Metadata-Version: 2.1
Name: apischema
Version: 0.10.1
Summary: JSON (de)serialization + schema generation through python typing, with a spoonful of sugar.
Home-page: https://github.com/wyfo/apischema
Author: Joseph Perez
Author-email: joperez@hotmail.fr
License: MIT
Description: # Apischema
        
        Makes your life easier when it comes to python API.
        
        JSON (de)serialization + schema generation through python typing, with a spoonful of sugar.
        
        ## Documentation
        
        [https://wyfo.github.io/apischema/](https://wyfo.github.io/apischema/)
        
        ## Install
        ```shell
        pip install apischema
        ```
        It requires only Python 3.6+ (and dataclasses [official backport](https://pypi.org/project/dataclasses/) for version 3.6 only)
        
        *PyPy3* is fully supported.
        
        ## Why another library?
        
        This library fulfill the following goals:
        
        - stay as close as possible to the standard library (dataclasses, typing, etc.) to be as accessible as possible — as a consequence do not need plugins for editor/linter/etc.;
        - be additive and tunable, be able to work with user own types as well as foreign libraries ones; do not need a PR for handling new types like `bson.ObjectId`;
        - avoid dynamic things like using string for attribute name.
        
        No known alternative achieves that.
        
        (Actually, *Apischema* is even adaptable enough to enable support of "rival" libraries in a few dozens of line of code)
        
        ## Example
        
        ```python
        from dataclasses import dataclass, field
        from uuid import UUID, uuid4
        
        from pytest import raises
        
        from apischema import ValidationError, deserialize, serialize
        from apischema.json_schema import deserialization_schema
        
        
        # Define a schema with standard dataclasses
        @dataclass
        class Resource:
            id: UUID
            name: str
            tags: set[str] = field(default_factory=set)
        
        
        # Get some data
        uuid = uuid4()
        data = {"id": str(uuid), "name": "wyfo", "tags": ["some_tag"]}
        # Deserialize data
        resource = deserialize(Resource, data)
        assert resource == Resource(uuid, "wyfo", {"some_tag"})
        # Serialize objects
        assert serialize(resource) == data
        # Validate during deserialization
        with raises(ValidationError) as err:  # pytest check exception is raised
            deserialize(Resource, {"id": "42", "name": "wyfo"})
        assert serialize(err.value) == [  # ValidationError is serializable
            {"loc": ["id"], "err": ["badly formed hexadecimal UUID string"]}
        ]
        # Generate JSON Schema
        assert deserialization_schema(Resource) == {
            "$schema": "http://json-schema.org/draft/2019-09/schema#",
            "type": "object",
            "properties": {
                "id": {"type": "string", "format": "uuid"},
                "name": {"type": "string"},
                "tags": {"type": "array", "items": {"type": "string"}, "uniqueItems": True},
            },
            "required": ["id", "name"],
            "additionalProperties": False,
        }
        ```
        *Apischema* works out of the box with your data model.
        
        [*Let's start the Apischema tour.*](https://wyfo.github.io/apischema/)
        
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Requires-Python: >=3.6
Description-Content-Type: text/markdown
