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- import pandas as pd
- from service.common_connect import trans
- wind_farms = {
- "WOF35900004": "平陆风电场",
- "WOF35100072": "阳曲风电场",
- "WOF35100073": "古交风电场",
- "WOF35200074": "马家梁风电场",
- "WOF35400075": "太谷风电场",
- "WOF35900076": "坡底风电场",
- "WOF35300077": "西潘风电场",
- "WOF35900078": "芮城风电场",
- "WOF34900079": "右玉风光互补电站",
- "WOF35800080": "贺家沟",
- "WOF35800081": "石楼风电场",
- "WOF35800082": "盂县风光互补电站"
- }
- # types = ['minute', 'second', 'warn', 'fault']
- types = ['warn', 'fault']
- def check_exist_table(table_name):
- sql = f"select count(1) as count from information_schema.tables where table_name= '{table_name}'"
- print(sql)
- data = trans.execute(sql)[0]['count']
- return int(data) > 0
- file_dir = r'C:\Users\wzl\Desktop\中广核104测点\20250513\data'
- def get_data(table_name, name, type):
- col = 'begin_time'
- if type in ['minute', 'second']:
- col = 'time_stamp'
- sql = f"select * from {table_name} where {col} > '2025-05-10 00:00:00'"
- df = pd.read_sql_query(sql, con=trans.get_engine())
- df.to_csv(f'{file_dir}\\{name}_{type}.csv', index=False, encoding='utf-8')
- for wind, name in wind_farms.items():
- for now_type in types:
- table_name = f'{wind}_{now_type}'
- if check_exist_table(table_name):
- get_data(table_name, name, now_type)
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