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.
1 maintainer
Metadata
1 maintainer
Release files for data-refinery 0.1.63
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