For more on how to create a Postman collection, see here Generating A Postman Collection from Laravel In testing APIs, I use PostMan to test and document my APIs by creating a collection under a namespace with PostMan. The API documentation can act as the central reference that keeps all the team members aligned on what your API’s objectives are, and how the API’s resources are exposed Įnables bugs and issues identification in the API’s architecture when defining it with the team And this helps internal and external users to understand the API and know what it can do It helps your internal teams know the details of your resources, methods, and their associated requests and responses, making maintenance and updates quicker Īgreement on API specs for the endpoints, data, types, attributes and more. Leads to good product maintenance and quicker updates. New users will start being productive earlier and will not depend on a person (already with the knowledge) who would need to spend slots of their time to explain how the API is design and how it works Improves the experience for developers consuming an API ĭecreases the amount of time spent on-boarding new users (internal developers or external partners). Why? Take a look to the following points:
CONVERT POSTMAN COLLECTION TO OPENAPI SOFTWARE
Why document APIs?Įven though working with Agile, and one of the principles being “Working Software Over Comprehensive Documentation”, from Agile Manifesto, documentation matters, and we invest our time doing it. Some aspects of API documentation can be generated automatically via Swagger or other documents. It also provides updates on the API’s lifecycle such as new versions or retirement. It includes instructions on how to effectively use and integrate the API. Swagger is my preferred way of sharing my API documentation with my colleagues and teams.ĪPI documentation is technical content that documents the API. Getting these collections out to be shared with teams(internal/external) in a clean format can be a pain sometimes. It’s used in testing API endpoints which can be grouped into project based collections. The previous screenshots were taken with Visual Studio Code.If I’m not mistaken, Postman is the most popular REST client out there. There were even some changes to Pydantic itself to support this.
This is not by chance, the whole framework was built around that design.Īnd it was thoroughly tested at the design phase, before any implementation, to ensure it would work with all the editors. You also get error checks for incorrect type operations: In your editor, inside your function you will get type hints and completion everywhere (this wouldn't happen if you received a dict instead of a Pydantic model): The JSON Schemas of your models will be part of your OpenAPI generated schema, and will be shown in the interactive API docs:Īnd will be also used in the API docs inside each path operation that needs them:
post ( "/items/" ) async def create_item ( item : Item ): return item
From typing import Union from fastapi import FastAPI from pydantic import BaseModel class Item ( BaseModel ): name : str description : Union = None price : float tax : Union = None app = FastAPI ().
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