def download_data(api: numerapi.NumerAPI, keys):
if int(keys['LATEST_ROUND']) == api.get_current_round():
return int(keys['LATEST_ROUND'])
else:
LATEST_ROUND = api.get_current_round()
api.download_current_dataset('./data')
return LATEST_ROUND
def downloadNumeraiData():
# set up paths for download of dataset and upload of predictions
dataset_parent_folder = "./datasets/"
# We don't need to login in order to download the dataset
napi = NumerAPI(verbosity="info")
# download current dataset
napi.download_current_dataset(dest_path=dataset_parent_folder, unzip=True)
sp.call("mv " + dataset_parent_folder + "/*.zip ZipFiles/", shell=True)
sp.call("rm " + dataset_parent_folder + "/*/example*")
def test_download_current_dataset(api: NumerAPI):
directory = None
csv_files = ['numerai_tournament_data.csv', 'numerai_training_data.csv']
try:
path = api.download_current_dataset(unzip=True)
assert os.path.exists(path)
directory = path.replace(".zip", "")
for csv_file in csv_files:
final_path_name = os.path.join(directory, csv_file)
assert os.path.exists(final_path_name)
finally:
if directory is not None:
for csv_file in csv_files:
os.remove(os.path.join(directory, csv_file))
os.removedirs(os.path.join(directory, 'numerai_dataset'))
os.remove('%s.zip' % directory)
# import dependencies
from numerapi import NumerAPI
from os import environ, path, getcwd
from yaml import safe_load
# Load your API keys and model from config.yml
with open("config.yml", "r") as yml:
numerai_conf = safe_load(yml)
# Set your API keys and model_id
public_id = numerai_conf["public_id"] if numerai_conf["public_id"] is not None else environ['NUMERAI_PUBLIC_ID']
secret_key = numerai_conf["secret_key"] if numerai_conf["secret_key"] is not None else environ['NUMERAI_SECRET_KEY']
model_id = numerai_conf["model_id"] if numerai_conf["model_id"] is not None else environ['NUMERAI_MODEL_ID']
napi = NumerAPI(public_id=public_id, secret_key=secret_key, verbosity="info")
current_round = napi.get_current_round()
dest_path = numerai_conf["dest_path"] if numerai_conf["dest_path"] is not None else environ['NUMERAI_DEST_PATH']
if not dest_path:
dest_path=environ['PWD']
path_numerai_dataset = f'{dest_path}/numerai_dataset_{current_round}'
# Download and unzip the tournament dataset of current round
if not path.isdir(path_numerai_dataset):
napi.download_current_dataset(dest_path=dest_path, unzip=True)
# Upload example_predictions.csv
submission_id = napi.upload_predictions(f'{path_numerai_dataset}/example_predictions.csv', model_id=model_id)