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💫 Industrial-strength Natural Language Processing (NLP) in Python
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Matthew Honnibal cb95ef6934 * Fix download script
2015-01-30 19:28:43 +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 * Fix download script 2015-01-30 19:28:43 +11:00
tests * Add test for parse tree navigation 2015-01-30 18:02:58 +11:00
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.travis.yml * Change travis.yml to build from source, instead of from PyPi. PyPi checking will be done in a different branch. 2015-01-30 18:06:02 +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
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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 * Fix the way numpy headers are installed during compilation from source 2015-01-30 18:14:45 +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