Vcsn

Vcsn is a platform for weighted automata and rational expressions.

It is composed of an efficient C++ generic library, shell tools, Python bindings, and a graphical interactive environment on top of Jupyter/IPython.

Copyright (C) 2012-2018 The Vcsn Group.

Overview

The Vcsn platform enables the development of C++ programs manipulating weighted finite automata in an abstract and general way with, at the same time, a large specialization power. On the one hand, we can write algorithms working on every automaton with weights in any semiring and with words from any free monoids. And on the other hand, a particular algorithm can be specialized for a particular data structure.

The Python bindings, and especially the IPython interface, make Vcsn a tool particularly well suited for practical sessions in courses of Formal Language Theory. More generally, it proves to be a handy means to explore compositions of algorithms on automata from small sizes to "real world" cases.

Although it is now quite mature, Vcsn is an ongoing development project. Therefore some algorithms and data structures may change in the future.

Please send any question or comments to [email protected], and report bugs to either our issue tracker https://gitlab.lrde.epita.fr/vcsn/vcsn/issues, or via emails to [email protected].

Using Vcsn

Documentation about Vcsn can be found in several places:

• The Python interface is available online. In particular, be sure to read the introduction to Vcsn.

• This documentation is also available in the directory doc/notebooks. Once Vcsn installed, run vcsn doc automaton.determinize for example.

• The file NEWS.md includes many examples of how to run commands and algorithms.

• The directory tests/python contains tons of test cases written in Python.

• The documentation of the C++ low-level interface is generated by Doxygen from the comments in the header files (vcsn/algos/*.hh). To generate the C++ documentation, run make doxygen. For a given algorithm it is useful to read the Python documentation, since it provides many examples.

• The dyn:: C++ interface is documented in vcsn/dyn/algos.hh. Look for the namespace vcsn/dyn in the Doxygen generated documentation.

Quick Start

Vcsn must be installed to be used. Once you installed it, here are a few commands to help you start using it.

• vcsn python or vcsn ipython

  Start a Python/IPython session. Then, for instance:

  $ vcsn ipython Python 3.6.4 (default, Dec 21 2017, 20:33:21) Type 'copyright', 'credits' or 'license' for more information IPython 6.2.1 -- An enhanced Interactive Python. Type '?' for help.

  In [1]: import vcsn

  In [2]: vcsn.B.expression('[ab]{4}a[ab]').standard().determinize().num_states() Out[2]: 12

• vcsn notebook

  Start a Jupyter notebook in a web browser. Then you can run the same Python commands as above. Requires that you have installed IPython.

• vcsn doc

  Opens the documentation.

• vcsn diagnose

  Checks that Vcsn is installed properly, and generates diagnostics.

• vcsn --help

  List the available commands.

Installation

To install Vcsn on your system, type in the classical sequence at the command prompt:

./configure
make
make install (as root)

Do not hesitate to run make -j3 if, for instance, your CPU features 4 threads. To enable the generation of the Doxygen documentation, pass --enable-doxygen to configure.

Note that an installation is specific to the compiler used to install it. Indeed, the call to ./configure enables some workarounds and, consequently, users must compile with the same compiler to avoid compatibility problems.

Between make and make install, you may also want to run:

make check

It run the test suite to check the whole platform. Beware that checking Vcsn is a very long process, also consider -j3.

Build Requirements

Packages needed

Vcsn was tested with the GNU Compiler Collection (GCC) versions 5, 6 and Clang from 3.5, to 6.0.

Boost is a C++ library which provides many useful features. You must install this library on your system. Vcsn should support any version after 1.49. The following Boost components are used:

• Boost.Algorithm
• Boost.DynamicBitset
• Boost.IOStreams
• Boost.Filesystem
• Boost.Flyweight
• Boost.Heap
• Boost.Iterator
• Boost.Python
• Boost.Range
• Boost.Regex
• Boost.System
• Boost.Tokenizer

Ccache saves the user from repeated compilations.

To load plugins, Vcsn relies on libltdl, which is a component of the GNU Libtool project. Depending on your distribution/packaging system, you may have to install libltdl-dev (e.g., Debian) or libtool (MacPorts).

Vcsn uses the Dot format to save automaton in a human readable file. You should install Graphviz to visualize these .gv files.

To provide safe support for ℚ, Vcsn relies on The GNU Multiple Precision Arithmetic Library.

Doxygen is used to generate the C++ reference documentation.

yaml-cpp is used to handle the configuration files. Beware that version 0.5.2 is buggy and will not work properly. Use 0.5.1, or 0.5.3 or more recent.

Ubuntu/Debian packages

Please, help us keep this list up-to-date!

ccache dot2tex g++ graphviz imagemagick ipython3-notebook libboost-all-dev libgmp-dev libzmq3-dev locales pdf2svg python3-colorama python3-dev python3-matplotlib python3-pandas python3-pip python3-psutil python3-regex python3-setuptools libyaml-cpp-dev

Vcsn expects to be built and to run in an UTF-8 environment. This requires the locales package, and that en_US.UTF-8 be supported:

sudo 'echo "en_US.UTF-8 UTF-8" >>/etc/locale.gen'
sudo locale-gen
export LANG=en_US.UTF-8   \
       LANGUAGE=en_US:en  \
       LC_ALL=en_US.UTF-8

MacPorts

First install these packages:

sudo port install  boost +python36  py36-notebook  python36

Make sure that Boost is configured to be used with Python 3.6:

$ port variant boost | grep -F +
[+]no_single: Disable building single-threaded libraries
[+]no_static: Disable building static libraries
(+)python36: Build Boost.Python for Python 3.6

Then install Vcsn.

sudo port install vcsn

Libraries installed in non-standard directories

If you have installed Boost in a non-standard directory (i.e., a directory that is not searched by default by your C++ compiler), you will have to set the CPPFLAGS and LDFLAGS variables to pass the necessary -I and -L options to the preprocessor and linker.

For instance if you installed Boost in /opt/boost/ you should run ./configure as follows:

./configure CPPFLAGS="-I/opt/boost" LDFLAGS="-L/opt/boost"

Layout of the tarball

The project directory layout is as follows:

build-aux : Auxiliary tools used by the GNU Build System during configure and make stages.

doc : Doxygen documentation, and IPython notebooks.

share : Data files to be installed on your system.

lib : Various libraries, including instantiation of some contexts.

vcsn : The Vcsn C++ Library headers.

python : The Python binding.

bin : Various programs to install. In particular the program vcsn, which provides access to all the other programs. See vcsn --help.

tests : The test suites.

Starting from the repository

To contribute to Vcsn, or to build it from its Git repository, you need more tools:

• Automake 1.14 or newer
• Autoconf 2.69 or newer
• Bison 3.0.4 or newer
• Flex 2.5.35 or newer

Before the configuration steps, run:

./bootstrap

to set up the GNU Build system.

Ubuntu

In addition of the packages above, you need:

autoconf automake libtool flex bison

License

This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 3 of the License, or (at your option) any later version.

The complete GNU General Public License Notice can be found as the COPYING.txt file in the root directory.

Contacts

The team can be reached by mail at [email protected]. Snail mail address:

• Vcsn - LRDE

  Akim Demaille & Alexandre Duret-Lutz
  Laboratoire de Recherche et Développement de l'EPITA
  14-16 rue Voltaire
  94276 Le Kremlin-Bicêtre CEDEX
  France