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A toy Markov chain implementation.

Project description

Vokram is a toy Markov chain library that is most likely implemented incorrectly and extremely inefficiently.

Installation

Use pip to install:

pip install vokram

Usage

Command Line Usage

Pipe a body of text into vokram and it will generate some (hopefully) plausible sentences synthesized from that body of text:

$ cat the_art_of_war.txt | vokram
Spies cannot be obtained inductively from experience, nor by any danger.

You can control the maximum number of words in the output and the n-gram size used when building the Markov model. All command line options are given below:

$ vokram --help

Outputs:

usage: vokram [-h] [-w NUM_WORDS] [-n NGRAM_SIZE]

Generates plausible new sentences from a corpus provided on STDIN.

optional arguments:
  -h, --help            show this help message and exit
  -w NUM_WORDS, --num-words NUM_WORDS
                        Maximum number of words in the resulting sentence.
  -n NGRAM_SIZE, --ngram-size NGRAM_SIZE

Library Usage

Vokram can also be used as a plain old Python library:

>>> import vokram
>>> corpus = open('the_art_of_war.txt')
>>> model = vokram.build_word_model(corpus, 2)
>>> vokram.markov_words(model, 25))
'Hence it is not supreme excellence; supreme excellence consists in breaking the enemy's few.'

Credits

Vokram was made with inspiration from this simple and approachable Python implementation and explanation.

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