BrandCultivation/database/db/mysql.py

from config import load_config
import pandas as pd
from sqlalchemy import create_engine, text
from sqlalchemy.orm import sessionmaker
from sqlalchemy.exc import SQLAlchemyError
from tqdm import tqdm

cfgs = load_config()


class MySqlDatabaseHelper:
    _instance = None
    
    def __new__(cls):
        if not cls._instance:
            cls._instance = super(MySqlDatabaseHelper, cls).__new__(cls)
            cls._instance._initialized = False
        return cls._instance
        
    def __init__(self):
        if self._initialized:
            return
        
        self._host = cfgs['mysql']['host']
        self._port = cfgs['mysql']['port']
        self._user = cfgs['mysql']['user']
        self._passwd = cfgs['mysql']['passwd']
        self._dbname = cfgs['mysql']['db']
        
        self.connect_database()
        self._initialized = True
        
    def connect_database(self):
        # 创建数据库连接
        try:
            conn = "mysql+pymysql://" + self._user + ":" + self._passwd + "@" + self._host + ":" + str(self._port) + "/" + self._dbname
        except Exception as e:
            raise ConnectionAbortedError(f"failed to create connection string: {e}")
        
        # 通过连接池创建engine
        self.engine = create_engine(
            conn,
            pool_size=20, # 设置连接池大小
            max_overflow=30, # 超过连接池大小时的额外连接数
            pool_recycle=1800, # 回收连接时间
            pool_pre_ping=True, # 防止断开连接
            isolation_level="READ COMMITTED" # 降低隔离级别
        )
        
        self._DBSession = sessionmaker(bind=self.engine)
    
    def load_data_with_page(self, query, params, page_size=100000):
        """分页查询数据"""
        data = pd.DataFrame()
        count_query = text(query.replace("SELECT *", "SELECT COUNT(*)"))
        query += " LIMIT :limit OFFSET :offset"
        query = text(query)
    
        # 获取总行数
        total_rows = self.fetch_one(count_query, params)[0]

        page = 1
        with tqdm(total=total_rows, desc="Loading data", unit="rows") as pbar:  # 初始化进度条
            while True:
                offset = (page - 1) * page_size  # 计算偏移量
                params["limit"] = page_size
                params["offset"] = offset

                df = pd.DataFrame(self.fetch_all(query, params))
                if df.empty:
                    break
                data = pd.concat([data, df], ignore_index=True)
            
                # 更新进度条
                pbar.update(len(df))  # 更新进度条的行数
            
                page += 1
        return data
        
        
    def fetch_all(self, query, params=None):
        """执行SQL查询并返回所有结果"""
        session = self._DBSession()
        try:
            results = session.execute(query, params or {}).fetchall()
            return results
        except SQLAlchemyError as e:
            session.rollback()
            print(f"error: {e}")
        finally:
            session.close()
            
    def fetch_one(self, query, params=None):
        """执行SQL查询并返回单条结果"""
        session = self._DBSession()
        try:
            result = session.execute(query, params or {}).fetchone()
            return result
            
        except SQLAlchemyError as e:
            session.rollback()
            print(f"error: {e}")
        finally:
            session.close()
            
    def insert_data(self, table_name, data_dict):
        """插入单条数据到指定表"""
        if not data_dict:
            return 0
        
        columns = ", ".join(data_dict.keys())
        values = ", ".join([f":{key}" for key in data_dict.keys()])
        query = text(f"INSERT INTO {table_name} ({columns}) VALUES ({values})")
        
        session = self._DBSession()
        
        try:
            result = session.execute(query, data_dict)
            session.commit()
            return result.rowcount
        
        except SQLAlchemyError as e:
            session.rollback()
            print(f"Error inserting data: {e}")
            return 0
        finally:
            session.close()
            
    def update_data(self, table_name, update_dict, conditions, condition_params=None):
        """更新表中符合条件的数据"""
        if not update_dict:
            return 0
        
        set_clause = ", ".join([f"{key} = :{key}" for key in update_dict.keys()])
        
        if len(conditions) == 1:
            where_clause = f"WHERE {conditions[0]}"
        elif len(conditions) > 1:
            where_clause = f"WHERE {' AND '.join(conditions)}"
        else:
            where_clause = ""
        
        query = text(f"UPDATE {table_name} SET {set_clause} {where_clause}")
        
        params = update_dict.copy()
        if condition_params:
            params.update(condition_params)
            
        session = self._DBSession()
        try:
            result = session.execute(query, params)
            session.commit()
            return result.rowcount
        except SQLAlchemyError as e:
            session.rollback()
            print(f"Error updating data: {e}")
            return 0
        
        finally:
            session.close()
    
    def execute_query(self, query, params=None):
        """执行SQL语句 (无返回值, 如INSERT, UPDATE, DELETE)"""
        session = self._DBSession()
        try:
            session.execute(query, params or {})
            session.commit()
        except SQLAlchemyError as e:
            session.rollback()
            print(f"Error: {e}")
        finally:
            session.close()
            
if __name__ == '__main__':
    db_helper = MySqlDatabaseHelper()
    
    table_name = 'tads_brandcul_report'
    data_dict = {
        'cultivacation_id': 10000002,
        'city_uuid': '00000000000000000000000011445301',
        'limit_cycle_name': '202505W1(05.05-05.11)',
        'product_code': '440298',
        'product_info_table': 'D72E3FAE8DCE4270BD23C3EC015C0A35',
        'relation_table': 'AD889019FD4F4EE7B887981162BA09EC',
        'similarity_product_table': 'CE436AC24D96461FA0C091CB01E9BC05',
        'recommend_table': 'A7C5918B8DDB4BEA9D921936955CBAF6',
    }
    
    # db_helper.insert_data(table_name, data_dict)
    
    update_data = {"val_table": "A7C5918B8DDB4BEA9D921936955CBAF6"}
    conditions = [
        "cultivacation_id = :cultivacation_id",
        "city_uuid = :city_uuid"
    ]
    condition_params = {
        'cultivacation_id': 10000001,
        'city_uuid': '00000000000000000000000011445301',
    }
    
    db_helper.update_data(table_name, update_data, conditions, condition_params)