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linter fixes for markov library methods

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This commit is contained in:
Brian S. Stephan 2023-02-16 16:29:48 -06:00
parent 8b3caabb57
commit e27087a86b
Signed by: bss
GPG Key ID: 3DE06D3180895FCB
1 changed files with 15 additions and 21 deletions
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36
markov/lib.py
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@ -1,17 +1,16 @@
"""Provide methods for manipulating markov chain processing."""
import logging
import random
from random import SystemRandom as sysrand
from django.db.models import Sum
from markov.models import MarkovContext, MarkovState, MarkovTarget
log = logging.getLogger('markov.lib')
log = logging.getLogger(__name__)
def generate_line(context, topics=None, min_words=15, max_words=30, sentence_bias=2, max_tries=5):
"""String multiple sentences together into a coherent sentence."""
"""Combine multiple sentences together into a coherent sentence."""
tries = 0
line = []
min_words_per_sentence = min_words / sentence_bias
@ -23,7 +22,7 @@ def generate_line(context, topics=None, min_words=15, max_words=30, sentence_bia
else:
if len(line) > 0:
if line[-1][-1] not in [',', '.', '!', '?', ':']:
line[-1] += random.choice(['?', '.', '!'])
line[-1] += sysrand.choice(['?', '.', '!'])
tries += 1
@ -33,7 +32,6 @@ def generate_line(context, topics=None, min_words=15, max_words=30, sentence_bia
def generate_longish_sentence(context, topics=None, min_words=15, max_words=30, max_tries=100):
"""Generate a Markov chain, but throw away the short ones unless we get desperate."""
sent = ""
tries = 0
while tries < max_tries:
@ -52,20 +50,19 @@ def generate_longish_sentence(context, topics=None, min_words=15, max_words=30,
def generate_sentence(context, topics=None, min_words=15, max_words=30):
"""Generate a Markov chain."""
words = []
# if we have topics, try to work from it and work backwards
if topics:
topic_word = random.choice(topics)
topic_word = sysrand.choice(topics)
topics.remove(topic_word)
log.debug("looking for topic '{0:s}'".format(topic_word))
log.debug("looking for topic '%s'", topic_word)
new_states = MarkovState.objects.filter(context=context, v=topic_word)
if len(new_states) > 0:
log.debug("found '{0:s}', starting backwards".format(topic_word))
log.debug("found '%s', starting backwards", topic_word)
words.insert(0, topic_word)
while len(words) <= max_words and words[0] != MarkovState._start2:
log.debug("looking backwards for '{0:s}'".format(words[0]))
log.debug("looking backwards for '%s'", words[0])
new_states = MarkovState.objects.filter(context=context, v=words[0])
# if we find a start, use it
if MarkovState._start2 in new_states:
@ -87,7 +84,7 @@ def generate_sentence(context, topics=None, min_words=15, max_words=30):
i = len(words)
while words[-1] != MarkovState._stop:
log.debug("looking for '{0:s}','{1:s}'".format(words[i-2], words[i-1]))
log.debug("looking for '%s','%s'", words[i-2], words[i-1])
new_states = MarkovState.objects.filter(context=context, k1=words[i-2], k2=words[i-1])
log.debug("states retrieved")
@ -103,7 +100,7 @@ def generate_sentence(context, topics=None, min_words=15, max_words=30):
words.append(MarkovState._stop)
elif len(target_hits) > 0:
# if there's a target word in the states, pick it
target_hit = random.choice(target_hits)
target_hit = sysrand.choice(target_hits)
log.debug("found a topic hit %s, using it", target_hit)
topics.remove(target_hit)
words.append(target_hit)
@ -129,7 +126,6 @@ def generate_sentence(context, topics=None, min_words=15, max_words=30):
def get_or_create_target_context(target_name):
"""Return the context for a provided nick/channel, creating missing ones."""
target_name = target_name.lower()
# find the stuff, or create it
@ -156,7 +152,6 @@ def get_or_create_target_context(target_name):
def get_word_out_of_states(states, backwards=False):
"""Pick one random word out of the given states."""
# work around possible broken data, where a k1,k2 should have a value but doesn't
if len(states) == 0:
states = MarkovState.objects.filter(v=MarkovState._stop)
@ -168,9 +163,9 @@ def get_word_out_of_states(states, backwards=False):
# this being None probably means there's no data for this context
raise ValueError("no markov states to generate from")
hit = random.randint(0, count_sum)
hit = sysrand.randint(0, count_sum)
log.debug("sum: {0:d} hit: {1:d}".format(count_sum, hit))
log.debug("sum: %s hit: %s", count_sum, hit)
states_itr = states.iterator()
for state in states_itr:
@ -183,13 +178,12 @@ def get_word_out_of_states(states, backwards=False):
break
log.debug("found '{0:s}'".format(new_word))
log.debug("found '%s'", new_word)
return new_word
def learn_line(line, context):
"""Create a bunch of MarkovStates for a given line of text."""
log.debug("learning %s...", line[:40])
words = line.split()
@ -200,7 +194,7 @@ def learn_line(line, context):
return
for i, word in enumerate(words):
log.debug("'{0:s}','{1:s}' -> '{2:s}'".format(words[i], words[i+1], words[i+2]))
log.debug("'%s','%s' -> '%s'", words[i], words[i+1], words[i+2])
state, created = MarkovState.objects.get_or_create(context=context,
k1=words[i],
k2=words[i+1],