FastAPI web Framework

Create simple CRUD application in FastAPI framework beginner-friendly

FastAPI is a web framework for developing web applications. It builds on top of Starlette and Pydantic. Starlette handles HTTP requests, and Pydantic is used for data and type validations. I am trying to make tutorial very, very simple so that anyone can learn and start coding

1. It is fast.
2. Built-in swagger.
3. Use AGI (Asynchronous Server Gateway Interface).

Installation

In order to work with fastAPI, we need to install the FastAPI, Uvicorn, and pydantic libraries

pip install fastapi uvicorn pydantic

Create the first program

from fastapi import FastAPI

api= FastAPI()

@api.get("/")
def users():
    return 'Hello'

Save this file.

Here we import FastAPI, create an object of FastAPI, and assign it to api variable.
We use this api variable to take requests using @ with that and define the type of request.

Run the program

uvicorn <filename>:<object-name> — — reload

uvicorn main:app --reload

Use localhost:8000 to run in a browser.
For the Swagger document: localhost:8000/docs

Path Parameter

A path parameter is an endpoint of a web URL.

from fastapi import FastAPI

api= FastAPI()

@api.get("/user/{id}")
def userDetail(id):
    return id

Run using localhost:8000/user/1

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Validation:

We can add validation by using typing library

from fastapi import FastAPI
from typing import Annotated

api= FastAPI()

@api.get("/hello/{id}")
def userDetail(id: Annotated[int, Path(len=3)]):
    return id

Query Parameter

The query parameter is defined in the function only

from fastapi import FastAPI

api= FastAPI()

@api.get("/user")
def userDetail(id):
    return id

We can use swagger for this query parameter or define in the URL by localhost:8000/user?id=1

POST

The POST method is the way to send and store new data. Pydantic is a prerequisite to use this method. We need to create a Pydantic model.

from fastapi import FastAPI
from pydantic import BaseModel

class User(BaseModel):
    name:str
    age:int 
    height:int


api= FastAPI()

@api.post("/save")
def save(user: User):
    ## perforn operations to store values in file or db
    return JSONResponse(status_code=200, content=user.model_dump_json())

We can test by using Postman or Swagger docs. We pass values in JSON format. http://localhost:8000/docs

PUT

PUT is being used for updating data.

from fastapi import FastAPI
from pydantic import BaseModel

class User(BaseModel):
    name:str
    age:int 
    height:int

api= FastAPI()

@api.put("/update/{id}")
def save(id:int, user: User):
    ## perforn operations to update values in file or db
    return JSONResponse(status_code=200, content=user.model_dump_json())

DELETE

The delete method is being used for deleting data.

from fastapi import FastAPI

api= FastAPI()

@api.delete("/delete/{id}")
def delete(id:int):
    ## perforn operations to delete values in file or db
    return JSONResponse(status_code=200, content=['Deleted'])