Python库 | marshmallow_dataclass-0.5.2.tar.gz

# marshmallow_dataclass [](https://travis-ci.org/lovasoa/marshmallow_dataclass) [](https://badge.fury.io/py/marshmallow-dataclass) Automatic generation of [marshmallow](https://marshmallow.readthedocs.io/) schemas from dataclasses. Specifying a schema to which your data should conform is very useful, both for (de)serialization and for documentation. However, using schemas in python often means having both a class to represent your data and a class to represent its schema, which means duplicated code that could fall out of sync. With the new features of python 3.6, types can be defined for class members, and that allows libraries like this one to generate schemas automatically. An use case would be to document APIs (with [flasgger](https://github.com/rochacbruno/flasgger#flasgger), for instance) in a way that allows you to statically check that the code matches the documentation. ## How to use You simply import [`marshmallow_dataclass.dataclass`](https://lovasoa.github.io/marshmallow_dataclass/html/marshmallow_dataclass.html#marshmallow_dataclass.dataclass) instead of [`dataclasses.dataclass`](https://docs.python.org/3/library/dataclasses.html#dataclasses.dataclass). It adds a `Schema` property to the generated class, containing a marshmallow [Schema](https://marshmallow.readthedocs.io/en/2.x-line/api_reference.html#marshmallow.Schema) class. If you need to specify custom properties on your marshmallow fields (such as `attribute`, `error`, `validate`, `required`, `dump_only`, `error_messages`, `description` ...) you can add them using the `metadata` argument of the [`field`](https://docs.python.org/3/library/dataclasses.html#dataclasses.field) function. ```python from dataclasses import field from marshmallow_dataclass import dataclass # Importing from marshmallow_dataclass instead of dataclasses import marshmallow.validate from typing import List, Optional @dataclass class Building: # The field metadata is used to instantiate the marshmallow field height: float = field(metadata={'validate': marshmallow.validate.Range(min=0)}) name: str = field(default="anonymous") @dataclass class City: name: Optional[str] buildings: List[Building] = field(default_factory=lambda: []) # City.Schema contains a marshmallow schema class city, _ = City.Schema().load({ "name": "Paris", "buildings": [ {"name": "Eiffel Tower", "height":324} ] }) # Serializing city as a json string city_json, _ = City.Schema().dumps(city) ``` The previous syntax is very convenient, as the only change you have to apply to your existing code is update the `dataclass` import. However, as the `.Schema` property is added dynamically, it can confuse type checkers. If you want to avoid that, you can also use the standard `dataclass` decorator, and generate the schema manually using [`class_schema`](https://lovasoa.github.io/marshmallow_dataclass/html/marshmallow_dataclass.html#marshmallow_dataclass.class_schema) : ```python from dataclasses import dataclass from datetime import datetime import marshmallow_dataclass @dataclass class Person: name: str birth: datetime PersonSchema = marshmallow_dataclass.class_schema(Person) ``` You can also declare the schema as a [`ClassVar`](https://docs.python.org/3/library/typing.html#typing.ClassVar): ```python from marshmallow_dataclass import dataclass from marshmallow import Schema from typing import ClassVar, Type @dataclass class Point: x:float y:float Schema: ClassVar[Type[Schema]] = Schema ``` You can specify the [`Meta`](https://marshmallow.readthedocs.io/en/3.0/api_reference.html#marshmallow.Schema.Meta) just as you would in a marshmallow Schema: ```python from marshmallow_dataclass import dataclass @dataclass class Point: x:float y:float class Meta: ordered = True ``` ## installation This package [is hosted on pypi](https://pypi.org/project/marshmallow-dataclass/) : ```shell pipenv install marshmallow-dataclass ``` ## Documentation The project documentation is hosted on github pages: - [documentation](https://lovasoa.github.io/marshmallow_dataclass/). ## Usage warning This library depends on python's standard [typing](https://docs.python.org/3/library/typing.html) library, which is [provisional](https://docs.python.org/3/glossary.html#term-provisional-api).