python-constraint

python-constraint is a module implementing support for handling CSPs (Constraint Solving Problems) over finite domain


Keywords
csp, constraint, solving, problems, problem, solver, constraint-satisfaction-problem, python
License
BSD-3-Clause
Install
pip install python-constraint==1.1

Documentation

PyPI - License Build Status Documentation Status PyPI - Python Versions PyPI - Downloads PyPI - Status Code Coverage

python-constraint

This software is now back to active development / maintainance status.
For an overview of recent changes, visit the Changelog.
The complete documentation can be found here.

Introduction

The python-constraint module offers efficient solvers for Constraint Satisfaction Problems (CSPs) 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:

>>> 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:

>>> 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:

>>> 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

Predefined constraint types currently available:

  • FunctionConstraint
  • AllDifferentConstraint
  • AllEqualConstraint
  • MaxSumConstraint
  • ExactSumConstraint
  • MinSumConstraint
  • MaxProdConstraint
  • MinProdConstraint
  • InSetConstraint
  • NotInSetConstraint
  • SomeInSetConstraint
  • SomeNotInSetConstraint

API documentation

Documentation for the module is available at: http://python-constraint.github.io/python-constraint/. It can be built locally by running make clean html from the docs folder. For viewing RST files locally, restview is recommended.

Download and install

$ pip install python-constraint

Testing

Run 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 pytest (optionally add --no-cov if you have the C-extensions enabled).

Contributing

Feel free to contribute by submitting pull requests or opening issues. Please refer to the contribution guidelines before doing so.

Roadmap

This GitHub organization and repository is a global effort to help to maintain 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.

Planned development:

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

Contact

But it's probably better to open an issue.