def load_tweets_to_grids(): # mongodb mg = MongoDB() mg.connect() tweets = mg.find() grid_db = GridDB() grid_db.add(tweets) return grid_db
def all_grids(): mg = MongoDB() mg.connect() griddb = GridDB() print('querying grid volumes...') results = mg.group_by([{'$match': {'created_at': {'$gt': datetime.strptime('2012-10-15T20:00:02Z', '%Y-%m-%dT%H:%M:%SZ'), '$lt': datetime.strptime('2012-11-15T20:00:02Z', '%Y-%m-%dT%H:%M:%SZ')}}}]) # print(results) griddb.add(results) ret = Grid.get_raw_pandas_ts(results, 'D') STL.seasonal_decomposition(ret)