Python swagger fastapi example

Python swagger fastapi example

Here's an example of how you can use Swagger and FastAPI to create a simple API with documentation:

Step 1: Install required dependencies

To get started, we'll need to install the necessary dependencies for our project. We'll be using Python as our programming language.

First, let's install FastAPI, which is a modern web framework that allows us to easily define and generate APIs:

pip install fastapi

Next, we'll install Swagger UI, which provides a user-friendly interface to explore our API:

pip install swagger-ui

Step 2: Create your FastAPI application

Now that we have the dependencies installed, let's create a new Python file for our FastAPI application:

# main.py
from fastapi import FastAPI
from pydantic import BaseModel
app = FastAPI()
class User(BaseModel):
name: str
email: str
@app.post("/users/")
async def create_user(user: User):
Store user data in a database or file, for example
print(f"User created: {user.name}, {user.email}")
return {"message": "User created successfully"}
Define another route
@app.get("/hello/{name}")
async def hello(name: str):
return f"Hello {name}!"

In this code, we've defined two routes for our API. The first one is a POST request that creates a new user with the provided data. The second one is a GET request that returns a greeting message with the name of the person.

Step 3: Generate Swagger documentation

To generate Swagger documentation for our API, we'll use the swagger_ui library:

from fastapi import FastAPI
import swagger_ui
app = FastAPI()
class User(BaseModel):
...
@app.post("/users/")
async def create_user(user: User):
...
Define another route
@app.get("/hello/{name}")
async def hello(name: str):
...
Generate Swagger documentation
swagger_ui = SwaggerUI(
app,
path="/docs",
title="My API Documentation",
description="This is my API documentation"
)
app.include_router(swagger_ui.router)

In this code, we've defined a SwaggerUI object that generates documentation for our API. We can customize the path and title of our documentation by providing additional arguments to the constructor.

Step 4: Run your FastAPI application

Finally, let's run our FastAPI application:

uvicorn main:app --host 0.0.0.0 --port 8000

This command starts a development server for our API that listens on port 8000 and hosts the Swagger documentation at http://localhost:8000/docs.

Step 5: Explore your Swagger documentation

Now, let's open a web browser and navigate to http://localhost:8000/docs. We should see our API documentation with information about each route, including request and response examples.

For example, if we click on the "POST /users/" route, we'll see a form that allows us to send a POST request with the required data:

{
"name": "John Doe",
"email": "[email protected]"
}

We can then press the "Send" button to create a new user and view the response in the Swagger UI.

This is just a simple example of how you can use FastAPI with Swagger documentation. With this setup, you can easily generate documentation for your API without having to write manual documentation or create separate tools like Doxygen or Javadoc.

I hope this helps! Let me know if you have any questions or need further assistance.

Python swagger fastapi github

I'd be happy to provide a response in English.

Python, Swagger, FastAPI, and GitHub: A Winning Combination

In the world of web development, there's no shortage of innovative tools and technologies that can help you build robust and scalable applications. In this response, I'll focus on Python, Swagger, FastAPI, and GitHub – four popular tools that, when used together, can significantly streamline your development workflow.

Python: A Powerhouse Programming Language

Python is a high-level, interpreted programming language known for its simplicity, flexibility, and ease of use. With millions of users worldwide, Python has become a staple in the developer community, particularly for data analysis, machine learning, web development, and more. Its vast library ecosystem, extensive documentation, and vast community support make it an excellent choice for any project.

Swagger: Documenting APIs with Ease

Swagger, also known as OpenAPI, is a popular framework for designing and documenting RESTful APIs. By using Swagger, developers can create robust API documentation that's easy to read and understand, making it simpler for other team members or even external partners to learn about your API's capabilities and usage. With Swagger, you can generate client code in various programming languages, ensuring seamless integration with your application.

FastAPI: A Modern Web Framework

FastAPI is a modern web framework built on top of Python 3.7+ and ASGI (Asynchronous Server Gateway Interface). It combines the speed and efficiency of Go with the ease-of-use and rapid development capabilities of Django. FastAPI supports async/await syntax, making it easy to write efficient, concurrent code that takes advantage of asynchronous I/O operations.

GitHub: The Central Hub for Collaboration

GitHub is a web-based platform that provides an incredible range of tools and services for version control, collaboration, and project management. Its core feature – the Git version control system – allows developers to track changes, collaborate on projects, and manage different versions of their codebase. GitHub's vast repository of open-source projects, extensive community support, and seamless integration with various development tools make it an essential hub for any developer.

Combining Python, Swagger, FastAPI, and GitHub: The Winning Combination

When you combine the power of Python with the flexibility of Swagger, the speed and efficiency of FastAPI, and the collaborative capabilities of GitHub, you get a winning combination that streamlines your development workflow. Here are some benefits:

In conclusion, Python, Swagger, FastAPI, and GitHub form a formidable combination that can help you build robust, scalable, and collaborative applications. By leveraging these tools, you can streamline your development workflow, reduce errors, and improve overall project efficiency – making you an even more valuable asset to your team or organization.