Boolean-Solver 0.3.0

Fast development with generated boolean expressions.

Introduction

A picture is worth a thousand words and a vid is worth a thousand pictures, so watch a short intro or continue reading…

This is a python 2 project 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 :).

Package Setup

1. 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()
def and_function(a, b):
    pass

Add a unittest(test.py) with specs:

import unittest
from boolean_solver import solver
import start


class MyTest(unittest.TestCase):
    """
    1. Set conditions of your boolean function (for True outputs)
    2. Run solver.execute(self, callable, table) where callable is the boolean function
     with the decorator=@solve() in functions1.
     See examples below:
    """
    def test_AND_function(self):

        # The output is explicitly set to true
        cond = solver.Conditions(a=True, b=True, output=True)
        solver.execute(self, start.and_function, cond)

Then run $ python -m unittest test. In start.py the result should be:

def and_function(a, b):
    return a and b

Non-Boolean outputs

What if the output for a given logical condition is not a boolean. In that case a programmer would use an if. In the next example this package solves this case automatically:

Modify start.py to look like this:

from boolean_solver import solver as s

@s.solve()
def if_function(a, b):
    pass

Change test.py to:

import unittest
from boolean_solver import solver
import start


class MyTest(unittest.TestCase):

    def test_ifs(self):
        """
        Testing ifs.
        """
        cond = solver.Conditions(a=False, b=True, output=1)  # non-boolean output
        cond.add(a=True, b=False, output=0)  # non-boolean output
        solver.execute(self, start.if_function, cond)

Then run $ python -m unittest test.

Now, some cool coding

Modify start.py to look like this:

from boolean_solver import solver as s

@s.solve()
def recursive(a):
    pass

Change test.py to:

import unittest
from boolean_solver import solver
import start


class MyTest(unittest.TestCase):

    def test_recursive_function(self):
        """
        Will do recursion, extremely cool!!!
        """
        args = {'a': solver.Code('not a')}
        out = solver.Output(start.recursive, args)

        cond = solver.Conditions(a=False, output=0, default=out)
        solver.execute(self, start.recursive, cond)

The result this time will be a recursive function :)

Source Code

Setup with source code

1. Clone repository: $ git clone [e-mail]:jisazaTappsi/BooleanSolver.git

Intro Example with source code

1. Enter boolean_solver: $ cd boolean_solver

2. Run: $ python start_sample.py

   Sorry, run:
   $ python -m unittest test_sample
   first, to solve the riddle :)

3. So, run test with: $ python -m unittest test_sample

   Solved and tested and_function_3_variables
   .Solved and tested and_function
   .Solved and tested or_function
   .Solved and tested xor_function
   .
   ----------------------------------------------------------------------
   Ran 4 tests in 0.006s
   
   OK

4. Run: $ python start_sample.py

   You made it, Congrats !!!
   Now, see the functions, enjoy :)

You just solved 4 boolean expressions: and, or, xor & and3. Specs for these functions are in test_sample.py.

How does Boolean Solver works?

Takes a function and a truth_table which is processed using the Quine-McCluskey 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, conditions)

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() line 2: signature eg: def my_function(a, b) line 3: body: only one line, eg: return False. This line will be replaced by the boolean expression.

3. 1. solver.Conditions() instance: An object that can handle logical conditions with named arguments eg:

      cond = solver.Conditions(a=True, b=False)

      cond.add(a=True, b=True)

   The reserved word output allows:

   cond.add(a=False, b=False, output=False)

   Meaning that when a=False, b=False I want the output to be False

   2. Truth table: Alternatively a truth table can be specified (as a set containing tuples). Where each row is a tuple, the general form is:

      {tuple_row(tuple_inputs(a, b, …), output), …}

   or with a implicit True output:

   {tuple_inputs(a, b, ...), ...}

Arguments of solver.Conditions() and cond.add()

These are specified as a dictionary containing certain keywords as well as the function inputs.

Keywords are:

output: Determines the value to be returned when the given condition is True.

output_args: Dictionary with the values for the arguments when output is a function.

default: Value returned when non of the conditions are True.

Helper Classes

solver.Output: Class that helps define a function with arguments as an output. Has fields function(to assign a callable) and arguments to enter a dictionary with the inputs.

solver.Code: Class that helps output pieces of code. The code is given as a String.