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