YAP_Term` _Clause_) Compile the Prolog term _Clause_ and assert it as the last clause for the corresponding procedure.
    • `int` YAP_ContinueGoal(`void`) Continue execution from the point where it stopped.
    • `void` YAP_Error(`int` _ID_,`YAP_Term` _Cause_,`char \*` _error_description_) Generate an YAP System Error with description given by the string _error_description_. _ID_ is the error ID, if known, or `0`. _Cause_ is the term that caused the crash.
    • `void` YAP_Exit(`int` _exit_code_) Exit YAP immediately. The argument _exit_code_ gives the error code and is supposed to be 0 after successful execution in Unix and Unix-like systems.
    • `YAP_Term` YAP_GetValue(`Atom` _at_) Return the term _value_ associated with the atom _at_. If no such term exists the function will return the empty list.
    • YAP_FastInit(`char \*` _SavedState_) Initialize a copy of YAP from _SavedState_. The copy is monolithic and currently must be loaded at the same address where it was saved. `YAP_FastInit` is a simpler version of `YAP_Init`.
    • YAP_Init( _InitInfo_) Initialize YAP. The arguments are in a `C` structure of type `YAP_init_args`. The fields of _InitInfo_ are `char \*` _SavedState_, `int` _HeapSize_, `int` _StackSize_, `int` _TrailSize_, `int` _NumberofWorkers_, `int` _SchedulerLoop_, `int` _DelayedReleaseLoad_, `int` _argc_, `char \*\*` _argv_, `int` _ErrorNo_, and `char \*` _ErrorCause_. The function returns an integer, which indicates the current status. If the result is `YAP_BOOT_ERROR` booting failed. If _SavedState_ is not NULL, try to open and restore the file _SavedState_. Initially YAP will search in the current directory. If the saved state does not exist in the current directory YAP will use either the default library directory or the directory given by the environment variable [YAPLIBDIR](@ref YAPLIBDIR). Note that currently the saved state must be loaded at the same address where it was saved. If _HeapSize_ is different from 0 use _HeapSize_ as the minimum size of the Heap (or code space). If _StackSize_ is different from 0 use _HeapSize_ as the minimum size for the Stacks. If _TrailSize_ is different from 0 use _TrailSize_ as the minimum size for the Trails. The _NumberofWorkers_, _NumberofWorkers_, and _DelayedReleaseLoad_ are only of interest to the or-parallel system. The argument count _argc_ and string of arguments _argv_ arguments are to be passed to user programs as the arguments used to call YAP. If booting failed you may consult `ErrorNo` and `ErrorCause` for the cause of the error, or call `YAP_Error(ErrorNo,0L,ErrorCause)` to do default processing.
    • `void` YAP_PutValue(`Atom` _at_, `YAP_Term` _value_) Associate the term _value_ with the atom _at_. The term _value_ must be a constant. This functionality is used by YAP as a simple way for controlling and communicating with the Prolog run-time.
    • `YAP_Term` YAP_Read(`IOSTREAM \*Stream`) Parse a _Term_ from the stream _Stream_.
    • `YAP_Term` YAP_Write(`YAP_Term` _t_) Copy a Term _t_ and all associated constraints. May call the garbage collector and returns `0L` on error (such as no space being available).
    • `void` YAP_Write(`YAP_Term` _t_, `IOSTREAM` _stream_, `int` _flags_) Write a Term _t_ using the stream _stream_ to output characters. The term is written according to a mask of the following flags in the `flag` argument: `YAP_WRITE_QUOTED`, `YAP_WRITE_HANDLE_VARS`, `YAP_WRITE_USE_PORTRAY`, and `YAP_WRITE_IGNORE_OPS`.
    • `int` YAP_WriteBuffer(`YAP_Term` _t_, `char \*` _buff_, `size_t` _size_, `int` _flags_) Write a YAP_Term _t_ to buffer _buff_ with size _size_. The term is written according to a mask of the following flags in the `flag` argument: `YAP_WRITE_QUOTED`, `YAP_WRITE_HANDLE_VARS`, `YAP_WRITE_USE_PORTRAY`, and `YAP_WRITE_IGNORE_OPS`. The function will fail if it does not have enough space in the buffer.
