def start_day(market_open, market_close): print("MARKET STARTED") print(dt.now()) collect_data() schedule.every(5).minutes.do(collect_data) # when to stop while (time_is_between(market_open, market_close)): schedule.run_pending() time.sleep(1)
import numpy as np import joblib from keras.models import load_model from data_collector import series_to_supervised, collect_data, read_dataset, get_filename from datetime import datetime loaded_model = load_model('model/saved_model.model') scaler = joblib.load('model/scaler.save') from_symbol = 'BTC' to_symbol = 'USD' exchange = 'Bitstamp' datetime_interval = 'day' collect_data(from_symbol, to_symbol, exchange, datetime_interval) current_datetime = datetime.now().date().isoformat() orginal_data = read_dataset( get_filename(from_symbol, to_symbol, exchange, datetime_interval, current_datetime)) num_past_days = 20 num_features = len(orginal_data.columns) num_obs = num_features * num_past_days scaled = scaler.transform(orginal_data.values) data = series_to_supervised(scaled, n_in=num_past_days, n_out=1) values = data.values # n_train_days = int(0.9 * len(data)) n_train_days = len(data) - 70
from link_collector import collect_links from data_collector import collect_data from save_file import save url = 'https://www.ru-chipdip.by/catalog' header = {'user-agent': 'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) OPR/55.0.2994.44'} links = collect_links(url, header) for key in links.keys(): for dept in links[key]: item_data = collect_data(dept, header) data_dict = {key: { dept: { item_data } } } save(data_dict)
def collect_data(): """Collect a new data point and store it.""" return data_collector.collect_data()