import configparser
import pandas as pd
from sqlalchemy import create_engine
from urllib.parse import quote_plus
# 读取配置文件
config = configparser.ConfigParser()
config.read('config.ini')

# 获取数据库连接配置
source_config = {
    'host': config.get('source_db', 'host'),
    'user': config.get('source_db', 'user'),
    'password': config.get('source_db', 'password'),
    'database': config.get('source_db', 'database'),
    'port': config.getint('source_db', 'port')
}

target_config = {
    'host': config.get('target_db', 'host'),
    'user': config.get('target_db', 'user'),
    'password': config.get('target_db', 'password'),
    'database': config.get('target_db', 'database'),
    'port': config.getint('target_db', 'port')
}

# 创建数据库引擎
source_engine = create_engine(
    f"mysql+pymysql://{source_config['user']}:{quote_plus(source_config['password'])}@{source_config['host']}:{source_config['port']}/{source_config['database']}"
)
target_engine = create_engine(
    f"mysql+pymysql://{target_config['user']}:{quote_plus(target_config['password'])}@{target_config['host']}:{target_config['port']}/{target_config['database']}"
)

# 定义UNIT_ID到unit_name的映射
unit_mapping = {
    9: 'm', 90: '根', 91: '个', 92: '付', 93: '支', 94: '双', 95: '套',
    96: '组', 97: '只', 98: '台', 99: '顶', 100: '件', 101: '米', 102: '面',
    103: '片', 104: '盘', 105: '张', 106: '块', 107: '副', 108: '袋', 109: '条',
    110: '节', 111: '瓶', 112: '斤', 113: '把', 114: '平方米', 115: '床',
    123: 'kg', 124: '份', 125: '卷'
}


def clean_existing_data():
    """清理目标表中需要更新的数据"""
    try:
        # 删除重复的地锚规格等不需要的数据（根据实际业务需求调整）
        with target_engine.connect() as conn:
            conn.execute("""
                DELETE FROM ma_type 
                WHERE type_name IN ('重复的地锚规格', '其他需要删除的规格名称')
            """)
        print("已清理目标表中的重复/无效数据")
        return True
    except Exception as e:
        print(f"清理数据时出错: {str(e)}")
        return False


def process_machine_types():
    """处理ma_machine_type表数据"""
    try:
        # 读取源数据
        df = pd.read_sql("SELECT * FROM ma_machine_type", source_engine)

        # 按照规则转换数据
        result = pd.DataFrame()
        result['type_id'] = df['ID'] + 6000  # ID加6000
        result['parent_id'] = df['PARENT_ID']
        result['type_name'] = df['NAME']
        result['level'] = df['LEVEL']
        result['unit_name'] = df['UNIT_ID'].map(unit_mapping)  # 单位映射
        result['storage_num'] = df['STORAGE_NUM']
        result['buy_price'] = df['PURCHASE_PRICE']
        result['notax_price'] = df['NOTAX_PRICE']
        result['lease_price'] = df['RENTAL_PRICE']
        result['manage_type'] = df['IS_COUNT']
        result['rated_load'] = df['CONSUMABLE']

        # 处理新增规格（示例，根据实际情况调整）
        new_types = [
            {'type_id': 6601, 'type_name': '新增规格1', 'unit_name': '个', 'level': 3},
            {'type_id': 6602, 'type_name': '新增规格2', 'unit_name': '套', 'level': 3}
        ]
        new_df = pd.DataFrame(new_types)
        result = pd.concat([result, new_df], ignore_index=True)

        # 先清理目标表
        if not clean_existing_data():
            return False

        # 写入目标表（使用更新模式）
        result.to_sql('ma_type', target_engine,
                      if_exists='append', index=False)

        print(f"成功转换并导入 {len(result)} 条记录到 ma_type")

        # 更新现有库存和租赁单价（根据type_id）
        with target_engine.connect() as conn:
            # 更新storage_num
            conn.execute("""
                UPDATE ma_type t, ma_machine_type s
                SET t.storage_num = s.STORAGE_NUM,
                    t.lease_price = s.LEASE_PRICE
                WHERE t.type_id = s.ID + 6000
            """)
            print("已更新现有库存和租赁单价")

        return True

    except Exception as e:
        print(f"处理 ma_machine_type 时发生错误: {str(e)}")
        return False


if __name__ == "__main__":
    process_machine_types()