Metadata-Version: 2.1
Name: AutoMD
Version: 1.2.0
Summary: AutoMD is a documentation library for Flask APIs build with FlaskRESTful and Webargs.
Home-page: https://github.com/cliftbar/automd
Author: Cameron Barclift
Author-email: cwbarclift@gmail.com
License: MIT
Description: # AutoMD
        AutoMD is a documentation library for Flask APIs build with FlaskRESTful and Webargs.
        Endpoint parameters and basic responses are automatically parsed into the OpenAPI specification,
        using Type Hints and introspection, and a endpoints registered to serve the specification.
        
        ## Motivation
        Documentation libraries tend to rely heavily on elaborate docstrings and static generation from source code.
        This library requires minimal changes to existing code, and most information (especially parameter specs)
        doesn't rely on keeping docstrings up to date.
        
        ## Installation
        AutoMD is available through PyPi.  Install using pip:
        ```
        pip install automd
        ```
        
        AutoMD also install the following dependancies:
        - Flask
        - FlaskRESTful
        - Webargs
        - ApiSpec
        - PyYAML
        
        ## Usage
        ### AutoMD registration/initialization
        The first step is to initialize the AutoMD app from a FlaskRESTful Api.
        
        ```python
        app: Flask = Flask(__name__)
        api: Api = Api(app)
        
        spec: AutoMDApp = AutoMDApp(api, "AutoMD Test App", "1.0.0", "3.0.0")
        ``` 
        
        After that, all that is *required* is adding the `@automd` decorator to an existing Resource endpoint.
        
        ```python
        class MinimalStatus(Resource):
            get_query_arguments = {
                "text": fields.String(required=False)
            }
        
            @automd()
            @use_kwargs(get_query_arguments)
            def get(self, text):
                return text
        ```
        which will mark the endpoint for inclusion in the OpenAPI spec.  In this example, the spec information
        will be pretty limited, but will still have the API url, argument, and a default value.
        
        With more complete python annotations, more information can be gleaned:
        ```python
        class IntrospectionStatus(Resource):
            post_query_arguments = {
                "text": fields.String(required=False)
            }
        
            @automd()
            @use_kwargs(post_query_arguments, location="json")
            def post(self, text: str = "Hello AutoMD") -> str:
                ret_text: str = "status check OK"
        
                if text is not None:
                    ret_text = f"{ret_text}: {text}"
        
                return ret_text
        ```
        From this the APISpec also get the parameter type, default value, and API response type.  It does not get the parameter
        location yet though, that takes more aguements to automd.
        
        Filling in more information in the webargs fields, automd decorator, use_kwargs decorator, and using one of the
        AutoMD response classes for type annotation and  gives even better information:
        ```python
        class Status(Resource):
            get_query_arguments = {
                "text": fields.String(required=False, description='Text to return', doc_default="Hello AutoMD")
            }
        
            @automd(parameter_schema=get_query_arguments,
                     summary="Status Endpoint",
                     description="Status Endpoint, responds with a message made from the input string")
            @use_kwargs(get_query_arguments, location="query")
            def get(self, text: str = None) -> ValueResponse:
                log_text: str = "status check OK"
        
                log_text = f"{log_text}: {text or 'Hello AutoMD'}"
        
                return ValueResponse(log_text)
        ```
        
        With this information, argument types, return types, summaries, descriptions, detailed default
        information, and parameter location info (body, query, etc) is included.  Summary and description
        are the only "magic strings" needed, and those will generally not change much or be onerous to
        keep up to date compared to the automatically grabbed information.
        
        An example Flask API app is provided to showcase some functionality.  Start it using `run.py`.
        A sample of the OpenAPI spec generated is [here](https://cliftbar.github.io/automd/documentation/sample_spec.html).
        
Platform: any
Classifier: Environment :: Web Environment
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Topic :: Internet :: WWW/HTTP :: Dynamic Content
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Description-Content-Type: text/markdown
