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A lazy MySQL client for Python that simplifies database operations with intuitive methods for CRUD operations, automatic connection management, and result formatting. Features include easy-to-use SELECT, INSERT, UPDATE, DELETE operations with pandas DataFrame support, where clause builders, and table export capabilities.

Project description

Lazy_mysql

zread

简体中文

一个轻量级的Python库,为MySQL数据库操作提供简洁优雅的解决方案。

✨ 核心特性

  • 🔌 统一SQL执行接口 - 简化复杂的数据库操作流程
  • 📊 智能查询构建器 - 支持复杂条件、多表关联、排序限制
  • 💾 批量数据操作 - 自动优化策略,支持超大数量级数据处理
  • 🔄 Upsert支持 - 智能判断存在更新/不存在插入
  • 🛡️ 安全防注入 - 参数化查询,自动SQL注入防护
  • 📈 结果格式化 - 支持DataFrame、字典、列表等多种格式输出
  • 📝 表结构导出 - 一键导出Markdown格式文档
  • 高性能优化 - LOAD DATA INFILE支持,百万级数据秒级处理

🚀 快速安装

pip install --upgrade lazy-mysql

🎯 快速开始

1. 数据库连接初始化

from lazy_mysql import SQLExecutor, MySQLConfig, NDayInterval

# 创建数据库配置
config = MySQLConfig(
    host='localhost',
    user='your_username',
    passwd='your_password',
    database='your_database'
)

# 指定数据库
executor = SQLExecutor(config, database='database')

# 不传入配置时自动从环境变量读取:
# LAZY_MYSQL_HOST / LAZY_MYSQL_PORT / LAZY_MYSQL_USER / LAZY_MYSQL_PASSWD / LAZY_MYSQL_DATABASE

# 支持混合配置:host/user/passwd 从环境变量读取,database 由参数指定
executor = SQLExecutor(database='another_db')

2. 智能查询操作

# 基础查询(select 自动构造 SQL)
users = executor.select('users', ['id', 'name', 'email'])
print(users)

# 手写复杂 SQL(query 直接执行)
result = executor.query(
    "SELECT id, name, RANK() OVER (ORDER BY score DESC) as rank FROM users",
    fetch_config={'output_format': 'df_dict', 'data_label': ['id', 'name', 'rank']}
)

# 条件查询 + 排序限制
active_users = executor.select(
    'users',
    ['id', 'name', 'email'],
    conditions={'status': 'active', 'age': ('>', 18)},
    order_by='created_at DESC',
    limit=10
)

# 复杂条件查询
results = executor.select(
    'users',
    ['id', 'name', 'score'],
    conditions={
        'status': ('IN', ['active', 'premium']),
        'score': ('BETWEEN', [80, 100]),
        'name': ('LIKE', '%John%'),
        'order_dateTime': ('>=', NDayInterval(7))  # 最近7天
    },
    fetch_config={'output_format': 'df'}  # 返回DataFrame格式
)

3. 使用完毕后关闭连接

# 直接关闭数据库连接
executor.close()
# 提交数据并关闭连接
executor.commit_close()

📚 详细文档

🔗 连接与配置

🔍 查询操作

💾 数据修改

🛠️ SQL工具函数

  • SQL工具函数 - add_limit条件构建、build_where/build_sql_with_where WHERE子句构建、resolve_sql智能路径解析、load_sql文件加载

📦 PyPI 项目

项目已发布到PyPI,可通过以下链接访问:

🔧 环境要求

  • Python: 3.10+
  • MySQL: 8.0.36+
  • 依赖库:
    • mysql-connector-python>=9.4.0
    • pandas>=2.3.1

📄 开源协议

本项目采用MIT开源协议 - 详见 LICENSE 文件

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