Markov Speaking （马尔科夫链随机文本生成）
This project is an package generating random sentences by markov chain. If you have any problems/ideas, please email me, or open your PR. I feel honored to learn from your help.
markov_speaking.py is written in
Python 2.7, using
re. You need to install
pip2 install jieba.
markov_speaking.pyprovides a class
__init__(self, filepath = None, mode = 0, coding="utf8").
filepathis the file you want to parse, and the sentences the class build will base on this file.
modeis 0 if you want to parse English, and 1 if Chinese.
codingassigns the codec, default is UTF-8.
pbe a instance of
Markov, you can use
p.train(self, filepath = '', mode = 0, coding="utf8")to regenerate the instance.
- After you have built
pand trained, you can use
p.say(length)to generate a random sentence. The length is the max length of sentence to generate, default is 10.
Examples For Use
>>> import markov_speaking >>> p = markov_speaking.Markov('swords.txt', 1) Building prefix dict from the default dictionary ... Loading model from cache /home/forec/cache Dumping model to file cache /home/forec/cache Loading model cost 1.578 seconds. Prefix dict has been built succesfully. >>> p.say(5) 忽然想到一计说道师伯令狐师兄行侠仗义。
- 2016-10-10: Add project and build repository.
- 2016-10-11: Fix problems in English part: Not split words by sentences.
- 2016-10-12: Fix train function.
- 2016-10-13: Remove useless chinese upper condition.
All codes in this repository are licensed under the terms you may find in the file named "LICENSE" in this directory.