def main(): parser = build_parser() options = parser.parse_args() if not os.path.exists("./" + config.DATA_SAVE_DIR): os.makedirs("./" + config.DATA_SAVE_DIR) if not os.path.exists("./" + config.TRAINED_MODEL_DIR): os.makedirs("./" + config.TRAINED_MODEL_DIR) if not os.path.exists("./" + config.TENSORBOARD_LOG_DIR): os.makedirs("./" + config.TENSORBOARD_LOG_DIR) if not os.path.exists("./" + config.RESULTS_DIR): os.makedirs("./" + config.RESULTS_DIR) if options.mode == "train": import finrl.autotrain.training finrl.autotrain.training.train_one() elif options.mode == "download_data": from finrl.marketdata.yahoodownloader import YahooDownloader df = YahooDownloader(start_date=config.START_DATE, end_date=config.END_DATE, ticker_list=config.DOW_30_TICKER).fetch_data() now = datetime.datetime.now().strftime("%Y%m%d-%Hh%M") df.to_csv("./" + config.DATA_SAVE_DIR + "/" + now + ".csv")
def fetch_and_store(start_date=config.START_DATE, end_date=None, interval=None, ticker_list=config.CRYPTO_TICKER): print("==============Start Fetching Data===========") df = YahooDownloader(start_date=start_date, end_date=end_date or datetime.utcnow().strftime("%Y-%m-%d"), ticker_list=ticker_list).fetch_data() now = datetime.now().strftime(config.DATETIME_FMT) filename = f'./{config.DATA_SAVE_DIR}/{now}.csv' df.to_csv(filename) return df
def main(): parser = build_parser() options = parser.parse_args() # add following folders if not os.path.exists("./" + config.DATA_SAVE_DIR): os.makedirs("./" + config.DATA_SAVE_DIR) # From config.py file get following: # start_date START_DATE = config.START_DATE # end_date END_DATE = config.END_DATE # list of stocks# STOCK_LIST = config.DOW_30_TICKER print("All stocks used for training:", STOCK_LIST) print("Historical data are used from: ", START_DATE) print("Till end date: ", END_DATE) # Download and save the data in a pandas DataFrame: data_frame = YahooDownloader(start_date=START_DATE, end_date=END_DATE, ticker_list=STOCK_LIST).fetch_data() print("Data Frame shape is: ", data_frame.shape) print("Data Frame format is following: \n\n", data_frame.head()) ## ## Save downloaded data to file ## if os.path.exists("./" + config.DATA_SAVE_DIR + "/" + options.name + ".csv"): os.remove("./" + config.DATA_SAVE_DIR + "/" + options.name + ".csv") print("The download data file deleted") else: print("The download data file does not exist") data_frame.to_csv("./" + config.DATA_SAVE_DIR + "/" + options.name + ".csv") print( "Successfuly completed the task of downloading and saving financial data." )