Exemple #1
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def load_and_classify_job(coin):
    localtz = pytz.timezone('US/Pacific')

    todate = datetime.now(localtz)

    try:
        last_tweet = find_last_tweet(coin)
        from_date = last_tweet[0]['created_at']
        print(from_date)
    except Exception:
        from_date = (datetime.now(localtz) + timedelta(days=-30)).isoformat()

    print("Loading tweets from {} to {}".format(
        from_date, (todate + timedelta(days=1)).isoformat()))
    load_tweets(from_date, (todate + timedelta(days=1)).isoformat(), coin)

    #recover
    hours = (todate - parse(from_date)).total_seconds() / 3600
    for i in range(0, int(hours)):
        from_range = to_date(from_date) + timedelta(hours=i)
        to_range = to_date(from_date) + timedelta(hours=i + 1)
        classify_new_tweets(coin, from_range.isoformat(), to_range.isoformat(),
                            from_range.isoformat())

    #last classification
    todate_new = datetime.now(localtz)
    fromdate_new = datetime.now(localtz) - timedelta(hours=-1)
    classify_new_tweets(coin, fromdate_new.isoformat(), todate_new.isoformat(),
                        fromdate_new.isoformat())
    build_influencers(coin)
Exemple #2
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 def __init__(self, params_dict):
     self.twitter_id = params_dict.get("id")
     self.text = params_dict.get("text")
     self.sentiment = None
     self.sentiment_score = None
     self.created_at = to_date(params_dict.get("created_at"))
     self.author = Author(params_dict.get("user"))
Exemple #3
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 def __init__(self, params_dict):
     self.twitter_id = params_dict.get("id")
     self.name = params_dict.get("name")
     self.followers_count = params_dict.get("followers_count")
     self.friends_count = params_dict.get("friends_count")
     self.favourites_count = params_dict.get("favourites_count")
     self.created_at = to_date(params_dict.get("created_at"))
     self.verified = params_dict.get("verified")
     self.location = params_dict.get("location")
     self.url = params_dict.get("url")
     self.retweet_rate = None
     self.like_rate = None
     self.reply_rate = None
def find_classification(coin_code, start_date, end_date):
    collection = db[coin_code.lower()]

    classifications = list(
        collection.find(
            {'classification_date': {
                '$gte': start_date,
                '$lt': end_date
            }}))

    for classification in classifications:
        classification['_id'] = str(classification['_id'])
        classification['classification_date'] = to_date(
            to_local_timezone(classification['classification_date']))

    return classifications
def get_coin_price(coin_code, currency, time=None):
    return cryptocompare.get_historical_price(coin_code, currency, time)


def get_coin_list():
    coin_dict = cryptocompare.get_coin_list()

    coins = []
    for key, coin_data in coin_dict.items():
        id = int(coin_data[coin_property.ID])
        code = coin_data[coin_property.NAME]
        name = coin_data[coin_property.FULL_NAME]
        sortOrder = int(coin_data[coin_property.SORT_ORDER])
        coin = Coin(id, code.lower(), name.lower(), sortOrder)
        coins.append(coin)

    sorted_coins = sorted(coins, key=lambda x: x.sortOrder)
    return sorted_coins


if __name__ == "__main__":
    import time

    date_str = "2018-05-17T18:20:00.448083-07:00"
    date_gmt = to_date(to_gmt(date_str))
    timestamp = time.mktime(date_gmt.timetuple())
    print(timestamp)

    #price = get_coin_price("ZIL", "USD", date_gmt)
    #print(price['ZIL']['USD'])