BrandCultivation/dao/mysql_client.py

#!/usr/bin/env python3
# -*- coding:utf-8 -*-
import os
from sqlalchemy import create_engine, text
from sqlalchemy.dialects.mysql import pymysql
from sqlalchemy.orm import sessionmaker
from sqlalchemy.ext.declarative import declarative_base
from config import load_config
import pandas as pd
import sys

cfgs = load_config()

class Mysql(object):
    def __init__(self):
        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']
        
        # 通过连接池创建engine
        self.engine = create_engine(
            self._connect(self._host, self._port, self._user, self._passwd, self._dbname),
            pool_size=10, # 设置连接池大小
            max_overflow=20, # 超过连接池大小时的额外连接数
            pool_recycle=3600 # 回收连接时间
        )
        self._DBSession = sessionmaker(bind=self.engine)

    def _connect(self, host, port, user, pwd, db):
        try:
            client = "mysql+pymysql://" + user + ":" + pwd + "@" + host + ":" + str(port) + "/" + db
            return client
        except Exception as e:
            raise ConnectionError(f"failed to create connection string: {e}")
        
    def create_session(self):
        """创建返回一个新的数据库session"""
        return self._DBSession()
    
    def fetch_data_with_pagination(self, tablename, query_text, field_name, city_uuid, page=1, page_size=1000):
        """分页查询数据，并根据 city_uuid 进行过滤"""
        offset = (page - 1) * page_size  # 计算偏移量
        query = text(f"SELECT {query_text} FROM {tablename} WHERE {field_name} = :city_uuid LIMIT :limit OFFSET :offset")
    
        with self.create_session() as session:
            results = session.execute(query, {"city_uuid": city_uuid, "limit": page_size, "offset": offset}).fetchall()
            df = pd.DataFrame(results)
    
        return df
    
    def load_data(self, tablename, query_text, field_name, city_uuid, page=1, page_size=1000):
        # 创建一个空的DataFrame用于存储所有数据
        total_df = pd.DataFrame()
    
        try:
            while True:
                df = self.fetch_data_with_pagination(tablename, query_text, field_name, city_uuid, page, page_size)
                if df.empty:
                    break
            
                total_df = pd.concat([total_df, df], ignore_index=True)
                print(f"Page {page}: Retrieved {len(df)} rows, Total rows so far: {len(total_df)}")
                page += 1  # 继续下一页
                
        except Exception as e:
            print(f"Error: {e}")
            return None
        
        finally:
            self.closed()
            return total_df
        
    def load_mock_data(self, tablename, query_text, page=1, page_size=1000):
        # 创建一个空的DataFrame用于存储所有数据
        total_df = pd.DataFrame()
    
        try:
            while True:
                offset = (page - 1) * page_size  # 计算偏移量
                query = text(f"SELECT {query_text} FROM {tablename} LIMIT :limit OFFSET :offset")
    
                with self.create_session() as session:
                    results = session.execute(query, { "limit": page_size, "offset": offset}).fetchall()
                    df = pd.DataFrame(results)
                if df.empty:
                    break
            
                total_df = pd.concat([total_df, df], ignore_index=True)
                print(f"Page {page}: Retrieved {len(df)} rows, Total rows so far: {len(total_df)}")
                page += 1  # 继续下一页
                
        except Exception as e:
            print(f"Error: {e}")
            return None
        
        finally:
            self.closed()
            return total_df
    
    def closed(self):
        """关闭连接，回收资源"""
        self.engine.dispose()


if __name__ == '__main__':
    
    client = Mysql()
    tablename = "mock_order"
    
    # 设置分页参数
    page = 1
    page_size = 1000
    
    query_text = '*'
    client.load_data("mock_order", query_text, page, page_size)