Skip to content

Instantly share code, notes, and snippets.

What would you like to do?
Generate random words based on markov chains rather than random sentences.
#!/usr/bin/env python
import random
class Markov:
def __init__(self, file, size):
self.size = size
self.starts = []
self.cache = {}
def file_to_words(self, file):
data =
self.words = data.split("\n")
def tuples(self, word):
if len(word) < self.size - 1:
word = word + "\n"
for i in range(len(word) - self.size):
yield (word[i:i+self.size], word[i+self.size])
def parse_words(self):
for word in self.words:
for key, next in self.tuples(word):
if key in self.cache:
self.cache[key] = [next]
def generate_word(self):
key = random.choice(self.starts)
word = key
next = random.choice(self.cache[key])
while next != "\n":
word = word + next
key = key[1:] + next
next = random.choice(self.cache[key])
return word
from optparse import OptionParser
def main():
parser = OptionParser()
parser.add_option('-p', type='int', dest='prev_num', default=3,
help='number of previous letters to base chain on')
parser.add_option('-n', type='int', dest='num', default=5,
help='number of generated words')
parser.add_option('-s', '--source-text', type='string',
default='wordlist-en.txt', dest='source',
help='file to use as basis for generating the words')
(options, args) = parser.parse_args()
file = open(options.source)
markov = Markov(file, options.prev_num)
for i in range(options.num):
print markov.generate_word()
if __name__ == '__main__':

This comment has been minimized.

Copy link
Owner Author

Eckankar commented Apr 8, 2010

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
You can’t perform that action at this time.