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Bindings to CryptoMiniSat 5.0.1 (a SAT solver)

Project description

pycryptosat: bindings to the CryptoMiniSat SAT solver

This directory provides Python bindings to CryptoMiniSat on the C++ level,
i.e. when importing pycryptosat, the CryptoMiniSat solver becomes part of the
Python process itself.

The pycryptosat python package compiles while compiling CryptoMiniSat. It
cannotbe compiled on its own, it must be compiled at the same time as
CryptoMiniSat. You will need the python development libraries in order to

apt-get install python-dev

After this, cmake then indicate that pycryptosat will be compiled:

cd cryptominisat
mkdir build
cd build
cmake ..
-- Found PythonInterp: /usr/bin/python2.7 (found suitable version "2.7.9", minimum required is "2.7")
-- Found PythonLibs: /usr/lib/x86_64-linux-gnu/ (found suitable version "2.7.9", minimum required is "2.7")
-- PYTHON_EXECUTABLE:FILEPATH=/usr/bin/python2.7
-- PYTHON_LIBRARY:FILEPATH=/usr/lib/x86_64-linux-gnu/
-- PYTHON_INCLUDE_DIR:FILEPATH=/usr/include/python2.7
-- OK, found python interpreter, libs and header files
-- Building python interface

It will then generate the pycryptosat library and install it when calling
`make install`.


The ``pycryptosat`` module has one object, ``Solver`` that has two functions
``solve`` and ``add_clause``.

The funcion ``add_clause()`` takes an iterable list of literals such as
``[1, 2]`` which represents the truth ``1 or 2 = True``. For example,
``add_clause([1])`` sets variable ``1`` to ``True``.

The function ``solve()`` solves the system of equations that have been added
with ``add_clause()``:

>>> from pycryptosat import Solver
>>> s = Solver()
>>> s.add_clause([1, 2])
>>> sat, solution = s.solve()
>>> print sat
>>> print solution
(None, True, True)

The return value is a tuple. First part of the tuple indicates whether the
problem is satisfiable. In this case, it's ``True``, i.e. satisfiable. The second
part is a tuple contains the solution, preceded by None, so you can index into
it with the variable number. E.g. ``solution[1]`` returns the value for
variabe ``1``.

The ``solve()`` method optionally takes an argument ``assumptions`` that
allows the user to set values to specific variables in the solver in a temporary
fashion. This means that in case the problem is satisfiable but e.g it's
unsatisfiable if variable 2 is FALSE, then ``solve([-2])`` will return
UNSAT. However, a subsequent call to ``solve()`` will still return a solution.
If instead of an assumption ``add_clause()`` would have been used, subsequent
``solve()`` calls would have returned unsatisfiable.

``Solver`` takes the following keyword arguments:
* ``confl_limit``: the propagation limit (integer)
* ``verbose``: the verbosity level (integer)

The ``confl_limit`` argument sets a kind of time-out limit to the solver. If
the solver runs out of time, it returns with ``(None, None)``.


Let us consider the following clauses, represented using
the DIMACS `cnf <>`_

p cnf 5 3
1 -5 4 0
-1 5 3 4 0
-3 -4 0

Here, we have 5 variables and 3 clauses, the first clause being
(x\ :sub:`1` or not x\ :sub:`5` or x\ :sub:`4`).
Note that the variable x\ :sub:`2` is not used in any of the clauses,
which means that for each solution with x\ :sub:`2` = True, we must
also have a solution with x\ :sub:`2` = False. In Python, each clause is
most conveniently represented as a list of integers. Naturally, it makes
sense to represent each solution also as a list of integers, where the sign
corresponds to the Boolean value (+ for True and - for False) and the
absolute value corresponds to i\ :sup:`th` variable::

>>> import pycryptosat
>>> solver = pycryptosat.Solver()
>>> solver.add_clause([1, -5, 4])
>>> solver.add_clause([-1, 5, 3, 4])
>>> solver.add_clause([-3, -4])
>>> solver.solve()
(True, (None, True, False, False, True, True))

This solution translates to: x\ :sub:`1` = x\ :sub:`4` = x\ :sub:`5` = True,
x\ :sub:`2` = x\ :sub:`3` = False

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