def __init__(self, brain_db, chain_length):
self.brain_db = brain_db
self.chain_length = chain_length
# Holds markov chain data. key(tuple(words[chain_length])) -> {word_choice1: count, word_choice2: count}
self.sqlite_dict = DatabaseDictionary(self.brain_db,
MARKOV_VALUE_PROPS,
MarkovDictionaryValue)
def load_brain(self):
print 'Brain loading...'
as_process(markov_dictionary_from_file,
(self.temp_db_file, self.brain_file, self.chain_length
)) # Shields main process from intermediate memory used
self.markov = DatabaseDictionary(self.temp_db_file, MARKOV_VALUE_PROPS)
print 'Brain loaded.'
print 'Markov dictionary has %i keys' % (len(self.markov), )
def sync_with_file(self, brain_file):
if len(self.sqlite_dict) > 0:
return
self.sqlite_dict.close()
as_process(markov_dictionary_from_file,
(self.brain_db, brain_file, self.chain_length))
self.sqlite_dict = DatabaseDictionary(self.brain_db,
MARKOV_VALUE_PROPS,
MarkovDictionaryValue)
def markov_dictionary_from_file(temp_db_file, brain_file, chain_length):
print 'Creating markov chains from %s' % brain_file
line_count = count_lines(brain_file)
temp_dict = {}
for c in xrange(1, chain_length + 1):
print 'Creating markov chains of length %i' % c
with open(brain_file, 'r') as f:
progress_bar = ProgressBar(line_count)
for line in f:
add_to_markov_dictionary(temp_dict, c,
line.strip().decode('utf-8').lower())
progress_bar.update()
print 'Populating database dictionary with markov chains'
db_dict = DatabaseDictionary(temp_db_file, MARKOV_VALUE_PROPS)
db_dict.begin()
db_dict.replace(temp_dict)
db_dict.commit()
db_dict.close()
