Metadata-Version: 2.1
Name: mPyPl
Version: 0.0.3.9
Summary: Monadic Pipeline Library for Python
Home-page: https://github.com/shwars/mPyPl
Author: Dmitri Soshnikov
Author-email: dmitri@soshnikov.com
License: MIT license
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Topic :: Software Development
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Description-Content-Type: text/markdown; charset=UTF-8
License-File: LICENSE

# mPyPl -- [Official Site](http://shwars.github.io/mPyPl)

## Monadic Pipeline Library for Python

This library was created by a team of enthusiastic software developers / data scientists at Microsoft, who
wanted to simplify tasks of data processing and creating complex data pipelines. The library is inspired
by the following main ideas:

 * Using functional approach to data processing (which implies immutability, lazy evaluation, etc.) 
 * Using [pipe](https://github.com/JulienPalard/Pipe) module in Python to achieve data pipelines similar to 
   [F#](http://fsharp.org).
 * Data pipeline uses dictionaries with different fields as base type, new operations would typically enrich data and add 
   new fields by using `apply` function. Those dictionaries are similar to *monads*, and `apply` is similar to *lift* operation
   on monads. Thus the naming of the library.

## Tutorial

You can [watch demo video](https://www.youtube.com/watch?v=EI1ZYZPcQyI), this [3 min intro](https://youtu.be/F1c_qQC4Wlw), or read project wiki.
   
## Credits

Principal developers of mPyPl:

 * [Dmitri Soshnikov](https://github.com/shwars)
 * [Yana Valieva](https://github.com/vJenny)
 * [Tim Scarfe](https://github.com/ecsplendid)
 
[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/shwars/mPyPl/master)


