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)
