Data Refinery: transformating data
Project description
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.TupleOperations import wrap, keep, substitution
from datarefinery.CombineOperations import sequential
x2 = wrap(lambda x: x*2)
operation = sequential(keep(["name"]), substitution(["value"], x2))
(res, err) = operation({"name": "John", "value": 10})
print(res) # {"name": "John", "value": 20}
Documentation
Visit complete documentation at readthedocs.io.
Compatibility
Python: 3.5, 3.6
Contribute
Follow the steps on the how to contribute document.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
data-refinery-0.2.8.tar.gz
(10.0 kB
view hashes)
Built Distribution
Close
Hashes for data_refinery-0.2.8-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | f2bc7a225f3a0783ad7067993c752099125bd1a892dd28bf729c3db550959c8d |
|
MD5 | 7f5c10f3d08fbd4ed37796e57bffc376 |
|
BLAKE2b-256 | d78e24d1a34fbef48a14006ecd90150cb18156576cf307bb0e392915edaa384a |