def load_index(self, fn):
"""
Loads a pre-computed index (or indices) so we can answer queries.
Input:
fn - file name of pickled index.
"""
return utils.load_obj(name=fn)
def update_tweets_postings(self):
"""
:return:
"""
for i in range(self.tweets_postings_counter):
tweets_postings_file = utils.load_obj(
str(i + 1), self.config.get_tweets_postings_path())
for doc_id in tweets_postings_file.keys():
tweet_posting = tweets_postings_file[doc_id]
self.update_single_tweet_postings(tweet_posting)
utils.save_obj(tweets_postings_file, str(i + 1),
self.config.get_tweets_postings_path())
def get_relevant_tweets_postings(self, relevant_tweets):
"""
iterates over tweets postings and extracts postings of all relevant tweets.
:param relevant_tweets: set of relevant tweets based on query's terms
:return: postings of every relevant tweet.
"""
relevant_tweets_information = dict()
for i in range(self._indexer.get_tweets_postings_counter()):
tweets_postings_file = utils.load_obj(
str(i + 1),
self._indexer.get_config().get_tweets_postings_path())
for doc_id in relevant_tweets:
if doc_id in tweets_postings_file.keys():
relevant_tweets_information[doc_id] = tweets_postings_file[
doc_id]
return relevant_tweets_information