def request_Key_Word_Classifier(submission, phrase_set):
'''
This is a hand made feature set to id titles that make reddit-typical
requests for help, but might not phrase the request as a question
'''
text = ' '.join(summarizeText.parseStringSimple01(submission.title))
# Pass phrase_set through string parser and back, it'll help?
#phrase_set = botHelperFunctions.load_autoreply_key_phrases(fl_path='misc/autoreplyKeyPhrases.txt')
'''
phrase_set = ['need help', '[help]', '[ help ]', '[question]',
'[ question ]', 'noob ', 'n00b ', ' newb','please help',
'noobie question', 'help!', 'help me', "isn't working",
'not working', 'issues with', 'issue with',
'looking for tutorial', 'Quick question', 'help needed',
'plz help', "what's wrong", "need some help", '[q]',
'[Beginner Question]']
'''
request_Made = False
#print text
for phrase in phrase_set:
if ' '.join(summarizeText.parseStringSimple01(phrase)).lower() in text:
logging.info(phrase + " Was used in the post title")
request_Made = True
break
#if submission.id not in submission.url:
# Links off site
# This check was not in early versions of the bot (v pa0.1.01 and earlier)
# logging.debug( '\t'+'Results: Error. Classification is dead, (URL) Mismatch. ')
# request_Made = False
return request_Made
def xrequest_Key_Word_Filter(submission, phrase_set):
'''
This is a hand made feature set to id titles that make reddit-typical
requests for help, but might not phrase the request as a question
'''
# Consider adding a time delay here?
text = ' '.join(summarizeText.parseStringSimple01(submission.title))
# Pass phrase_set through string parser and back, it'll help?
#phrase_set = botHelperFunctions.load_autoreply_key_phrases(fl_path='misc/autoreplyKeyPhrases.txt')
'''
phrase_set = ['need help', '[help]', '[ help ]', '[question]',
'[ question ]', 'noob ', 'n00b ', ' newb','please help',
'noobie question', 'help!', 'help me', "isn't working",
'not working', 'issues with', 'issue with',
'looking for tutorial', 'Quick question', 'help needed',
'plz help', "what's wrong", "need some help", '[q]',
'[Beginner Question]']
'''
request_Made = False
#print text
for phrase in phrase_set:
if ' '.join(summarizeText.parseStringSimple01(phrase)).lower() in text:
logging.info(phrase + " Was used in the post title")
request_Made = True
break
if request_Made:
text = summarizeText.parseStringSimple01(submission.selftext)
sents = nltk.sent_tokenize(' '.join(text))
# Returning the last sentence is chosen purely based on a guess
# It'll be more useful to select sents based on idf and entropy score
try:
return sents[-1]
except:
logging.info(
"Failed to grab last sentence: Probably links offsite")
pass
return False
def basicQuestionClassify(submission, classifier):
"""
A really simple classifier. if a submission is old enough, has low enough votes
and asks a question, it's treated as a basic question that r/learnpython is
better suited for.
Parameters
----------
submission : praw submission object
user : praw user object
classifier : nltk classifier object
tdm : term document matrix object
Returns
-------
Notes
-----
It's not what I want, but it'll force me to
References
----------
Examples
--------
"""
#title = summarizeText.parseStringSimple01(submission.title)
#text = summarizeText.parseStringSimple01(submission.selftext)
#postText = title + text
postAge = datetime.datetime.utcnow() - submission.created_utc
hours2 = datetime.timedelta(hours=2)
#logging.debug( '\t'+"Post Age: "+ str(postAge) )
votes = submission.score
upvoteRatio = submission.upvote_ratio
#print title
#logging.debug( '\t'+ "Votes: "+ str(votes))
#logging.debug( '\t'+ "Upvote Ratio: "+str( upvoteRatio))
if postAge < hours2:
return False
if votes > 0:
return False
if upvoteRatio > 0.41:
return False
if submission.id not in submission.url:
# Links off site
logging.debug( '\t'+'Results: Error. Classification is dead, (URL) Mismatch. ')
return False
# ID if a question is here right now
title = summarizeText.parseStringSimple01(submission.title, removeURL=True)
text = summarizeText.parseStringSimple01(submission.selftext, removeURL=True)
postText = title + text
sents = nltk.sent_tokenize(' '.join(postText))# nltk.sent_tokenize(title) + nltk.sent_tokenize(text)
#print " ".join(sents)
question_Sents = []
for sent in sents:
#sentDisplay = ' '.join(sent.strip().split('\n'))
#print '\t', sentDisplay.strip()
classified = questionIdentifier.classifyString(sent, classifier)
#print classified
if "question" in classified.lower():
question_Sents.append(sent)
logging.debug(str(classified) +': '+ str(sent))
print('\tSentence: ', sent)
print('\tClassified As: ', classified)
#print '\t', classified
if len(question_Sents) > 0:
logging.info('|'.join(question_Sents))
return question_Sents
logging.debug("\tNo Question Identified")
# All else
return False