Metadata-Version: 2.1
Name: ex-dataclass
Version: 1.2.0
Summary: A more powerful data model management than DataClass that reduces maintenance costs and improves coding efficiency.
Home-page: https://github.com/Shadow-linux/ex_dataclass
Author: ShadowYD
Author-email: 972367265@qq.com
License: UNKNOWN
Platform: UNKNOWN
Requires-Python: >=3.7
License-File: LICENSE

ex\_dataclass
=============

|LICENSE| |VERSION| |PYPI| |LANGUAGE| |codebeat badge|

ex\_dataclass 是什么？
~~~~~~~~~~~~~~~~~~~~~~

-  它一款继基于 ``dataclass`` 开发的 ``python``
   库，但对数据模型处理更加的友好。它通过 **Python3类型注解**
   能轻易的处理 ``dict`` 与自定义 ``class``
   间的转换，从而明确复杂数据模型的类型，降低维护代码的压力及有效降低操作复杂数据难度。
-  它在配合 ``Python3 typing``
   模块的特殊容器的类型注解能实现更多高级功能；

特性
~~~~

-  **注解类型**
-  [x] **int**
-  [x] **str**
-  [x] **float**
-  [x] **bool**
-  [x] **dict**
-  [x] **list**
-  [x] **typing.Dict**
-  [x] **typing.List**
-  [x] **typing.Union**
-  [x] **typing.Type**

-  **功能**
-  [x] 支持 ``ex_dataclass`` 类型继承的正反解析；
-  [x] 支持 ``typing.List`` 中 ``ex_dataclass`` 类型正反解析；
-  [x] 支持 ``typing.List``
   嵌套正反解析，如：\ ``{a: [[{a:1, b:2}, {a:3, b:4}]]}``
-  [x] 支持 ``typing.Union`` 和 ``typing.Type``
   特殊容器类型注解的多态行为，精确匹配字段存在最多 ``ex_dataclass`` 类
-  [x] 支持反向解析下存在冗余字段，默认行为是抛弃冗余字段（可进行配置）
-  [x] 支持typing.Union 和 typing.Type 特殊容器类型相互嵌套场景
-  [ ] 支持 ``ex_dataccass``
   字段检测校验，通过类型注解获取类后进行值的校验；

