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A Markov model trained on Internet Archive text files.

Project description

Create Markov models trained on Internet Archive text files.

  • Free software: BSD license


pip install ia-markov

Quick Start

from ia_markov import MarkovModel

m = MarkovModel()
'Courage, audacity, and revolt will be drunk with love and admiration for us.'


To run the all tests run:


Note, to combine the coverage data from all the tox environments run:

set PYTEST_ADDOPTS=--cov-append
PYTEST_ADDOPTS=--cov-append tox


0.3.1 (2018-10-14)

  • Added tests to sentence_split method - @danhenriquesc

0.3.0 (2018-10-05)

  • Added MarkovModel.make_sentence - @Abelarm
  • Use Spacy instead of NLTK for POS - @ex00
  • Added pipenv for dependency management - @alxwrd
  • Removed breaking coverage combine call in Travis CI build - @accraze

0.2.1 (2018-9-01)

  • Updated NLTK to v3.3
  • Updated markovify to v0.7.1
  • Updated internetarchive to 1.8.1

0.2.0 (2018-7-29)

  • Added ability to set custom hidden state sizes
  • Fix flaky model test

0.1.3 (2018-7-22)

  • EOL Py2.7 and Windows support
  • Fix docs CI build

0.1.2 (2018-7-21)

  • Test mocks when downloading corpus
  • Deprecate Windows/appveyor support

0.1.1 (2018-7-14)

  • Fixed failing flake8 check tests
  • Updated travis CI build config

0.1.0 (2016-11-27)

  • First release on PyPI.

Project details

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