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Nlpcleaner Build Status

Clean and prepare text for modeling with machine learning.

  • lower all
  • strip all
  • remove numbers
  • remove symbols
  • remove url
  • strip html tags
  • remove stopwords by detected language or passed language
  • lemming or stemming

Usage

from nlpcleaner import TextCleaner
TextCleaner(txt).clean()

Tests

pipenv install .
python setup.py test

Push on PyPi

python setup.py sdist
pip install twine
twine upload dist/*

TODO

  • Add tests to cover different cases and languages;
  • check performances

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Source Distribution

nlpcleaner-0.3.1.tar.gz (17.5 MB view details)

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  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.2.0 requests-toolbelt/0.9.1 tqdm/4.40.2 CPython/3.7.5

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