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- import cudf
- import multiprocessing as mp
- from sqlalchemy import create_engine
- from datetime import datetime as dt
- import pandas as pd
- import logging
- def t(df, u):
- st = dt.now()
- t = cudf.DataFrame()
- try:
- for i in range(len(df)):
- t = cudf.concat([t, df.iloc[i].to_frame().T], axis=0)
- except BaseException as e:
- print(e)
- t.loc[i + 1, 'HL'] = 1
- print(f'{u}完成,{dt.now() - st}')
- if __name__ == '__main__':
- # mp.freeze_support()
- logger = mp.log_to_stderr()
- logger.setLevel(logging.DEBUG)
- engine = create_engine(
- 'mysql+pymysql://root:r6kEwqWU9!v3@172.18.0.4:3306/qmt_stocks_whole?charset=utf8')
- # engine = create_engine(
- # 'mysql+pymysql://root:r6kEwqWU9!v3@localhost:3307/qmt_stocks_whole?charset=utf8')
- df = pd.read_sql_table('000001.SZ_1d', con=engine.connect())
- df = cudf.from_pandas(df)
- print(df.shape)
- # df_cudf = cudf.from_pandas(df)
- pool = mp.Pool(2)
- try:
- for j in range(1):
- pool.apply_async(func=t, args=(df, j))
- pool.close()
- pool.join()
- except BaseException as e:
- print(e)
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