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- import datetime
- import pandas as pd
- from sqlalchemy import create_engine
- def get_engine():
- username = 'envision'
- password = 'envision'
- host = '172.21.6.37'
- port = 3306
- dbname = 'envision'
- return create_engine(f'mysql+pymysql://{username}:{password}@{host}:{port}/{dbname}')
- def generate_sql(df: pd.DataFrame, wind_name: str):
- print(f"开始执行{wind_name}")
- wind_nos = df['风机号'].unique()
- all_sqls = list()
- begin_time_str = '2025-01-01 00:00:00'
- end_time_str = '2025-03-01 00:00:00'
- for wind_no in wind_nos:
- wind_df = df[df['风机号'] == wind_no]
- for wind_factory, table, col, en_name in zip(wind_df['风场'], wind_df['历史采样表名'], wind_df['历史采样域名'],
- wind_df['en_name']):
- all_sqls.append((wind_factory,
- f"select '{wind_factory}' as wind_factory,{wind_no} as wind_no, occur_time, {col} as {en_name}"
- f" from {table} where occur_time >= '{begin_time_str}' and occur_time <'{end_time_str}'"))
- return all_sqls
- def show_sqls(datas):
- for index, data in enumerate(datas):
- print('--', data[0])
- print(data[1])
- print()
- def save_to_csv(datas):
- dfs = list()
- for index, data in enumerate(datas):
- begin = datetime.datetime.now()
- print('开始', begin)
- dfs.append(pd.read_sql(data[1], get_engine()))
- df.to_csv(data[0] + str(index) + ".csv", encoding='utf8', index=False)
- print('结束', datetime.datetime.now(), '耗时:', datetime.datetime.now() - begin)
- if __name__ == '__main__':
- df = pd.read_csv(r"C:\Users\wzl\Desktop\中广核104测点\min_tables.csv")
- datas = generate_sql(df[df['风场'] == '右玉'], '右玉')
- show_sqls(datas)
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