Metadata-Version: 2.1
Name: mPyPl
Version: 0.0.3.7
Summary: Monadic Pipeline Library for Python
Home-page: https://github.com/shwars/mPyPl
Author: Dmitri Soshnikov
Author-email: dmitri@soshnikov.com
License: MIT license
Description: # 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)
         
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
