Boolean-Solver 0.1.5

BooleanSolver
=============

Introduction
------------
This is a [python 2 project](https://pypi.python.org/pypi/Boolean-Solver/0.1.1#downloads) to speed up boolean expression coding. Sometimes we need to crack a problem by combining boolean operators such as: `and`, `or` & `not`. We as humans are prone to err, specially when expressions get big. But there is an algorithm (Quine-McCluskey) to get this expressions with zero error. Just specify your specs in a test and set a dummy function on your code. When you run your tests a solver will take your specs and code them into a simple boolean expression, enjoy :).

Setup
-----
1. Install quine-mccluskey package:
`$ pip install quine-mccluskey`

2. Install Boolean-Solver package:
`$ pip install Boolean-Solver`

Short Example
-------------
Add new script(start.py) with a mock function:

from boolean_solver import solver as s

@s.solve_boolean()
def and_function(a, b):
return False

Add a unittest(test.py) with specs:

import unittest
from boolean_solver import solver
import start


class MyTest(unittest.TestCase):
"""
1. Set the truth table of your boolean function (at least for rows where output=True)
2. run solver.execute(self, callable, table) where callable is the boolean function
with the decorator=@solve_boolean() in functions1.
See examples below:
"""
def test_AND_function(self):

# b1 b0 output
truth_table = {((False, False), False),
((False, True), False),
((True, False), False),
((True, True), True)}

solver.execute(self, start.and_function, truth_table)

Then run `$ python -m unittest test` and see the result below `def and_function(a, b)`.

How does Boolean Solver works?
------------------------------
Takes a function and a truth_table which is processed using the [Quine-McCluskey Algorithm](https://en.wikipedia.org/wiki/Quine%E2%80%93McCluskey_algorithm). Then finds a optimal boolean expression. This expression is inserted in the method definition with the decorator `@boolean_solver()`.

Arguments of `solver.execute(test, callable_function, truth_table)`
-------------------------------------------------------------------
1. The test case itself, to be able to perform tests, eg: `self`

2. A function to optimize, passed as a callable (with no arguments). This function needs a 3 mock line definition with:
line 1: decorator = `@solve_boolean()`
line 2: signature eg: `def myfunction(a, b)`
line 3: body: only one line, eg: `return False`. This line will be replaced by the boolean expression.

3. truth table is a set containing tuples. Where each row is a tuple the general form is:

`{tuple_row(tuple_inputs(a, b, ...), output), ...}`