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Getting Started with FastAPI

Getting Started with FastAPI, a high-performance, web framework for building APIs with Python

FastAPI is a modern, high-performance, web framework for building APIs with Python. It's designed to be easy to use, efficient, and to provide automatic generation of interactive documentation. FastAPI is built on top of Starlette and Pydantic, and it leverages Python 3.6+ type hints for request and response validation.

Getting Started with FastAPI - Tutorial provided by AppSeed.

In this introduction, I'll provide you with code samples to help you get started with FastAPI.

✅ Installation​

You can install FastAPI using pip:

pip install fastapi

You'll also want to install a web server like uvicorn to serve your FastAPI application:

pip install uvicorn

✅ Creating a FastAPI App​

Here's a basic example of a FastAPI application:

from fastapi import FastAPI

app = FastAPI()

@app.get("/")
async def read_root():
    return {"message": "Hello, World"}

Save this code to a Python file (e.g., main.py).

✅ Running the FastAPI App​

You can run your FastAPI app using uvicorn:

uvicorn main:app --reload

This command tells uvicorn to run the app instance in the main.py file and enables auto-reloading for development.

✅ Routes and Path Parameters​

FastAPI makes it easy to define routes and path parameters. Here's an example that includes path parameters:

from fastapi import FastAPI

app = FastAPI()

@app.get("/")
async def read_root():
    return {"message": "Hello, World"}

@app.get("/items/{item_id}")
async def read_item(item_id: int, query_param: str = None):
    return {"item_id": item_id, "query_param": query_param}

In this example, we define a route /items/{item_id} that takes an item_id as a path parameter and an optional query_param as a query parameter.

✅ Request and Response Models​

FastAPI allows you to define request and response models using Pydantic models. Here's an example:

from fastapi import FastAPI
from pydantic import BaseModel

app = FastAPI()

class Item(BaseModel):
    name: str
    description: str = None
    price: float
    tax: float = None

@app.post("/items/")
async def create_item(item: Item):
    return item

In this example, we define a Pydantic model Item for the request body of the POST request to /items/. FastAPI automatically validates and parses the incoming JSON data based on this model.

✅ Automatic Documentation​

One of FastAPI's standout features is its automatic generation of interactive API documentation. To access the documentation, go to http://localhost:8000/docs in your web browser while your FastAPI app is running.

✅ Validation and Serialization​

FastAPI automatically validates incoming requests and serializes responses based on the Pydantic models you define. If data doesn't match the expected model, FastAPI will return validation errors.

✅ In Summary​

These are just some of the basics of FastAPI. It provides many more features for building robust and efficient APIs, including dependency injection, authentication, and more.

FastAPI's official documentation is excellent and provides in-depth information on all of its features - FastAPI Official Documentation.

✅ Resources​