fntools 1.1.1

Functional programming tools for data processing

target:

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

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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)