def process(id, text, author, wilbur):
statuses = author.timeline(count=200, include_rts=False)
fav_per_tweet, rt_per_tweet = stats.get_averages(statuses)
response = "Based on your last 200 tweets, you average %0.3f favorites and %0.3f retweets per tweet" % (fav_per_tweet, rt_per_tweet,)
# Store data in tweets collection
util.add_tweets(statuses, wilbur)
return response
def process(id, text, author, wilbur):
statuses = author.timeline(count=200, include_rts=False)
common_hour, pm_or_am = stats.get_hour(statuses)
response = "Based on your last 200 tweets, you are most active on twitter on the hour of " + str(
common_hour) + " " + pm_or_am + " EST"
# Store data in tweets collection
util.add_tweets(statuses, wilbur)
return response
def add_tracker(ticker):
ticker = ticker.upper()
fundamentals = {}
connection = util.connect_to_postgres()
cursor = connection.cursor()
try:
cursor.execute("CALL add_tracker(%s);", (ticker, ))
except Exception as e:
return {'error': str(e)}
if not util.add_daily_price_data(ticker, session, connection,
cursor) or not util.add_minute_price_data(
ticker, session, connection, cursor):
cursor.close()
connection.close()
return {'error': 'COULD NOT ADD PRICE DATA FOR' + ' ' + ticker}
try:
cursor.execute("SELECT * FROM Fundamentals WHERE ticker = %s",
(ticker, ))
except Exception as e:
return {'error': str(e)}
fundamentals = cursor.fetchone()
util.add_tweets(ticker, fundamentals[1], TWEEPY_API, session, connection,
cursor)
util.add_news_articles(ticker, session, connection, cursor)
col_ref = mongo_db['Live_Stock_Prices']
daily_prices = util.get_past_week_prices_mongo(ticker, session)
if daily_prices:
connection.commit()
cursor.close()
connection.close()
new_tracker = {
'ticker': ticker,
'name': fundamentals[1],
'industry': fundamentals[2],
'sector': fundamentals[3],
'market_cap': fundamentals[4],
'description': fundamentals[5],
'daily_prices': daily_prices,
'minute_prices': [],
'prev_ema': [-1] * 391,
'ema_volume': [-1] * 391,
'minute_volume': [-1] * 391
}
col_ref.insert_one(new_tracker)
else:
cursor.close()
connection.close()
return {'error': 'Failed to add {}!'.format(ticker)}
return {'success': 'Successfully added {}!'.format(ticker)}
def process(id, text, author, wilbur):
statuses = author.timeline(count=200, include_rts=False)
# Part 1 = Get statistical data for reports
fav_per_tweet, rt_per_tweet = stats.get_averages(statuses)
# Round our numbers
fav_per_tweet = round(fav_per_tweet, 3)
rt_per_tweet = round(rt_per_tweet, 3)
emoji = stats.get_emoji(statuses)
hour = str(stats.get_hour(statuses)[0]) + " " + stats.get_hour(statuses)[1]
word_count = stats.get_word_count(statuses)
mention_count = stats.get_mention_count(statuses)
sorted_words = sorted(word_count.iteritems(),
key=operator.itemgetter(1),
reverse=True)[:5]
sorted_mention = sorted(mention_count.iteritems(),
key=operator.itemgetter(1),
reverse=True)[:5]
most_used_words = []
for word in sorted_words:
most_used_words.append(word[0])
most_mentioned = []
for mention in sorted_mention:
most_mentioned.append(mention[0])
# Part 2 = Store data in reports collection
data = {
'twitterHandle': author.screen_name,
'avgFavorites': fav_per_tweet,
'avgRetweets': rt_per_tweet,
'mostUsedEmoji': emoji,
'mostActiveHour': hour,
'mostUsedWords': most_used_words,
'mostMentioned': most_mentioned,
'updated': datetime.datetime.now().strftime("%m/%d %H:%M")
}
wilbur.reports.update({'twitterHandle': author.screen_name},
{"$set": data},
upsert=True)
response = "View your report at http://wilbur.wilhelmwillie.com/report/" + author.screen_name
# Part 3 = Store data in tweets collection
util.add_tweets(statuses, wilbur)
return response
def process(id, text, author, wilbur):
statuses = author.timeline(count=200, include_rts=False)
fav_per_tweet, rt_per_tweet = stats.get_averages(statuses)
response = "Based on your last 200 tweets, you average %0.3f favorites and %0.3f retweets per tweet" % (
fav_per_tweet,
rt_per_tweet,
)
# Store data in tweets collection
util.add_tweets(statuses, wilbur)
return response
def update_tweets(ticker, company_name):
ticker = ticker.upper()
connection = util.connect_to_postgres()
cursor = connection.cursor()
try:
cursor.execute("CALL remove_tweets(%s);", (ticker, ))
except Exception as e:
return {'error': str(e)}
util.add_tweets(ticker, company_name, TWEEPY_API, session, connection,
cursor)
connection.commit()
cursor.close()
connection.close()
return {'success': 'Successfully updated news for {}!'.format(ticker)}
def process(id, text, author, wilbur):
statuses = author.timeline(count=200, include_rts=False)
emoji = stats.get_emoji(statuses)
if emoji == "N/A":
response = "Based on your last 200 tweets, you don't seem to use emojis at all"
else:
response = "Based on your last 200 tweets, your most used emoji is " + emoji
# Store data in tweets collection
util.add_tweets(statuses, wilbur)
return response
def process(id, text, author, wilbur):
statuses = author.timeline(count=200, include_rts=False)
emoji = stats.get_emoji(statuses)
if emoji == "N/A":
response = "Based on your last 200 tweets, you don't seem to use emojis at all"
else:
response = "Based on your last 200 tweets, your most used emoji is " + emoji
# Store data in tweets collection
util.add_tweets(statuses, wilbur)
return response
def process(id, text, author, wilbur):
statuses = author.timeline(count=200, include_rts=False)
mention_count = stats.get_mention_count(statuses)
if len(mention_count) == 0:
response = "Based on your last 200 tweets, you don't talk to anyone on twitter"
else:
most_mentioned = max(mention_count.iteritems(), key=operator.itemgetter(1))[0]
response = "Based on your last 200 tweets, you mention @%s the most (%i)" % (most_mentioned,mention_count[most_mentioned],)
# Store data in tweets collection
util.add_tweets(statuses, wilbur)
return response
def process(id, text, author, wilbur):
statuses = author.timeline(count=200, include_rts=False)
word_count = stats.get_word_count(statuses)
most_used_words = sorted(word_count.iteritems(), key=operator.itemgetter(1), reverse=True)[:5]
response = "Based on your last 200 tweets, your " + str(len(most_used_words)) + " most used words are "
for i in range(len(most_used_words)):
response = response + "'" + most_used_words[i][0] + "' "
# Store data in tweets collection
util.add_tweets(statuses, wilbur)
return response
def process(id, text, author, wilbur):
statuses = author.timeline(count=200, include_rts=False)
word_count = stats.get_word_count(statuses)
most_used_words = sorted(word_count.iteritems(),
key=operator.itemgetter(1),
reverse=True)[:5]
response = "Based on your last 200 tweets, your " + str(
len(most_used_words)) + " most used words are "
for i in range(len(most_used_words)):
response = response + "'" + most_used_words[i][0] + "' "
# Store data in tweets collection
util.add_tweets(statuses, wilbur)
return response