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Data Refinery

The main goal of the library is perform a Transformation over a data event. Supports a variety of functions typically used on machine learning and AI.

Development is oriented into a functional style avoiding side effects on transformations.

Installation

In console pip install data-refinery or python setup.py install from sources.

Usage example

from datarefinery.tuple.TupleOperations import wrap, keep, substitution
from datarefinery.Tr import Tr

x2 = wrap(lambda x: x*2)

tr = Tr(keep(["name"])).then(substitution(["value"], x2))
operation = tr.apply()
(inp, res, err) = operation({"name": "John", "value": 10})
print(res) # {"name": "John", "value": 20}

Documentation

Visit complete documentation at github pages branch or at readthedocs.io.

Compatibility

Python: 3.5, 3.6

Contribute

Follow the steps on the how to contribute document.

Release files for data-refinery 0.1.63

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for data-refinery 0.1.63
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Table of built distributions (wheels) for data-refinery 0.1.63
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Total release size: 19.8 kB

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0.2.10

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