def test_update_new_result(self): dao_analyzed_tweets = AnalyzedTweets(self.client, self.database_name) dao_analyzed_tweets.save_new_analyzed_tweet(1234, 1234, ["PP", "PSOE"], ["@mariano", "@rajoy"], {"type": "Point", "coordinates": [-77.01944444, -12.12083333]}, str(int(time.time())), place_example, 0, "esto es una fiesta @mariano @rajoy") self.assertEqual(dao_analyzed_tweets.get_size(), 1)
from pymongo import MongoClient from DAOAnalyzedTweets import AnalyzedTweets client = MongoClient("127.0.0.1", 27017, connect=True) database_name = "Test" dao_analyzed_tweets = AnalyzedTweets(client, database_name) result = dao_analyzed_tweets.get_first_and_last_timestamp() print result
def test_timestamp_query(self): dao_analyzed_tweets = AnalyzedTweets(self.client, self.database_name) dao_analyzed_tweets.save_new_analyzed_tweet(1111, 1111, ["PP", "PSOE"], ["@mariano", "@rajoy"], {"type": "Point", "coordinates": [-77.01944444, -12.12083333]}, str(int(time.time())), place_example, 0, "esto es una fiesta @mariano @rajoy") time.sleep(1) start_query = long(time.time()) dao_analyzed_tweets.save_new_analyzed_tweet(2222, 2222, ["PP", "PSOE"], ["@mariano", "@rajoy"], {"type": "Point", "coordinates": [-77.01944444, -12.12083333]}, str(int(time.time())), place_example, 1, "esto es una fiesta @mariano @rajoy") dao_analyzed_tweets.save_new_analyzed_tweet(3333, 3333, ["PP", "PSOE"], ["@mariano", "@rajoy"], {"type": "Point", "coordinates": [-77.01944444, -12.12083333]}, str(int(time.time())), place_example, 1, "esto es una fiesta @mariano @rajoy") dao_analyzed_tweets.save_new_analyzed_tweet(4444, 4444, ["PP", "PSOE"], ["@mariano", "@rajoy"], {"type": "Point", "coordinates": [-77.01944444, -12.12083333]}, str(int(time.time())), place_example, 1, "esto es una fiesta @mariano @rajoy") dao_analyzed_tweets.save_new_analyzed_tweet(5555, 5555, ["PP", "PSOE"], ["@mariano", "@rajoy"], {"type": "Point", "coordinates": [-77.01944444, -12.12083333]}, str(int(time.time())), place_example, 1, "esto es una fiesta @mariano @rajoy") end_query = int(time.time()) time.sleep(1) dao_analyzed_tweets.save_new_analyzed_tweet(6666, 6666, ["PP", "PSOE"], ["@mariano", "@rajoy"], {"type": "Point", "coordinates": [-77.01944444, -12.12083333]}, str(int(time.time())), place_example, 1, "esto es una fiesta @mariano @rajoy") result_size = dao_analyzed_tweets.get_analyzed_tweets_by_dates(start_query, end_query).count() self.assertEqual(dao_analyzed_tweets.get_size()-2, result_size)