Generate random words based on Markov chains
Gibi is a random word generator, based on Markov chains.
It analyzes a text in order to deduce the probability of transition from one character to another, and then generates a completely random word that will look alike what you have feeded it as input.
Gibi can be used either as a CLI tool, either as a library.
The very simple rand_word.py will analyze any text file, and generate a random word based on it.
$ rand_word.py french_cities.txt jambous-dirchetomeilla
The best way to see how to use the API is to look how rand_word.py works:
with codecs.open(path, 'r', encoding='utf-8') as f: n = FrenchNormalizer(f) m = Matrix() m.feed(n) print(m.make_word())
You can also make something deterministic by providing a seed to make_word(). Given the same Matrix and the same seed, you will always get the same result. The provided seed is anything that Python’s random would accept. See the following example:
assert m.make_word(42) == m.make_word(42)
This project is written and copyrighted by its authors, as the Git log can testify.
It is released under the terms of the WTFPL. Please refer to the COPYING file for more information.
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