A Python interface, pyschlandals, is available from PyPi here.
The interface is still rudimentary; open a pull request if you need any functionality.
To install the Python interface, run pip install pyschlandals.
Running a simple problem
A problem in pyschlandals is a set of distributions and clauses.
The following code block shows how to create a simple problem instance for a Bayesian Network and solve it using the DPLL-based search.
Notice that the indexes in the clauses start at 1, and the distributions use the first indexes.
from pyschlandals.pwmc import PyProblem
problem = PyProblem()
problem.add_distribution([0.2, 0.8])
problem.add_distribution([0.3, 0.7])
problem.add_distribution([0.4, 0.6])
problem.add_distribution([0.1, 0.9])
problem.add_distribution([0.5, 0.5])
problem.add_clause([11, -1])
problem.add_clause([12, -2])
problem.add_clause([13, -11, -3])
problem.add_clause([13, -12, -5])
problem.add_clause([14, -11, -4])
problem.add_clause([14, -12, -6])
problem.add_clause([15, -13, -7])
problem.add_clause([15, -14, -9])
problem.add_clause([16, -13, -8])
problem.add_clause([16, -14, -10])
problem.add_clause([-15])
print(problem.solve())
The problem generation can be seen as lazy. The PyProblem is sent to the rust code only when problem.solve() is called.
At this point, the distributions and clauses are sent to Schlandals as an alternative to the .cnf files.