121 lines
4.5 KiB
Python
121 lines
4.5 KiB
Python
import pandas as pd
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import sqlalchemy
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from sqlalchemy import create_engine, text
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import configparser
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import os
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from datetime import datetime
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from urllib.parse import quote_plus
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def get_db_connection_string(config, section):
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"""从配置文件中构建数据库连接字符串"""
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return f"mysql+pymysql://{config[section]['user']}:{quote_plus(config[section]['password'])}@" \
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f"{config[section]['host']}:{config[section]['port']}/{config[section]['database']}"
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def transform_and_load_qrcode(config_file_path):
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"""
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从源数据库提取qr_code数据，转换后加载到目标数据库bm_qrcode_info
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:param config_file_path: 配置文件路径
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"""
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# 读取配置文件
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if not os.path.exists(config_file_path):
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raise FileNotFoundError(f"配置文件不存在: {config_file_path}")
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config = configparser.ConfigParser()
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config.read(config_file_path)
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try:
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# 获取数据库连接
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source_conn_str = get_db_connection_string(config, 'source_db')
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target_conn_str = get_db_connection_string(config, 'target_db')
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source_engine = create_engine(source_conn_str)
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target_engine = create_engine(target_conn_str)
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# 从源表读取数据（过滤COMPANY_ID=1的记录）
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print("正在从源表qr_code读取数据...")
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source_query = """
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SELECT code, ma_model, vender, is_bind, gen_month, nullif(task_id, '') as task_id
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FROM bm_qrcode
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WHERE COMPANY_ID = 1 \
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"""
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source_df = pd.read_sql(source_query, source_engine)
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if source_df.empty:
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print("没有符合条件的数据需要转换")
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return
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print(f"读取到{len(source_df)}条待转换数据")
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# 数据转换
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print("正在进行数据转换...")
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target_df = pd.DataFrame()
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# 字段映射（源字段 → 目标字段）
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field_mapping = {
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'code': 'qr_code',
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'ma_model': 'type_id',
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'vender': 'supplier_id',
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'is_bind': 'is_bind',
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'gen_month': 'create_time',
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'task_id': 'task_id'
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}
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# 复制字段
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for source_field, target_field in field_mapping.items():
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target_df[target_field] = source_df[source_field]
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# 检查数据质量
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print("\n数据质量检查:")
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print(f"- 空qr_code记录: {target_df['qr_code'].isna().sum()}")
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print(f"- 空type_id记录: {target_df['type_id'].isna().sum()}")
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# 写入目标表（使用connection避免重复记录问题）
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print("\n正在写入目标表bm_qrcode_info...")
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with target_engine.begin() as conn:
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# 先检查并删除可能重复的qr_code（根据业务需求决定是否保留）
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existing_codes = pd.read_sql(
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"SELECT qr_code FROM bm_qrcode_info",
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conn
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)['qr_code'].tolist()
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new_records = target_df[~target_df['qr_code'].isin(existing_codes)]
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dup_count = len(target_df) - len(new_records)
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if dup_count > 0:
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print(f"发现{dup_count}条重复qr_code记录，将自动跳过")
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if not new_records.empty:
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new_records.to_sql(
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'bm_qrcode_info',
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conn,
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if_exists='append',
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index=False,
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dtype={
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'qr_code': sqlalchemy.types.VARCHAR(length=100),
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'type_id': sqlalchemy.types.INTEGER(),
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'supplier_id': sqlalchemy.types.INTEGER(),
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'is_bind': sqlalchemy.types.SmallInteger(),
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'create_time': sqlalchemy.types.DateTime(),
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'task_id': sqlalchemy.types.VARCHAR(length=50)
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}
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)
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print(f"成功写入{len(new_records)}条新数据")
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else:
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print("没有新数据需要写入")
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except Exception as e:
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print(f"\n处理过程中发生错误: {str(e)}")
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raise
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finally:
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if 'source_engine' in locals():
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source_engine.dispose()
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if 'target_engine' in locals():
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target_engine.dispose()
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if __name__ == "__main__":
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# 配置文件路径
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config_file = "config.ini"
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try:
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transform_and_load_qrcode(config_file)
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except Exception as e:
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print(f"程序执行失败: {str(e)}") |