def pipeline(liwc, bbapi, db, filter, blackboard, should_trim_rt,
indicator_resolution):
tweets = get_tweets(bbapi, filter, blackboard=blackboard) * extract()
if should_trim_rt:
tweets *= trim_rt()
if indicator_resolution == "category":
tweets *= liwc_tweets(liwc, normalize=True, compute_values=False)
elif indicator_resolution == "rule":
tweets *= rule_liwc_tweets(liwc, normalize=True)
else:
return
return tweets
def pipeline(liwc, bbapi, db, filter):
tweets = ( get_tweets(bbapi, filter)
* extract()
* liwc_tweets(liwc, normalize=False, compute_values=False))
return tweets
def pipeline(liwc, bbapi, db, filter):
tweets = (get_tweets(bbapi, filter) * extract() * liwc_tweets(liwc))
g = (tweets + once(None)) * accumulate(liwc)
return g
def pipeline(countrules, bbapi, db, filter):
tweets = (get_tweets(bbapi, filter) * extract() *
count_rules_docs(countrules))
return tweets