fntools

fntools

.. image:: https://readthedocs.org/projects/fntools/badge/?version=master

:target: https://readthedocs.org/projects/fntools/?badge=master :alt: Documentation Status

fntools provides functional programming tools for data processing. This module is a set of functions that I needed in my work and found useful.

Installation

::

pip install fntools

Examples

• Split a list of elements with factors with split::

  songs = ('Black', 'Even Flow', 'Amongst the waves', 'Sirens') albums = ('Ten', 'Ten', 'Backspacer', 'Lightning Bolt') print split(songs, albums) {'Lightning Bolt': ['Sirens'], 'Ten': ['Black', 'Even Flow'], 'Backspacer': ['Amongst the waves']}

• Determine whether any element of a list is included in another list with any_in::

  print any_in(['Oceans', 'Big Wave'], ['Once', 'Alive', 'Oceans', 'Release']) True

  print any_in(['Better Man'], ['Man of the Hour', 'Thumbing my way']) False

• Apply many functions on the data with dispatch::

  Suppose we want to know the mean, the standard deviation and the median of

  a distribution (here we use the standard normal distribution)

  import numpy as np np.random.seed(10) x = np.random.randn(10000)

  print dispatch(x, (np.mean, np.std, np.median)) [0.0051020560019149385, 0.98966401277169491, 0.013111308495186252]

Many more useful functions are available. For more details, go to the documentation_.

Inspirations

• The excellent toolz_ by Matthew Rocklin_
• A pratical introduction to functional programming_ by Mary Rose Cook_
• A bit of R_ (multimap, use, use_with)

.. _documentation: http://fntools.readthedocs.org/en/latest .. _toolz: https://github.com/mrocklin/toolz .. _A pratical introduction to functional programming: http://maryrosecook.com/blog/post/a-practical-introduction-to-functional-programming .. _Matthew Rocklin: https://github.com/mrocklin .. _Mary Rose Cook: https://github.com/maryrosecook .. _R: http://www.r-project.org