119 lines
3.7 KiB
Python
119 lines
3.7 KiB
Python
import pandas as pd
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import json
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import utils
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from config_p import MYSQL_HOST,MYSQL_USER,MYSQL_PASSWORD,MYSQL_DB
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import mysql.connector
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# 读取 Excel 文件
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df = pd.read_excel('/Users/zhengfei/Desktop/cb/ttt.xlsx', header=0)
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# 将 DataFrame 转换为字典列表
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data_list = df.to_dict(orient='records')
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year = 2023
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conn = mysql.connector.connect(
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host = MYSQL_HOST,
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user = MYSQL_USER,
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password = MYSQL_PASSWORD,
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database = MYSQL_DB
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)
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# 创建一个cursor对象来执行SQL语句
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cursor = conn.cursor()
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insert_query = '''
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INSERT INTO measure_create_config
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(config_id, meta_measure, same_mean_measure, measure_period, change_type, black_list)
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VALUES (%s, %s, %s, %s, %s, %s)
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'''
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for data in data_list:
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show_measure = str(data['指标'])
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same_mean_measure = str(data['同义表述'])
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period_measure = str(data['周期'])
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change_measure = str(data['变动'])
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black_list = str(data['黑名单词'])
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config_id = utils.get_md5(show_measure)
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insert_query_data = (config_id, show_measure, same_mean_measure, period_measure, change_measure, black_list)
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cursor.execute(insert_query, insert_query_data)
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conn.commit()
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# 读取 Excel 文件
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df_period = pd.read_excel('/Users/zhengfei/Desktop/cb/period.xlsx', header=0)
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# 将 DataFrame 转换为字典列表
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period_list = df_period.to_dict(orient='records')
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period_insert_query = '''
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INSERT INTO measure_create_period
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(period_name, same_mean_period)
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VALUES (%s, %s)
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'''
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for data in period_list:
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period_name = str(data['标准表述'])
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same_mean_period = str(data['同义表述'])
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insert_query_data = (period_name, same_mean_period)
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cursor.execute(period_insert_query, insert_query_data)
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conn.commit()
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data_query = '''
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SELECT * FROM measure_create_config where delete_status = 0
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'''
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period_query = '''
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SELECT * FROM measure_create_period
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'''
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cursor.execute(data_query)
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data_list = cursor.fetchall()
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cursor.execute(period_query)
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period_list = cursor.fetchall()
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for data in data_list:
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config_id = data[0]
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show_measure = data[1]
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same_mean_measure = data[2]
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period_measure = data[3]
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change_measure = data[4]
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same_mean_measure_arr = []
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period_measure_arr = []
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change_measure_arr = []
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if same_mean_measure != 'nan' :
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same_mean_measure_arr = same_mean_measure.split(',')
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same_mean_measure_arr.append(show_measure)
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if period_measure != 'nan' :
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period_measure_arr = period_measure.split(',')
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if change_measure != 'nan' :
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change_measure_arr = change_measure.split(',')
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for c in change_measure_arr:
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period_measure_arr.append(c)
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for x in period_measure_arr:
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if x in change_measure_arr:
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show_name = show_measure+x
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else:
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show_name = x+show_measure
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for y in same_mean_measure_arr:
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if x in change_measure:
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parser_name = y+x
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else:
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parser_name = x+y
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print(f'{show_name},{parser_name}')
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for p in period_list:
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period_exra_name = p[0]
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period_exra_value = p[1]
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if x.find(period_exra_name) != -1:
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for v in period_exra_value.split(','):
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if x in change_measure:
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parser_name = y + x.replace(period_exra_name, v)
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else:
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parser_name = x.replace(period_exra_name, v) + y
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print(f'{show_name},{parser_name}')
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cursor.close()
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conn.close() |