    • `char \*` YAP_WriteDynamicBuffer(`YAP_Term` _t_, `char \*` _buff_, `size_t` _size_, `size_t` _\*lengthp_, `size_t` _\*encodingp_, `int` _flags_) Write a YAP_Term _t_ to buffer _buff_ with size _size_. The code will allocate an extra buffer if _buff_ is `NULL` or if `buffer` does not have enough room. The variable `lengthp` is assigned the size of the resulting buffer, and `encodingp` will receive the type of encoding (currently only `PL_ENC_ISO_LATIN_1` and `PL_ENC_WCHAR` are supported)
    • `void` YAP_InitConsult(`int` _mode_, `char \*` _filename_) Enter consult mode on file _filename_. This mode maintains a few data-structures internally, for instance to know whether a predicate before or not. It is still possible to execute goals in consult mode. If _mode_ is `TRUE` the file will be reconsulted, otherwise just consulted. In practice, this function is most useful for bootstrapping Prolog, as otherwise one may call the Prolog predicate [compile/1](@ref compile) or [consult/1](@ref consult) to do compilation. Note that it is up to the user to open the file _filename_. The `YAP_InitConsult` function only uses the file name for internal bookkeeping.
    • `void` YAP_EndConsult(`void`) Finish consult mode.
    Some observations:
    • The system will core dump if you try to load the saved state in a different address from where it was made. This may be a problem if your program uses `mmap`. This problem will be addressed in future versions of YAP.
    • Currently, the YAP library will pollute the name space for your program.
    • The initial library includes the complete YAP system. In the future we plan to split this library into several smaller libraries (e.g. if you do not want to perform Input/Output).
    • You can generate your own saved states. Look at the `boot.yap` and `init.yap` files.
    @page Compatibility Compatibility with Other Prolog systems YAP has been designed to be as compatible as possible with other Prolog systems, and initially with C-Prolog. More recent work on YAP has included features initially proposed for the Quintus and SICStus Prolog systems. Developments since `YAP4.1.6` we have striven at making YAP compatible with the ISO-Prolog standard. @section ChYProlog Compatibility with the C-Prolog interpreter @subsection Major_Differences_with_ChYProlog Major Differences between YAP and C-Prolog. YAP includes several extensions over the original C-Prolog system. Even so, most C-Prolog programs should run under YAP without changes. The most important difference between YAP and C-Prolog is that, being YAP a compiler, some changes should be made if predicates such as `assert`, `clause` and `retract` are used. First predicates which will change during execution should be declared as `dynamic` by using commands like: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ :- dynamic f/n. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ where `f` is the predicate name and n is the arity of the predicate. Note that several such predicates can be declared in a single command: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ :- dynamic f/2, ..., g/1. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Primitive predicates such as `retract` apply only to dynamic predicates. Finally note that not all the C-Prolog primitive predicates are implemented in YAP. They can easily be detected using the `unknown` system predicate provided by YAP. Last, by default YAP enables character escapes in strings. You can disable the special interpretation for the escape character by using: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ :- yap_flag(character_escapes,off). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ or by using: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ :- yap_flag(language,cprolog). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ @subsection Fully_ChYProlog_Compatible YAP predicates fully compatible with C-Prolog These are the Prolog built-ins that are fully compatible in both C-Prolog and YAP: @subsection Not_Strictly_ChYProlog_Compatible YAP predicates not strictly compatible with C-Prolog These are YAP built-ins that are also available in C-Prolog, but that are not fully compatible: @subsection Not_in_ChYProlog YAP predicates not available in C-Prolog These are YAP built-ins not available in C-Prolog. @subsection Not_in_YAP YAP predicates not available in C-Prolog These are C-Prolog built-ins not available in YAP:
    • 'LC' The following Prolog text uses lower case letters.
    • 'NOLC' The following Prolog text uses upper case letters only.
    @section SICStus_Prolog Compatibility with the Quintus and SICStus Prolog systems The Quintus Prolog system was the first Prolog compiler to use Warren's Abstract Machine. This system was very influential in the Prolog community. Quintus Prolog implemented compilation into an abstract machine code, which was then emulated. Quintus Prolog also included several new built-ins, an extensive library, and in later releases a garbage collector. The SICStus Prolog system, developed at SICS (Swedish Institute of Computer Science), is an emulator based Prolog system largely compatible with Quintus Prolog. SICStus Prolog has evolved through several versions. The current version includes several extensions, such as an object implementation, co-routining, and constraints. Recent work in YAP has been influenced by work in Quintus and SICStus Prolog. Wherever possible, we have tried to make YAP compatible with recent versions of these systems, and specifically of SICStus Prolog. You should use ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ :- yap_flag(language, sicstus). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ for maximum compatibility with SICStus Prolog. @subsection Major_Differences_with_SICStus Major Differences between YAP and SICStus Prolog. Both YAP and SICStus Prolog obey the Edinburgh Syntax and are based on the WAM. Even so, there are quite a few important differences:
    • Differently from SICStus Prolog, YAP does not have a notion of interpreted code. All code in YAP is compiled.
