pgmanage 2.0.2

pgsql数据库工具

使用说明

本程序包用到的库：psycopg3 官方文档：https://www.psycopg.org/psycopg3/docs/advanced/pool.html#other-ways-to-create-a-pool 开源地址：https://gitee.com/manjim/pgmanage

# 依赖模块
psycopg[binary,pool]

# pandas df 转列表字典
data = dfbb.to_dict(orient='records')

1. 下载安装

# 安装
pip install pgmanage

# 升级
pip install --upgrade pgmanage

# 卸载
pip uninstall pgmanage

2. 导入包模块

from pgmanage import PgPool         # 数据库连接池模块
from pgmanage import PgExec         # 全功能模块 包含连接池
from pgmanage import AsyncPgPool    # 异步数据库连接池模块
from pgmanage import AsyncPgExec    # 异步全功能模块 包含连接池

数据库连接字符串

根据环境变量配置的数据库字符串，自动链接数据库。也可传入连接字符串参数。

环境变量名称：PGLINK_URL
链接字符串示例：'dbname=shop_data user=postgres password=1116666688 host=127.0.0.1 port=5432'
环境变量写法示例：PGLINK_URL='dbname=shop_data user=postgres password=1116666688 host=127.0.0.1 port=5432'

3.使用示例

同步模式

• 示例1——PgPool

from pgmanage import PgPool

dbm = PgPool()
with dbm.pool.connection() as conn:
    with conn.cursor() as cur:
        cur.execute("SELECT 1")
        data = cur.fetchone()
        print("查询结果:",data)
# 使用完成后会自动关闭连接池

• 示例2-PgExec

# 设置日志
import logging
logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
logger = logging.getLogger(__name__)

from pgmanage import PgExec

def main():

    # 生成10万行的测试数据
    data_to_bulk_insert = []
    for i in range(100000):
        data_to_bulk_insert.append({'id': f'{i}', 'name': f'name{i}88','name2': f'name{i}88', 'age': i % 100, 'email': f'email{i}@example.com','fasle': True})


    # 创建数据库管理器实例
    db_mgr = PgExec()

    # 写入数据，主键冲突时更新所有非主键列 upsert_data
    rows_inserted = db_mgr.upsert_data(
        schema='data_test', 
        table='table_test', 
        data=data_to_bulk_insert,
        batch_size=10000,
        update=True,
        create=True,
        add_columns=True,
        max_workers=10,
    )
    logger.info(f"总共插入 {rows_inserted} 行")

    # 执行 SQL 查询
    query = "SELECT * FROM data_test.table_test LIMIT 10;"
    result = db_mgr.exec_query(query)
    for row in result:
        logger.info(row)
        
    # 删除数据
    query = "delete  FROM data_test.table_test;"
    result = db_mgr.exec_query_rowcount(query)
    logger.info(f"删除结果:{result}")

if __name__ == '__main__':
    main()

• 示例3-同步copy模式

if __name__ == '__main__':
    # 示例用法
    from pgmanage import CopyToPGSQL
    import pandas as pd
    from pdcleaner import DataSet

    # 初始化连接池
    PGLINK_URL = 'dbname=shop_data host=127.0.0.1 port=5432 user=postgres2 password=55555688'
    conn=psycopg.connect(PGLINK_URL)

    # 示例数据
    schema = 'douyin_shop'
    table = 'dy_dp_dd_ddgl_bzbb_copy12'
    data = pd.read_csv(r"C:\Users\manji\Downloads\抖音订单\1752550967_6e03f011910e5e4414e47f8f6dc317c8OtkVGLHs.csv", dtype=str)
    data = DataSet.clean_data(data, add_time=True)
    print(f"数据清洗完成，数据行数: {len(data)}")


    # 执行COPY
    copier = CopyToPGSQL()
    copier.copyrun(
        conn=conn,
        schema=schema,
        table=table,
        data=data,
        update=True,
        create=True,
        db_only=True,
        skipPK=True
    )

    conn.close()

异步模式

• 示例1——AsyncPgPool

import asyncio
from pgmanage import AsyncPgPool
async def main():
    try:
        # 初始化连接池
        pool = await AsyncPgPool.initialize()

        # 使用连接池执行数据库操作
        async with pool.connection() as conn:
            async with conn.cursor() as cur:
                await cur.execute("SELECT 1")
                rows = await cur.fetchall()
                for row in rows:
                    print("查询结果:",row)
    except Exception as e:
        logger.error(f"发生错误: {e}")
        raise

if __name__ == "__main__":
    asyncio.run(main())

• 示例2-AsyncPgExec

import logging
import asyncio
from pgmanage import AsyncPgExec

# 设置日志
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)


# 使用示例
async def main():
    import os
    DBURI = os.environ.get("PGLINK_URL")
    
    # 方式1：使用上下文管理器（推荐）
    async with AsyncPgExec(DBURI) as dbmange:
        # 生成测试数据
        data_to_bulk_insert = [
            {'id': f'{i}', 'name': f'name{i}88', 'age': i % 100, 
             'email': f'email{i}@example.com', 'fasle': True}
            for i in range(100000)
        ]

        result = await dbmange.upsert_data(
            'data_test', 'table_test', data_to_bulk_insert,
            batch_size=10000, update=True, create=True, add_columns=True
        )
        
        logger.info(f"总共成功插入或更新了 {result} 条记录")


    # 方式2：直接使用（程序结束时会自动关闭连接池）
    # 生成测试数据
    data_to_bulk_insert = [
        {'id': f'{i}', 'name': f'name{i}88', 'age': i % 100, 
         'email': f'email{i}@example.com', 'fasle': True}
        for i in range(100000)
    ]
    db_exec = AsyncPgExec(DBURI)
    db_exec.pool = await db_exec.async_pool.initialize()
    result = await db_exec.upsert_data(
        'data_test', 'table_test', data_to_bulk_insert,
        batch_size=10000, update=True, create=True, add_columns=True
    )
    logger.info(f"总共成功插入或更新了 {result} 条记录")
    # 不需要手动关闭，atexit 会处理

if __name__ == "__main__":
    asyncio.run(main())