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💫 Industrial-strength Natural Language Processing (NLP) in Python
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Matthew Honnibal 0981d68022 * Set a sent_end flag during parsing, for later use
2015-01-31 13:41:46 +11:00
bin/parser * Allow parsers and taggers to be trained on text without gold pre-processing. 2015-01-30 16:36:24 +11:00
docs * Add draft work on features 2015-01-30 16:46:52 +11:00
spacy * Set a sent_end flag during parsing, for later use 2015-01-31 13:41:46 +11:00
tests * Don't load parser in test_pre_punct 2015-01-30 20:11:47 +11:00
.gitignore * Upd gitignore 2015-01-30 16:49:44 +11:00
.travis.yml * Upd travis.yml 2015-01-30 20:27:35 +11:00
dev_setup.py * Upd dev_setup 2015-01-03 21:02:03 +11:00
fabfile.py * Fix clean command 2015-01-25 14:49:29 +11:00
LICENSE.txt * Add license file 2015-01-26 03:07:18 +11:00
MANIFEST.in * Add manifest file 2015-01-30 16:49:02 +11:00
README.md Update README.md 2015-01-27 21:55:36 +11:00
requirements.txt * Upd requirements 2015-01-25 23:01:42 +11:00
setup.py * Handle failure when numpy headers are already installed correctly 2015-01-30 19:48:19 +11:00

README.md

spaCy

http://honnibal.github.io/spaCy

Fast, state-of-the-art natural language processing pipeline. Commercial licenses available, or use under AGPL.

Tested (and working) with:

  • CPython 2.7
  • CPython 3.4
  • OSX
  • Linux

Untested:

  • Windows

Fails with:

  • PyPy 2.7
  • PyPy 3.4