Metadata-Version: 2.1
Name: djagger
Version: 1.1.0
Summary: OpenAPI 3 documentation generator for Django using pydantic.
Home-page: https://github.com/royhzq/djagger
Author: Roy
Author-email: royhung@protonmail.com
License: MIT License
Download-URL: https://github.com/royhzq/djagger/archive/refs/tags/v0.1.0-alpha.tar.gz
Description: ===============================================================
        🗡️Djagger - OpenAPI schema generator for Django using pydantic
        ===============================================================
        
        .. |Package Badge| image:: https://github.com/royhzq/djagger/actions/workflows/python-package.yml/badge.svg
        .. |Pypi Badge| image:: https://badge.fury.io/py/djagger.svg
        
        |Package Badge| |Pypi Badge|
        
        
        Automated OpenAPI documentation generator for Django. Djagger provides you with a clean and straightforward way to generate a comprehensive API documentation of your Django project by utilizing pydantic to create schema objects for your views.  
        
        | Example Django project using Djagger: 
        | https://github.com/royhzq/djagger-example
        
        | Generated API documentation from the example project: 
        | https://djagger-example.netlify.app/  
        
        | The Djagger repo: 
        | https://github.com/royhzq/djagger  
        
        
        Djagger is designed to be:
        
        🧾 **Comprehensive** - Every aspect of your API should be document-able straight from your views, to the full extent of the OpenAPi 3.0 specification. 
        
        
        👐 **Unintrusive** - Integrate easily with your existing Django project. Djagger can document vanilla Django views (function-based and class-based views), as well as any Django REST framework views. As long as you are using Django's default URL routing, you are good to go. You do not need to redesign your APIs for better documentation.
        
        
        🍭 **Easy** - Djagger uses pure, unadulterated pydantic models to generate schemas. If you have used pydantic, there is no learning curve. If you have not heard of pydantic, it is a powerful data validation library that is pretty straightforward to pickup (like dataclasses). `Check it out here <https://pydantic-docs.helpmanual.io/>`_. Either way, documenting your APIs will feel less like a chore.
        
        Examples
        --------
        
        Example GET Endpoint
        ====================
        
        .. code:: python
        
            from rest_framework.views import APIView
            from rest_framework.response import Response
            from pydantic import BaseModel as Schema
            import datetime
        
        
            class ArticleDetailSchema(Schema):
                created : datetime.datetime
                title : str
                author : str
                content : str
        
        
            class RandomArticleAPI(APIView):
                """Return a random article from the Blog"""
        
                response_schema = ArticleDetailSchema
        
                def get(self, request):
                    ...
                    return Response({})
        
        
        **Generated documentation**
        
        .. image:: https://user-images.githubusercontent.com/32057276/148027310-3248b5aa-f8a5-46d1-b044-044d001dcddd.png
          :width: 800
          :alt: UserDetailsAPI Redoc
          :target: https://djagger-example.netlify.app/#tag/Blog/paths/~1blog~1articles~1random/get
          
        Example POST Endpoint
        =====================
        
        .. code:: python
        
            from rest_framework.views import APIView
            from rest_framework.response import Response
            from pydantic import BaseModel as Schema, Field
            import datetime
        
        
            class ArticleDetailSchema(Schema):
                created : datetime.datetime
                title : str
                author : str
                content : str
        
            class ArticleCreateSchema(Schema):
                """POST schema for blog article creation"""
                title : str = Field(description="Title of Blog article")
                content : str = Field(description="Blog article content")
        
        
            class ArticleCreateAPI(APIView):
        
                request_schema = ArticleCreateSchema
                response_schema = ArticleDetailSchema
        
                def post(self, request):
                    ...
                    return Response({})
        
        
        
        
        **Generated documentation**
        
        .. image:: https://user-images.githubusercontent.com/32057276/148027403-4acca98c-e4af-4265-a9f5-c385f143be73.png
          :width: 800
          :alt: CreateItemAPI Redoc
          :target: https://djagger-example.netlify.app/#tag/Blog/paths/~1blog~1articles~1create/post
          
        
        Documentation & Support
        =======================
        * This project is in continuous development. If you have any questions or would like to contribute, please email `royhung@protonmail.com <royhung@protonmail.com>`_
        * If you want to support this project, do give it a ⭐ on github!
        
Platform: UNKNOWN
Classifier: Environment :: Web Environment
Classifier: Framework :: Django
Classifier: Framework :: Django :: 3.0
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: BSD License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Topic :: Internet :: WWW/HTTP
Classifier: Topic :: Internet :: WWW/HTTP :: Dynamic Content
Requires-Python: >=3.6
Description-Content-Type: text/x-rst
