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| import sys | |
| import time | |
| import tqdm | |
| import cbpro | |
| import pandas as pd | |
| if __name__ == '__main__': | |
| if len(sys.argv) < 3: | |
| print(f'Usage: {sys.argv[0]} start_date end_date') | |
| exit() | |
| cl = cbpro.PublicClient() | |
| dr = pd.date_range(*sys.argv[1:3], freq='5min')[::-300].sort_values() | |
| couples = list((lambda x: zip(x[:-1], x[1:]))(dr.tolist())) | |
| tm = time.time() | |
| for i in tqdm.tqdm(couples): | |
| lst = cl.get_product_historic_rates('BTC-EUR', i[0].isoformat(), i[1].isoformat(), granularity=300) | |
| df = pd.DataFrame(lst, columns='date open high low close volume'.split(' ')).set_index('date') | |
| df = df.set_index(df.index.astype('datetime64[s]')) | |
| df.to_csv(f'files/{i[0].strftime("%Y%m%d%H%M%S")}.csv') | |
| ntm = time.time() | |
| if ntm - tm < .75: | |
| time.sleep(.75 - ntm + tm) | |
| tm = time.time() |
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| from glob import glob | |
| from tqdm import tqdm | |
| import pandas as pd | |
| files = glob('files/*.csv') | |
| df = None | |
| for i in tqdm(files): | |
| dfi = pd.read_csv(i).set_index('date') | |
| df = pd.concat([df, dfi]) if df is not None else dfi | |
| df = df.set_index(df.index.astype('datetime64')).sort_index() | |
| df['open_interest'] = pd.Series(index=df.index) | |
| df.columns = pd.MultiIndex.from_product([['BTC-EUR'], df.columns]) | |
| df.to_csv('all.csv') | |
| df.astype('float64').to_hdf('crypto.h5', 'table') |
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