dynamic_programming.edit_distance
=================================

.. py:module:: dynamic_programming.edit_distance

.. autoapi-nested-parse::

   Author  : Turfa Auliarachman
   Date    : October 12, 2016

   This is a pure Python implementation of Dynamic Programming solution to the edit
   distance problem.

   The problem is :
   Given two strings A and B. Find the minimum number of operations to string B such that
   A = B. The permitted operations are removal,  insertion, and substitution.



Attributes
----------

.. autoapisummary::

   dynamic_programming.edit_distance.solver


Classes
-------

.. autoapisummary::

   dynamic_programming.edit_distance.EditDistance


Module Contents
---------------

.. py:class:: EditDistance

   Use :
   solver              = EditDistance()
   editDistanceResult  = solver.solve(firstString, secondString)


   .. py:method:: __min_dist_top_down_dp(m: int, n: int) -> int


   .. py:method:: min_dist_bottom_up(word1: str, word2: str) -> int

      >>> EditDistance().min_dist_bottom_up("intention", "execution")
      5
      >>> EditDistance().min_dist_bottom_up("intention", "")
      9
      >>> EditDistance().min_dist_bottom_up("", "")
      0



   .. py:method:: min_dist_top_down(word1: str, word2: str) -> int

      >>> EditDistance().min_dist_top_down("intention", "execution")
      5
      >>> EditDistance().min_dist_top_down("intention", "")
      9
      >>> EditDistance().min_dist_top_down("", "")
      0



   .. py:attribute:: dp
      :value: []



   .. py:attribute:: word1
      :value: ''



   .. py:attribute:: word2
      :value: ''



.. py:data:: solver