=========== cpmoptimize

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Description

This library provides a decorator that disassembles the function's bytecode, checks if it calculates linear recurrences, and tries to reduce the algorithm's time complexity from O(n) to O(log n) using the fast matrix exponentiation_.

.. _fast matrix exponentiation: https://en.wikipedia.org/wiki/Exponentiation_by_squaring

Detailed description: Russian_, English_.

.. _English: http://kukuruku.co/hub/algorithms/automatic-algorithms-optimization-via-fast-matrix-exponentiation .. _Russian: http://habrahabr.ru/post/236689/

Inspired by the Alexander Skidanov's optimizing interpreter.

.. _Alexander Skidanov: https://github.com/SkidanovAlex .. _optimizing interpreter: https://github.com/SkidanovAlex/interpreter

Update (Feb 2022): This library was created in 2014 and only supports Python 2.6-2.7 (not Python 3). I don't plan to upgrade it myself but I'd be happy to help anyone willing to do that (this is a good exercise to understand how it works). If you're interested, please open an issue.

Example

Suppose we want to calculate the ten millionth Fibonacci number_ in Python. The function with a trivial algorithm is rather slow:

.. code:: python

def fib(n):
    a = 0
    b = 1
    for i in xrange(n):
        a, b = b, a + b
    return a

result = fib(10 ** 7)

# Time: 25 min 31 sec

But if we apply the optimizing decorator, the function will give you the answer much faster:

.. code:: python

from cpmoptimize import cpmoptimize

@cpmoptimize()
def fib(n):
    a = 0
    b = 1
    for i in xrange(n):
        a, b = b, a + b
    return a

result = fib(10 ** 7)

# Time: 18 sec (85x faster)

.. _Fibonacci number: https://en.wikipedia.org/wiki/Fibonacci_number

Installation

You can install the stable version of the library using pip::

sudo pip install cpmoptimize

Or install a previously downloaded and extracted package::

sudo python setup.py install

Author

Copyright (c) 2014, 2015 Alexander Borzunov