197 lines
6.7 KiB
Python
197 lines
6.7 KiB
Python
import configparser
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import pandas as pd
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from sqlalchemy import create_engine
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from urllib.parse import quote_plus
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from datetime import datetime
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# 读取配置文件
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config = configparser.ConfigParser()
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config.read('config.ini')
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# 获取数据库连接配置
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source_config = {
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'host': config.get('source_db', 'host'),
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'user': config.get('source_db', 'user'),
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'password': config.get('source_db', 'password'),
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'database': config.get('source_db', 'database'),
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'port': config.getint('source_db', 'port')
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}
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target_config = {
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'host': config.get('target_db', 'host'),
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'user': config.get('target_db', 'user'),
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'password': config.get('target_db', 'password'),
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'database': config.get('target_db', 'database'),
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'port': config.getint('target_db', 'port')
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}
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# 创建数据库引擎（增加charset参数避免中文乱码）
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source_engine = create_engine(
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f"mysql+pymysql://{source_config['user']}:{quote_plus(source_config['password'])}@{source_config['host']}:{source_config['port']}/{source_config['database']}?charset=utf8mb4"
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)
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target_engine = create_engine(
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f"mysql+pymysql://{target_config['user']}:{quote_plus(target_config['password'])}@{target_config['host']}:{target_config['port']}/{target_config['database']}?charset=utf8mb4"
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)
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def safe_convert_to_int(series):
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"""安全转换为整数，处理空字符串、浮点字符串等情况"""
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str_series = series.astype(str)
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str_series = str_series.replace({'': '0', 'None': '0', 'nan': '0'})
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return pd.to_numeric(str_series, errors='coerce').fillna(0).astype(int)
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def safe_convert_to_float(series):
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"""安全转换为浮点数"""
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str_series = series.astype(str)
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str_series = str_series.replace({'': '0.0', 'None': '0.0', 'nan': '0.0'})
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return pd.to_numeric(str_series, errors='coerce').fillna(0.0)
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def process_tm_task():
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"""处理新购任务主表"""
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try:
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sql = """
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SELECT
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(be.ID + 500000) as task_id,
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0 as task_type,
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IF(be.`STATUS` = 17, 19, 4) as task_status,
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be.`CODE` as code,
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pu.`NAME` as create_by,
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be.CREATE_TIME
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FROM
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bpm_example be
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LEFT JOIN sys_data_dict sdd on be.`STATUS` = sdd.ID
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LEFT JOIN pm_user pu on be.CREATOR = pu.ID
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WHERE be.DEFINITION_ID = 2
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AND be.CREATE_TIME BETWEEN '2025-01-01' AND NOW()
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"""
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df = pd.read_sql(sql, source_engine)
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# 转换状态字段
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df['task_status'] = safe_convert_to_int(df['task_status'])
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# 确保时间字段格式正确
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if 'CREATE_TIME' in df.columns:
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df['CREATE_TIME'] = pd.to_datetime(df['CREATE_TIME'])
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df.to_sql('tm_task', target_engine, if_exists='append', index=False)
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print(f"成功导入 {len(df)} 条新购任务主表数据")
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return True
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except Exception as e:
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print(f"处理新购任务主表时出错: {str(e)}")
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return False
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def process_purchase_check_info():
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"""处理采购验收信息表"""
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try:
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sql = """
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SELECT
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(be.ID + 500000) as task_id,
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baf.BUY_TIME as purchase_time,
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be.CREATE_TIME as arrival_time,
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(baf.SUPPLIER_ID + 500) as supplier_id,
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pu.`NAME` as create_by,
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be.CREATE_TIME
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FROM
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bpm_example be
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LEFT JOIN bpm_accept_form baf on be.ID = baf.EXAMPLE_ID
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LEFT JOIN sys_data_dict sdd on be.`STATUS` = sdd.ID
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LEFT JOIN pm_user pu on be.CREATOR = pu.ID
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WHERE be.DEFINITION_ID = 2
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AND be.CREATE_TIME BETWEEN '2025-01-01' AND NOW()
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"""
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df = pd.read_sql(sql, source_engine)
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# 处理时间字段
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time_cols = ['purchase_time', 'arrival_time', 'CREATE_TIME']
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for col in time_cols:
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if col in df.columns:
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df[col] = pd.to_datetime(df[col])
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# 处理供应商ID
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if 'supplier_id' in df.columns:
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df['supplier_id'] = safe_convert_to_int(df['supplier_id'])
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df.to_sql('purchase_check_info', target_engine, if_exists='append', index=False)
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print(f"成功导入 {len(df)} 条采购验收信息")
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return True
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except Exception as e:
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print(f"处理采购验收信息时出错: {str(e)}")
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return False
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def process_purchase_check_details():
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"""处理采购验收明细表"""
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try:
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sql = """
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SELECT
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(be.ID + 500000) as task_id,
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(baf.MATYPE_ID + 6000) as type_id,
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baf.PURCHASE_PRICE as purchase_price,
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baf.NOTAX_PRICE as purchase_tax_price,
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(baf.SUPPLIER_ID + 500) as supplier_id,
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baf.ACCEP_NUM as purchase_num,
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baf.QUALIFIED_NUM as check_num,
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baf.ACTUALNUM as bind_num,
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baf.INPUT_NUM as input_num,
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IF(baf.PURCHASE_STATUS = 17, 19, 4) as status,
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pu.`NAME` as create_by,
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be.CREATE_TIME
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FROM
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bpm_example be
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LEFT JOIN bpm_accept_form baf on be.ID = baf.EXAMPLE_ID
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LEFT JOIN sys_data_dict sdd on be.`STATUS` = sdd.ID
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LEFT JOIN pm_user pu on be.CREATOR = pu.ID
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WHERE be.DEFINITION_ID = 2
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AND be.CREATE_TIME BETWEEN '2025-01-01' AND NOW()
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"""
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df = pd.read_sql(sql, source_engine)
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# 处理数值字段
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num_cols = [
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'type_id', 'purchase_num', 'check_num',
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'bind_num', 'input_num', 'status', 'supplier_id'
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]
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for col in num_cols:
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if col in df.columns:
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df[col] = safe_convert_to_int(df[col])
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# 处理价格字段
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price_cols = ['purchase_price', 'purchase_tax_price']
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for col in price_cols:
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if col in df.columns:
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df[col] = safe_convert_to_float(df[col])
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# 添加默认的生产时间（当前时间）
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df['production_time'] = datetime.now().strftime('%Y-%m-%d %H:%M:%S')
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# 计算验收结果
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df['check_result'] = df.apply(
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lambda row: 1 if row['check_num'] == row['purchase_num'] else 0,
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axis=1
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)
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df.to_sql('purchase_check_details', target_engine, if_exists='append', index=False)
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print(f"成功导入 {len(df)} 条采购验收明细")
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return True
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except Exception as e:
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print(f"处理采购验收明细时出错: {str(e)}")
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return False
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if __name__ == "__main__":
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# 执行所有转换流程
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processes = [
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process_tm_task,
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process_purchase_check_info,
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process_purchase_check_details
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]
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success = all([p() for p in processes])
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if success:
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print("所有新购待验收相关表转换完成！")
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else:
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print("!!! 部分转换失败，请检查错误日志 !!!") |