class PykuEbooks:
"""Generate Markov Chain haikus from Reddit source material"""
def __init__(self, ml, subreddit, location):
"""Initialize the Markov Chain and writer
ml:
MarkovChain's max_links
subreddit:
The subreddit to use as the text source
location:
"posts"|"comments" - Whether to get the text from the top posts in
the subreddit (faster), or from the children comments of the top
posts in the subreddit (can return more text).
sources:
An array of strings for the MC
"""
rr = RedditReader(subreddit)
if location == "posts":
texts = rr.get_many_post_bodies()
elif location == "comments":
texts = rr.get_many_comment_bodies()
else:
raise TypeError('`location` must be either "posts" or "comments"')
self.mc = MarkovChain(ml)
for text in texts:
self.mc.add_text(text)
self.w = Writer(self.mc)
def haiku(self):
return self.w.haiku()
filterer = self.__filterer(maximum, before, first, last)
word_tuples = self.markov_chain.chain_from_words(before)
return [wt for wt in word_tuples if filterer(wt)]
def __filterer(self, maximum, before, first, last):
"""Create a word filterer that can be used for many words"""
def filt(wt):
"""Determine if this word tuple is appropriate or not"""
w, s = wt
if s > maximum:
return False
if first and (not self.FIRST_QUERY.match(w)):
return False
if last and s == maximum and (not self.LAST_QUERY.search(w)):
return False
if not last and s == maximum and (not self.LINE_END_QUERY.search(w)):
return False
return True
return filt
if __name__ == "__main__":
mc = MarkovChain(2)
mc.add_text("This is a haiku. Written today (of all days). And it's not finished. This is a haiku. Written today (of all days). And it's not finished.")
w = Writer(mc)
print(w.haiku())
