import pandas as pd
import sqlalchemy
from sqlalchemy import create_engine,text
import configparser
import os
from datetime import datetime
from urllib.parse import quote_plus


def get_db_connection_string(config, section):
    """从配置文件中构建数据库连接字符串"""
    return f"mysql+pymysql://{config[section]['user']}:{quote_plus(config[section]['password'])}@" \
           f"{config[section]['host']}:{config[section]['port']}/{config[section]['database']}"


def transform_and_load_ma_machines(config_file_path):
    """
    从源数据库提取ma_machines数据，转换后加载到目标数据库ma_machine
    :param config_file_path: 配置文件路径
    """
    # 读取配置文件
    if not os.path.exists(config_file_path):
        raise FileNotFoundError(f"配置文件不存在: {config_file_path}")

    config = configparser.ConfigParser()
    config.read(config_file_path)

    # 定义状态替换映射
    status_mapping = {
        1: 0,  # 待通知 → 0
        2: 0,  # 待检验 → 0
        3: 0,  # 待打印 → 0
        4: 0,  # 待入库 → 0
        5: 1,  # 在库 → 1
        6: 2,  # 在用 → 2
        7: 3,  # 在修 → 3
        8: 3,  # 在试 → 3
        9: 5,  # 修试后待入库 → 5
        10: 7,  # 待报废 → 7
        11: 8,  # 已报废 → 8
        12: 7,  # 报废封存 → 7
        13: 4,  # 在检 → 4
        14: 4,  # 在审 → 4
        15: None,  # 移交 → NULL（根据业务需求处理）
        16: 17,  # 报废检验 → 17
        17: 17,  # 封存检验 → 17
        18: 18,  # 报备丢失 → 18
        19: 18  # 结算丢失 → 18
    }

    try:
        # 获取数据库连接
        source_conn_str = get_db_connection_string(config, 'source_db')
        target_conn_str = get_db_connection_string(config, 'target_db')
        source_engine = create_engine(source_conn_str)
        target_engine = create_engine(target_conn_str)

        # 从源表读取数据（过滤COMPANY_ID=1的记录）
        print("正在从源表ma_machines读取数据...")
        source_query = """
                       SELECT ID, \
                              TYPE, \
                              BATCH_STATUS, \
                              DEVICE_CODE, \
                              OUT_FAC_TIME, \
                              model_name,
                              OUT_FAC_NUM, \
                              VENDER_ID, \
                              QRCODE, \
                              ASSETS_NUM, \
                              THIS_CHECK_TIME,
                              THIS_CHECK_MAN, \
                              NEXT_CHECK_TIME, \
                              CYCLE_NUM
                       FROM ma_machines
                       WHERE COMPANY_ID = 1 \
                       """
        source_df = pd.read_sql(source_query, source_engine)

        if source_df.empty:
            print("没有符合条件的数据需要转换")
            return
        print(f"读取到{len(source_df)}条待转换数据")

        # 数据转换
        print("正在进行数据转换...")
        target_df = pd.DataFrame()

        # 直接复制字段
        target_df['ma_id'] = source_df['ID']
        target_df['type_id'] = source_df['TYPE']
        target_df['ma_code'] = source_df['DEVICE_CODE']
        target_df['out_fac_time'] = pd.to_datetime(source_df['OUT_FAC_TIME'], errors='coerce')
        target_df['machine_name'] = source_df['model_name']
        target_df['out_fac_code'] = source_df['OUT_FAC_NUM']
        target_df['ma_vender'] = source_df['VENDER_ID']
        target_df['qr_code'] = source_df['QRCODE']
        target_df['assets_code'] = source_df['ASSETS_NUM']
        target_df['this_check_time'] = pd.to_datetime(source_df['THIS_CHECK_TIME'], errors='coerce')
        target_df['check_man'] = source_df['THIS_CHECK_MAN']
        target_df['next_check_time'] = pd.to_datetime(source_df['NEXT_CHECK_TIME'], errors='coerce')
        target_df['in_out_num'] = source_df['CYCLE_NUM']

        # 替换状态字段
        target_df['ma_status'] = source_df['BATCH_STATUS'].map(status_mapping)

        # 检查数据质量
        print("\n数据质量检查:")
        print(f"- 无效出厂时间记录: {target_df['out_fac_time'].isna().sum()}")
        print(f"- 无效本次检验时间记录: {target_df['this_check_time'].isna().sum()}")
        print(f"- 无效下次检验时间记录: {target_df['next_check_time'].isna().sum()}")
        print(f"- 未映射的状态值: {source_df[target_df['ma_status'].isna()]['BATCH_STATUS'].unique()}")

        # 写入目标表
        print("\n正在写入目标表ma_machine...")
        # 步骤1：清空目标表
        with target_engine.connect() as conn:
            conn.execute(text("TRUNCATE TABLE ma_machine"))  # 注意需要从sqlalchemy导入text
            conn.commit()  # 显式提交事务

        # 步骤2：写入去重后的数据
        target_df.drop_duplicates(['type_id', 'ma_code']).to_sql(
            'ma_machine',
            target_engine,
            if_exists='append',
            index=False
        )

        target_df.to_sql(
            'ma_machine',
            target_engine,
            if_exists='append',
            index=False,
            dtype={
                'ma_id': sqlalchemy.types.INTEGER(),
                'type_id': sqlalchemy.types.INTEGER(),
                'ma_status': sqlalchemy.types.SmallInteger(),
                'ma_code': sqlalchemy.types.VARCHAR(length=50),
                'out_fac_time': sqlalchemy.types.DateTime(),
                'machine_name': sqlalchemy.types.VARCHAR(length=100),
                'out_fac_code': sqlalchemy.types.VARCHAR(length=50),
                'ma_vender': sqlalchemy.types.INTEGER(),
                'qr_code': sqlalchemy.types.VARCHAR(length=100),
                'assets_code': sqlalchemy.types.VARCHAR(length=50),
                'this_check_time': sqlalchemy.types.DateTime(),
                'check_man': sqlalchemy.types.VARCHAR(length=50),
                'next_check_time': sqlalchemy.types.DateTime(),
                'in_out_num': sqlalchemy.types.INTEGER()
            }
        )
        print(f"成功写入{len(target_df)}条数据")

    except Exception as e:
        print(f"\n处理过程中发生错误: {str(e)}")
        raise
    finally:
        if 'source_engine' in locals():
            source_engine.dispose()
        if 'target_engine' in locals():
            target_engine.dispose()


if __name__ == "__main__":
    # 配置文件路径
    config_file = "config.ini"

    try:
        transform_and_load_ma_machines(config_file)
    except Exception as e:
        print(f"程序执行失败: {str(e)}")