    • YAP does not support an intermediate byte-code representation, so the `fcompile/1` and `load/1` built-ins are not available in YAP.
    • YAP implements escape sequences as in the ISO standard. SICStus Prolog implements Unix-like escape sequences.
    • YAP implements [initialization/1](@ref initialization) as per the ISO standard. Use [prolog_initialization/1](@ref prolog_initialization) for the SICStus Prolog compatible built-in.
    • Prolog flags are different in SICStus Prolog and in YAP.
    • The SICStus Prolog `on_exception/3` and `raise_exception` built-ins correspond to the ISO built-ins [catch/3](@ref catch) and [throw/1](@ref throw).
    • The following SICStus Prolog v3 built-ins are not (currently) implemented in YAP (note that this is only a partial list): [file_search_path/2](@ref file_search_path), `stream_interrupt/3`, `reinitialize/0`, `help/0`, `help/1`, `trimcore/0`, `load_files/1`, [load_files/2](@ref load_files), and `require/1`. The previous list is incomplete. We also cannot guarantee full compatibility for other built-ins (although we will try to address any such incompatibilities). Last, SICStus Prolog is an evolving system, so one can be expect new incompatibilities to be introduced in future releases of SICStus Prolog.
    • YAP allows asserting and abolishing static code during execution through the [assert_static/1](@ref assert_static) and [abolish/1](@ref abolish) built-ins. This is not allowed in Quintus Prolog or SICStus Prolog.
    • The socket predicates, although designed to be compatible with SICStus Prolog, are built-ins, not library predicates, in YAP.
    • This list is incomplete.
    The following differences only exist if the [language](@ref language) flag is set to `yap` (the default):
    • The [consult/1](@ref consult) predicate in YAP follows C-Prolog semantics. That is, it adds clauses to the data base, even for preexisting procedures. This is different from [consult/1](@ref consult) in SICStus Prolog or SWI-Prolog.
    • By default, the data-base in YAP follows "logical update semantics", as Quintus Prolog or SICStus Prolog do. Previous versions followed "immediate update semantics". The difference is depicted in the next example: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ :- dynamic a/1. ?- assert(a(1)). ?- retract(a(X)), X1 is X +1, assertz(a(X)). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ With immediate semantics, new clauses or entries to the data base are visible in backtracking. In this example, the first call to [retract/1](@ref retract) will succeed. The call to *assertz/1* will then succeed. On backtracking, the system will retry [retract/1](@ref retract). Because the newly asserted goal is visible to [retract/1](@ref retract), it can be retracted from the data base, and `retract(a(X))` will succeed again. The process will continue generating integers for ever. Immediate semantics were used in C-Prolog. With logical update semantics, any additions or deletions of clauses for a goal will not affect previous activations of the goal. In the example, the call to [assertz/1](@ref assertz) will not see the update performed by the [assertz/1](@ref assertz), and the query will have a single solution. Calling `yap_flag(update_semantics,logical)` will switch YAP to use logical update semantics.
    • [dynamic/1](@ref dynamic) is a built-in, not a directive, in YAP.
    • By default, YAP fails on undefined predicates. To follow default SICStus Prolog use: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ :- yap_flag(unknown,error). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
    • By default, directives in YAP can be called from the top level.
    @subsection Fully_SICStus_Compatible YAP predicates fully compatible with SICStus Prolog These are the Prolog built-ins that are fully compatible in both SICStus Prolog and YAP: @subsection Not_Strictly_SICStus_Compatible YAP predicates not strictly compatible with SICStus Prolog These are YAP built-ins that are also available in SICStus Prolog, but that are not fully compatible: @subsection Not_in_SICStus_Prolog YAP predicates not available in SICStus Prolog These are YAP built-ins not available in SICStus Prolog. @section ISO_Prolog Compatibility with the ISO Prolog standard The Prolog standard was developed by ISO/IEC JTC1/SC22/WG17, the international standardization working group for the programming language Prolog. The book "Prolog: The Standard" by Deransart, Ed-Dbali and Cervoni gives a complete description of this standard. Development in YAP from YAP4.1.6 onwards have striven at making YAP compatible with ISO Prolog. As such:
    • YAP now supports all of the built-ins required by the ISO-standard, and,
    • Error-handling is as required by the standard.
