def test_date_time_binance_diff(self):
bapi = BinanceApi()
date_1 = datetime.strptime("2018-06-01 09:48:02", "%Y-%m-%d %H:%M:%S")
date_2 = datetime.strptime("2018-05-01", "%Y-%m-%d")
diff = bapi.get_diff_in_hours(date_1, date_2)
print('diff: ', diff)
def test_dateutil1(self):
dateutil = DateUtil()
ba = BinanceApi()
print(ba.get_server_time())
nowdt = datetime.now()
nowdt = nowdt + timedelta(hours=-2)
binancedt_int = dateutil.binance_datetime_int(nowdt)
print("binancedt_int ", binancedt_int)
def test_date_time_binance3(self):
bapi = BinanceApi()
coin = Coin()
coin.name = 'OMG'
one_day_before = datetime.now() + timedelta(days=-1)
coin.loadtime = one_day_before.strftime("%Y-%m-%d")
spech = datetime.now() + timedelta(hours=-1)
print("spec_closed_hour: ")
pricehourly = bapi.collect_coindata(coin, spech)
print(pricehourly)
def test_date_time_binance2(self):
bapi = BinanceApi()
coin = Coin()
coin.name = 'OMG'
spech = datetime.now() + timedelta(hours=-1)
print("spec_closed_hour: ")
json_spec_hour = bapi.get_last_n_hour_by_specific_hour_by_coin(
coin, spech, 1)
self.print_unix_as_date(json_spec_hour[0][0])
self.print_unix_as_date(json_spec_hour[0][6])
print(json_spec_hour)
def do_prepare(coin, specific_hour):
pd.set_option('display.max_rows', 99)
pd.set_option('precision', 10)
pd.set_option('display.width', 1000)
#Getting Tweets from DB
tweetio = TweetIO()
df = tweetio.read_db_tweet_last_n_hour_by_specific_hour_by_coin(
coin, specific_hour)
coin.tweets = df
print("tweets from DB: ")
print(len(df))
#Filter and sort tweets
#tapi = TwitterApi() we dont need twitter connection:
tweetcollector = TweetCollector(None)
df = tweetcollector.filter_tweets(coin.tweets)
df = tweetio.sort_and_clip(df, coin.loadtime)
coin.tweets = df
print("tweets>: ")
print(len(df))
#Collect retweets, users
rdf = tweetio.read_db_retweet_last_n_hour_by_specific_hour_by_coin(
coin, specific_hour)
setattr(coin, 'retweets', rdf)
print("retweets>: ")
#print(rdf)
udf = tweetio.read_db_referenced_users(coin)
print("Users>: ")
print(len(udf))
#tweetcollector.collect_all_users(coin, tapi, tmpdir=tmpd)
##PREPARE 1
#df = tweetio.read_all_scraped_retweet(coin, tmpd)
## MERGING TWEET FOLLOWERS
#tweetio.read_users_for_tweets(coin, tmpd)
print("nr. of tweets before merge:")
print(len(coin.tweets))
coin.tweets = coin.tweets.merge(udf,
left_on='user_history_row_id',
right_on='user_row_id',
how='inner')
print("nr. of tweets after merge:")
print(len(coin.tweets))
sid = SentimentAnalyzer()
#only with multicore CPU:
#dfsents = sid.paralellanalyse(coin.tweets)
#this with singlecore CPU:
dfsents = sid.analysedf(coin.tweets)
# print(dfsents.head())
print("coin.tweets ready.")
setattr(coin, 'tweets', dfsents)
# PREPARE 2
#df = tweetio.sort_and_clip(coin.tweets, coin.ico)
#coin.tweets = df
## MULTIPLYING RETWEETS FOLLOWERS
print("multiplying nr. of retweet followers by sentiments.")
sentanalyzer = SentimentAnalyzer()
sentanalyzer.merge_tweets_with_retweets(coin)
sentanalyzer.sent_mul_tweet_followers(coin)
sentanalyzer.sent_mul_retweet_followers(coin)
print(len(coin.retweets))
#print(coin.retweets.head())
## GROUPING RETWEETS BY HOUR
print("grouping retweets by hour basis")
sentanalyzer.group_retweet_by_hour(coin)
#print(coin.grtdf.head())
print("grouping tweets by hour basis")
sentanalyzer.group_tweet_by_hour(coin)
#print(coin.gtdf.head())
print("RETWEET S")
#print(coin.retweets)
print(len(coin.retweets))
print("TWEETS")
#print(coin.tweets)
print(len(coin.tweets))
print("USERS")
#print(udf)
print(len(udf))
## Setting in prices:
bapi = BinanceApi()
coin_price = bapi.collect_coindata(coin, specific_hour)
setattr(coin, 'pricehourly', coin_price)
coin.save_to_storeage(PHASE, tmpdir='runtime/')
return coin
def test_date_time_binance1(self):
bapi = BinanceApi()
print(bapi.get_nr_of_hour_distance_from_server())