https://github.com/shwars/mPyPl

Monadic Pipeline Library for Python
https://github.com/shwars/mPyPl

Last synced: about 2 months ago
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Monadic Pipeline Library for Python

• Host: GitHub
• URL: https://github.com/shwars/mPyPl
• Owner: shwars
• License: mit
• Created: 2018-10-18T18:08:22.000Z (almost 6 years ago)
• Default Branch: master
• Last Pushed: 2022-10-13T12:48:10.000Z (almost 2 years ago)
• Last Synced: 2024-07-14T15:05:54.318Z (2 months ago)
• Language: Python
• Size: 3.42 MB
• Stars: 66
• Watchers: 5
• Forks: 7
• Open Issues: 1
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# 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)

 

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