strings.min_cost_string_conversion
==================================

.. py:module:: strings.min_cost_string_conversion

.. autoapi-nested-parse::

   Algorithm for calculating the most cost-efficient sequence for converting one string
   into another.
   The only allowed operations are
   --- Cost to copy a character is copy_cost
   --- Cost to replace a character is replace_cost
   --- Cost to delete a character is delete_cost
   --- Cost to insert a character is insert_cost



Attributes
----------

.. autoapisummary::

   strings.min_cost_string_conversion.m


Functions
---------

.. autoapisummary::

   strings.min_cost_string_conversion.assemble_transformation
   strings.min_cost_string_conversion.compute_transform_tables


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

.. py:function:: assemble_transformation(ops: list[list[str]], i: int, j: int) -> list[str]

   Assembles the transformations based on the ops table.

   >>> ops = [['0', 'Ic', 'Iu', 'It'],
   ...        ['Dc', 'Cc', 'Iu', 'It'],
   ...        ['Da', 'Da', 'Rau', 'Rat'],
   ...        ['Dt', 'Dt', 'Rtu', 'Ct']]
   >>> x = len(ops) - 1
   >>> y = len(ops[0]) - 1
   >>> assemble_transformation(ops, x, y)
   ['Cc', 'Rau', 'Ct']

   >>> ops1 = [['0']]
   >>> x1 = len(ops1) - 1
   >>> y1 = len(ops1[0]) - 1
   >>> assemble_transformation(ops1, x1, y1)
   []

   >>> ops2 = [['0', 'I1', 'I2', 'I3'],
   ...         ['D1', 'C1', 'I2', 'I3'],
   ...         ['D2', 'D2', 'R23', 'R23']]
   >>> x2 = len(ops2) - 1
   >>> y2 = len(ops2[0]) - 1
   >>> assemble_transformation(ops2, x2, y2)
   ['C1', 'I2', 'R23']


.. py:function:: compute_transform_tables(source_string: str, destination_string: str, copy_cost: int, replace_cost: int, delete_cost: int, insert_cost: int) -> tuple[list[list[int]], list[list[str]]]

   Finds the most cost efficient sequence
   for converting one string into another.

   >>> costs, operations = compute_transform_tables("cat", "cut", 1, 2, 3, 3)
   >>> costs[0][:4]
   [0, 3, 6, 9]
   >>> costs[2][:4]
   [6, 4, 3, 6]
   >>> operations[0][:4]
   ['0', 'Ic', 'Iu', 'It']
   >>> operations[3][:4]
   ['Dt', 'Dt', 'Rtu', 'Ct']

   >>> compute_transform_tables("", "", 1, 2, 3, 3)
   ([[0]], [['0']])


.. py:data:: m