快速开始
~~~~~~~~

  示例 1

-  `typing 模块介绍 <https://juejin.cn/post/6939159210991026190>`__
-  `typing 官方文档 <https://docs.python.org/3/library/typing.html>`__

.. code:: python

    import typing
    from ex_dataclass import ex_dataclass, asdict, field, EXPack

    data = {
        "teams": [
            {
                "team_name": "Team-A",
                "users"    : [
                    {
                        "name": "zhangsan",
                        "age" : 18,
                    },
                    {
                        "name": "lisi",
                        "age" : 18,
                    }
                ]
            },
    {
                "team_name": "Team-B",
                "users"    : [
                    {
                        "name": "jack",
                        "age" : 18,
                    },
                    {
                        "name": "rose",
                        "age" : 18,
                    }
                ]
            }
        ]
    }


    @ex_dataclass
    class User:
        # default_factory: 需要给一个类（可callable）
        name: str = field(default_factory=str)
        # default: 给定一个默认值
        age: int = field(default=0)


    @ex_dataclass
    class Team:
        team_name: str = field(default_factory=str)
        # 没有值时，我们设置一个list给users字段
        users: typing.List[User] = field(default_factory=list)


    @ex_dataclass
    class AllTeam:
        teams: typing.List[Team] = field(default_factory=list)


    # 看看TeamUser 接受参数或字典

    all_team = AllTeam(**data)
    # 可以看到运行结果，所有类型都被转换成对象，对象在python中是非常的友好可以进行全方位自动补全，并且方便维护；
    print(all_team)
    # AllTeam(teams=[Team(team_name='Team-A', users=[User(name='', age=18), User(name='', age=18)]), Team(team_name='Team-B', users=[User(name='', age=18), User(name='', age=18)])])
    print(all_team.teams)
    # [Team(team_name='Team-A', users=[User(name='', age=18), User(name='', age=18)]), Team(team_name='Team-B', users=[User(name='', age=18), User(name='', age=18)])]
    print(all_team.teams[0].team_name)
    print(all_team.teams[0].users)
    # Team-A
    # [User(name='', age=18), User(name='', age=18)]
    print(all_team.teams[0].users[0].name)
    # zhangsan

    # 重新转回字典
    print(asdict(all_team))
    # {'teams': [{'team_name': 'Team-A', 'users': [{'name': 'zhangsan', 'age': 18}, {'name': 'lisi', 'age': 18}]}, {'team_name': 'Team-B', 'users': [{'name': 'jack', 'age': 18}, {'name': 'rose', 'age': 18}]}]}

-  看完第一个示例应该能发现 ``ex_dataclass``
   对数据转换成对象，全凭的是我们在属性字段后面写的\ **类型注解**\ 。通过这样的转换能力，我们就可以摆脱
   ``data_dict["a"]["b"]["c"]`` 这样取值的复杂场景；

  示例 2 \* 在继承关系中 ``ex_dataclass``
   依旧能准确识别你所需要转换的类型。

.. code:: python


    @ex_dataclass
    class Person:
        # default_factory: 需要给一个类（可callable）
        name: str = field(default_factory=str)
        # default: 给定一个默认值
        age: int = field(default=0)
        height: float = field(default=float)
        weight: float = field(default=float)


    @ex_dataclass
    class PersonDetails:
        address: str = field(default_factory=str)
        hobbies: typing.List[str] = field(default_factory=list)
        phone: str = field(default_factory=str)


    # 继承person使其拥有person的熟悉
    @ex_dataclass
    class Male(Person):
        gender: str = field(default="male")


    @ex_dataclass
    class Female(Person):
        gender: str = field(default="female")


    @ex_dataclass
    class Jack(Male):
        # 当你默认值需要PersonDetails 对象时，可以写入到default_factory, 如果不需要则写dict或None
        details: PersonDetails = field(default_factory=PersonDetails)


    @ex_dataclass
    class Rose(Female):
        details: PersonDetails = field(default_factory=dict)


    # 最终初始化两个人物，使用参数初始化, 这里并没有给出gender，因为已经设置默认值了
    jack = Jack(
            name="jack",
            age=18,
            height=1.80,
            weight=125.0,
            details={
                "address": "xxxx",
                "hobbies": ["aa", "bb", "cc"],
                "phone"  : "123456789"
            }
    )
    # 使用字典初始化
    rose = Rose(
            name="rose",
            age=18,
            height=1.680,
            weight=98.0,
            details={
                "address": "xxxx",
                "hobbies": ["aa", "bb", "cc"],
                "phone"  : "987654321"
            }
    )
    print(jack)
    print(jack.details.phone)
    print(rose)
    print(rose.details.phone)
    # Jack(name='jack', age=18, height=1.8, weight=125.0, gender='male', details=PersonDetails(address='xxxx', hobbies=['aa', 'bb', 'cc'], phone='123456789'))
    # 123456789
    # Rose(name='rose', age=18, height=1.68, weight=98.0, gender='female', details=PersonDetails(address='xxxx', hobbies=['aa', 'bb', 'cc'], phone='987654321'))
    # 987654321

-  若当前 **``ex_dataclass``** 库对你有帮助请给个 🌟 予以支持;

  实例 3

https://github.com/Shadow-linux/ex\_dataclass

更多详细用法
~~~~~~~~~~~~

https://github.com/Shadow-linux/ex\_dataclass

联系方式
~~~~~~~~

-  可以通过 **issue** 提出建议或意见。
-  EMail: 972367265@qq.com

.. |LICENSE| image:: https://img.shields.io/github/license/Shadow-linux/ex_dataclass
   :target: https://img.shields.io/github/license/Shadow-linux/ex_dataclass
.. |VERSION| image:: https://img.shields.io/github/v/release/Shadow-linux/ex_dataclass
   :target: https://img.shields.io/github/v/release/Shadow-linux/ex_dataclass
.. |PYPI| image:: https://img.shields.io/pypi/v/ex-dataclass
   :target: https://img.shields.io/pypi/v/ex-dataclass
.. |LANGUAGE| image:: https://img.shields.io/badge/python-3.7%2B-blue
   :target: https://img.shields.io/badge/python-3.7%2B-blue
.. |codebeat badge| image:: https://codebeat.co/badges/495b3202-92b5-4301-8afd-1e146e62fe3e
   :target: https://codebeat.co/projects/github-com-shadow-linux-ex_dataclass-master