    YAP by default is not fully ISO standard compliant. You can set the [language](@ref language) flag to `iso` to obtain very good compatibility. Setting this flag changes the following:
    • By default, YAP uses "immediate update semantics" for its database, and not "logical update semantics", as per the standard, ( (see [SICStus Prolog](@ref SICStus_Prolog))). This affects [assert/1](@ref assert), [retract/1](@ref retract), and friends. Calling `set_prolog_flag(update_semantics,logical)` will switch YAP to use logical update semantics.
    • By default, YAP implements the [atom_chars/2](@ref atom_chars)( (see [Testing Terms](@ref Testing_Terms))), and [number_chars/2](@ref number_chars), ( (see [Testing Terms](@ref Testing_Terms))), built-ins as per the original Quintus Prolog definition, and not as per the ISO definition. Calling `set_prolog_flag(to_chars_mode,iso)` will switch YAP to use the ISO definition for [atom_chars/2](@ref atom_chars) and [number_chars/2](@ref number_chars).
    • By default, YAP allows executable goals in directives. In ISO mode most directives can only be called from top level (the exceptions are [set_prolog_flag/2](@ref set_prolog_flag) and [op/3](@ref op)).
    • Error checking for meta-calls under ISO Prolog mode is stricter than by default.
    • The [strict_iso](@ref strict_iso) flag automatically enables the ISO Prolog standard. This feature should disable all features not present in the standard.
    The following incompatibilities between YAP and the ISO standard are known to still exist:
    • Currently, YAP does not handle overflow errors in integer operations, and handles floating-point errors only in some architectures. Otherwise, YAP follows IEEE arithmetic.
    Please inform the authors on other incompatibilities that may still exist. @section Operators Summary of YAP Predefined Operators The Prolog syntax caters for operators of three main kinds:
    • prefix;
    • infix;
    • postfix.
    Each operator has precedence in the range 1 to 1200, and this precedence is used to disambiguate expressions where the structure of the term denoted is not made explicit using brackets. The operator of higher precedence is the main functor. If there are two operators with the highest precedence, the ambiguity is solved analyzing the types of the operators. The possible infix types are: _xfx_, _xfy_, and _yfx_. With an operator of type _xfx_ both sub-expressions must have lower precedence than the operator itself, unless they are bracketed (which assigns to them zero precedence). With an operator type _xfy_ only the left-hand sub-expression must have lower precedence. The opposite happens for _yfx_ type. A prefix operator can be of type _fx_ or _fy_. A postfix operator can be of type _xf_ or _yf_. The meaning of the notation is analogous to the above. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ a + b * c ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ means ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ a + (b * c) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ as + and \* have the following types and precedences: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ :-op(500,yfx,'+'). :-op(400,yfx,'*'). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Now defining ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ :-op(700,xfy,'++'). :-op(700,xfx,'=:='). a ++ b =:= c ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ means ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ a ++ (b =:= c) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ The following is the list of the declarations of the predefined operators: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ :-op(1200,fx,['?-', ':-']). :-op(1200,xfx,[':-','-->']). :-op(1150,fx,[block,dynamic,mode,public,multifile,meta_predicate, sequential,table,initialization]). :-op(1100,xfy,[';','|']). :-op(1050,xfy,->). :-op(1000,xfy,','). :-op(999,xfy,'.'). :-op(900,fy,['\+', not]). :-op(900,fx,[nospy, spy]). :-op(700,xfx,[@>=,@=<,@<,@>,<,=,>,=:=,=\=,\==,>=,=<,==,\=,=..,is]). :-op(500,yfx,['\/','/\','+','-']). :-op(500,fx,['+','-']). :-op(400,yfx,['<<','>>','//','*','/']). :-op(300,xfx,mod). :-op(200,xfy,['^','**']). :-op(50,xfx,same). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ## Predicate Index ## ## Concept Index ##