python-constraint2

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python-constraint

| This software is now back to active development / maintainance status. | For an overview of recent changes, visit the Changelog <https://github.com/python-constraint/python-constraint/blob/main/CHANGELOG.md>. | The complete documentation can be found here <http://python-constraint.github.io/python-constraint/>.

.. contents:: :local: :depth: 1

Introduction

The :code:python-constraint module offers efficient solvers for Constraint Satisfaction Problems (CSPs) <https://en.wikipedia.org/wiki/Constraint_satisfaction_problem>_ over finite domains in an accessible Python package. CSP is class of problems which may be represented in terms of variables (a, b, ...), domains (a in [1, 2, 3], ...), and constraints (a < b, ...).

Examples

Basics

This interactive Python session demonstrates basic operations:

.. code-block:: python

    >>> from constraint import *
    >>> problem = Problem()
    >>> problem.addVariable("a", [1,2,3])
    >>> problem.addVariable("b", [4,5,6])
    >>> problem.getSolutions()
    [{'a': 3, 'b': 6}, {'a': 3, 'b': 5}, {'a': 3, 'b': 4},
     {'a': 2, 'b': 6}, {'a': 2, 'b': 5}, {'a': 2, 'b': 4},
     {'a': 1, 'b': 6}, {'a': 1, 'b': 5}, {'a': 1, 'b': 4}]

    >>> problem.addConstraint(lambda a, b: a*2 == b,
                              ("a", "b"))
    >>> problem.getSolutions()
    [{'a': 3, 'b': 6}, {'a': 2, 'b': 4}]

    >>> problem = Problem()
    >>> problem.addVariables(["a", "b"], [1, 2, 3])
    >>> problem.addConstraint(AllDifferentConstraint())
    >>> problem.getSolutions()
    [{'a': 3, 'b': 2}, {'a': 3, 'b': 1}, {'a': 2, 'b': 3},
     {'a': 2, 'b': 1}, {'a': 1, 'b': 2}, {'a': 1, 'b': 3}]

Rooks problem

The following example solves the classical Eight Rooks problem:

.. code-block:: python

>>> problem = Problem()
>>> numpieces = 8
>>> cols = range(numpieces)
>>> rows = range(numpieces)
>>> problem.addVariables(cols, rows)
>>> for col1 in cols:
...     for col2 in cols:
...         if col1 < col2:
...             problem.addConstraint(lambda row1, row2: row1 != row2,
...                                   (col1, col2))
>>> solutions = problem.getSolutions()
>>> solutions
>>> solutions
[{0: 7, 1: 6, 2: 5, 3: 4, 4: 3, 5: 2, 6: 1, 7: 0},
 {0: 7, 1: 6, 2: 5, 3: 4, 4: 3, 5: 2, 6: 0, 7: 1},
 {0: 7, 1: 6, 2: 5, 3: 4, 4: 3, 5: 1, 6: 2, 7: 0},
 {0: 7, 1: 6, 2: 5, 3: 4, 4: 3, 5: 1, 6: 0, 7: 2},
 ...
 {0: 7, 1: 5, 2: 3, 3: 6, 4: 2, 5: 1, 6: 4, 7: 0},
 {0: 7, 1: 5, 2: 3, 3: 6, 4: 1, 5: 2, 6: 0, 7: 4},
 {0: 7, 1: 5, 2: 3, 3: 6, 4: 1, 5: 2, 6: 4, 7: 0},
 {0: 7, 1: 5, 2: 3, 3: 6, 4: 1, 5: 4, 6: 2, 7: 0},
 {0: 7, 1: 5, 2: 3, 3: 6, 4: 1, 5: 4, 6: 0, 7: 2},
 ...]

Magic squares

This example solves a 4x4 magic square:

.. code-block:: python

    >>> problem = Problem()
    >>> problem.addVariables(range(0, 16), range(1, 16 + 1))
    >>> problem.addConstraint(AllDifferentConstraint(), range(0, 16))
    >>> problem.addConstraint(ExactSumConstraint(34), [0, 5, 10, 15])
    >>> problem.addConstraint(ExactSumConstraint(34), [3, 6, 9, 12])
    >>> for row in range(4):
    ...     problem.addConstraint(ExactSumConstraint(34),
                                  [row * 4 + i for i in range(4)])
    >>> for col in range(4):
    ...     problem.addConstraint(ExactSumConstraint(34),
                                  [col + 4 * i for i in range(4)])
    >>> solutions = problem.getSolutions()

Features
--------

The following solvers are available:

- Backtracking solver
- Optimized backtracking solver
- Recursive backtracking solver
- Minimum conflicts solver

.. role:: python(code)
   :language: python

Predefined constraint types currently available:

- :python:`FunctionConstraint`
- :python:`AllDifferentConstraint`
- :python:`AllEqualConstraint`
- :python:`MaxSumConstraint`
- :python:`ExactSumConstraint`
- :python:`MinSumConstraint`
- :python:`MaxProdConstraint`
- :python:`MinProdConstraint`
- :python:`InSetConstraint`
- :python:`NotInSetConstraint`
- :python:`SomeInSetConstraint`
- :python:`SomeNotInSetConstraint`

API documentation
-----------------
Documentation for the module is available at: http://python-constraint.github.io/python-constraint/.
It can be built locally by running :code:`make clean html` from the `docs` folder.
For viewing RST files locally, `restview <https://pypi.org/project/restview/>`_ is recommended.

Download and install
--------------------

.. code-block:: shell

    $ pip install python-constraint

Testing
-------

Run :code:`nox` (tests for all supported Python versions in own virtual environment).

To test against your local Python version: make sure you have the development dependencies installed.
Run :code:`pytest` (optionally add :code:`--no-cov` if you have the C-extensions enabled).

Contributing
------------

Feel free to contribute by `submitting pull requests <https://github.com/python-constraint/python-constraint/pulls>`_ or `opening issues <https://github.com/python-constraint/python-constraint/issues>`_.
Please refer to the `contribution guidelines <https://github.com/python-constraint/python-constraint/contribute>`_ before doing so.

Roadmap
-------

This GitHub organization and repository is a global effort to help to maintain :code:`python-constraint`, which was written by Gustavo Niemeyer and originaly located at https://labix.org/python-constraint.
For an overview of recent changes, visit the `Changelog <https://github.com/python-constraint/python-constraint/blob/main/CHANGELOG.md>`_.

Planned development:

- Add a string parser for constraints
- Add parallel-capable solver
- Versioned documentation

Contact
-------
- `Gustavo Niemeyer <https://github.com/niemeyer/>`_ <[e-mail]>
- `Sébastien Celles <https://github.com/scls19fr/>`_ <[e-mail]>
- `Floris-Jan Willemsen <https://github.com/fjwillemsen>`_

But it's probably better to `open an issue <https://github.com/python-constraint/python-constraint/issues>`_.

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