def get_tweet_list():
tweets: List[Status] = TweepyWrapper().get_trending_tweets_in_LA(limit=10)
result = []
for t in tweets:
tweet = Tweet.parse_from_status(t)
result.append(tweet.__dict__)
return result
def get_similar_tweets(tweet_id):
print(tweet_id)
print("==============================")
tweets = []
# get the tweet
tweet = TweepyWrapper().get_tweet(tweet_id)
original = Tweet.parse_from_status(tweet)
# extract entities
entities: List[str] = get_entities(original.text)
retry_count = 0
limit = 5
while len(tweets) < limit and retry_count < 5:
# find tweets with entities
statuses = []
for entity in entities:
statuses.extend(TweepyWrapper().get_tweets_by_keyword(
keyword=entity, limit=15))
potential_tweets: List[Tweet] = [
Tweet.parse_from_status(t) for t in statuses
]
# filter similarities
#print(len(tweets), retry_count, "===========================================")
for potential_tweet in potential_tweets:
similarity = sentence_distance.similarity(original.text,
potential_tweet.text)
#print(similarity)
# todo judge whether eligible
tweets.append(potential_tweet.__dict__)
if len(tweets) > limit:
break
# repeat if less than 15
retry_count += 1
return jsonify(tweets)