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."
)