Modules

Introduction To Python
  1. Advantages Of Learning Python As The First Programming Language
  2. Easy Python Setup Guide For Beginners
Basic Syntax And Variables
  1. Python Syntax Fundamentals
  2. Python Variables And Data Types
  3. Python Basic Operations
Control Flow
  1. Python Conditional Statements
  2. Python Loops
Functions And Modules
  1. Defining And Calling Python Functions
  2. Introduction To Python Modules And Importing
  3. Understanding Python Built In Functions Part 1
  4. Understanding Python Built In Functions Part 2
  5. Understanding Python Built In Functions Part 3
  6. Understanding Python Built In Functions Part 4
  7. Understanding Python Lambda Functions
Python Lists And Touples
  1. Manipulate Python Lists And Touples
  2. 5 Ways To Remove Items From A Python List By Index
  3. 5 Different Approaches To Check For Duplicate Values In Python Lists
  4. 5 Different Approaches To Check For A Specific Value In Python Lists
  5. 5 Various Approaches To Modify Elements In Python Lists
  6. Understanding Shallow Copy And Deep Copy In Python Lists
  7. 6 Various Approaches To Duplicating Lists In Python
  8. Exploring 8 Various Iteration Techniques In Python Lists
  9. Exploring Python List Concatenation Methods
  10. All You Must Know About Python Slicing
  11. Exploring Various Methods For Comparing Python Lists
  12. Converting Various Data Types To Python Lists
  13. Removing Duplicate Values From Python Lists
  14. Extend A Python List To A Desired Length
  15. Shorten A Python List To A Specific Length
  16. Efficient Ways To Creating Sequences In Python
Python Dictionaries
  1. Manipulate Python Dictionaries
  2. Understanding Python Enumerate Dictionary
  3. Efficient Ways Removing Items From Python Dictionaries
  4. 5 Different Ways To Check For Duplicate Values In Python Dictionaries
  5. Check For A Specific Value In Python Dictionaries
  6. Get Values By Key In Python Nested Dictionary
  7. Modify Values By Key In Python Nested Dictionary
  8. 7 Different Ways To Duplicating A Dictionary In Python
  9. 5 Various Iteration Techniques In Python Dict
  10. 4 Different Methods For Dictionary Concatenation In Python
  11. 4 Different Ways Of Comparing Python Dicts
  12. Converting Various Data Types To Python Dictionaries
  13. Efficient Ways To Remove Duplicate Values From Python Dictionaries
  14. Extend A Python Dictionary To A Desired Length
  15. Shorten Python Dictionaries To A Specific Length
  16. Efficient Approaches To Remove An Item By Value In Python Dictionaries
Python Sets
  1. Manipulate Python Sets
File Handling
  1. Reading From And Writing To Files In Python
  2. Python File Modes And Handling Exceptions
Object Oriented Programming
  1. Python Classes And Objects
  2. Python Inheritance Encapsulation And Polymorphism
Python Advanced Data Structures
  1. Python Collection Module
  2. Advanced Python Data Manipulation Techniques
Error Handling And Debugging
  1. Python Exception Handling
  2. Python Debugging Techniques And Tools
Regular Expressions
  1. Python Regular Expressions In Text Processing
  2. Python Regular Expressions Pattern Matching
Concurrency And Parallelism
  1. Threading Vs Multiprocessing In Python
  2. How To Achieve Concurrency And Parallelism In Python
  3. Concurrent Programming With Asyncio
Working With Apis
  1. Making Http Requests In Python
  2. Parsing Json Xml Responses In Python
Build Apis With Python Requests
  1. Python Requests Crud Operations
  2. Retry In Python Requests
  3. Python Requests Timeout
Build Apis With Python Urllib3
  1. Disabling Hostname Verification In Python Example
Build Apis With Python Aiohttp
  1. Asynchronous Crud Operations In Python
  2. Retry In Python Aiohttp Async Requests
Database Interaction
  1. Connecting To Databases In Python
  2. Python Crud Operations And Orm Libraries
Python For Web Development
  1. Introduction To Python Web Frameworks
  2. Building Web Applications Using Flask
  3. Building Web Applications Using Django
Data Analysis And Visualization
  1. Introduction To Numpy Pandas And Matplotlib
  2. Analyzing Datasets And Visualizations In Python
Machine Learning With Python
  1. Machine Learning Concepts And Python
  2. Introduction To Scikit Learn And Tensorflow Keras
Python Typing Module
  1. Type Error Not Subscriptable While Using Typing
All Course > Python > Python For Web Development Dec 14, 2023

Building Web Applications Using Fastapi

FastAPI is a powerful Python web framework that enables developers to rapidly build robust and efficient web applications. In this article, we'll provide a comprehensive introduction to using FastAPI for building web applications, covering everything from setting up a basic project to deploying it to a production environment.

Getting Started with FastAPI

To begin building web applications with FastAPI, you’ll first need to install it using pip, the Python package manager. You can do this by running the following command in your terminal:

pip install fastapi uvicorn

Once FastAPI is installed, you can create a new Python file for your web application. Let’s start with a simple example of a FastAPI app that exposes a single endpoint to greet users:

from fastapi import FastAPI

app = FastAPI()

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

Save this code in a file named main.py. You can then run your FastAPI app using the Uvicorn ASGI server:

uvicorn main:app --reload

Building RESTful APIs with FastAPI

One of the key features of FastAPI is its support for building RESTful APIs with minimal code. FastAPI automatically generates OpenAPI documentation for your API, making it easy for other developers to understand and interact with your endpoints.

from fastapi import FastAPI
from pydantic import BaseModel

app = FastAPI()

class Item(BaseModel):
    name: str
    price: float

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

In this example, we define a data model using Pydantic, a data validation library for Python. We then create a POST endpoint that expects a JSON payload representing an Item object. FastAPI automatically handles parsing the JSON data and validating it against the defined data model.

Handling Path Parameters

@app.get("/items/{item_id}")
async def read_item(item_id: int):
    return {"item_id": item_id}

In this example, we define a GET endpoint that expects a path parameter item_id. FastAPI automatically converts the parameter to the specified type (int in this case) and passes it to the handler function.

Query Parameters

@app.get("/items/")
async def read_items(skip: int = 0, limit: int = 10):
    return {"skip": skip, "limit": limit}

This endpoint accepts optional query parameters skip and limit, with default values of 0 and 10, respectively. These parameters can be used to paginate through a collection of items.

Deploying FastAPI Apps to Production

Deploying a FastAPI app to a production environment is straightforward thanks to its compatibility with ASGI servers like Uvicorn and Hypercorn. You can deploy your FastAPI app to platforms like AWS, Google Cloud, or Heroku using Docker containers for easy scalability and management.

docker build -t my-fastapi-app .
docker run -d -p 80:80 my-fastapi-app

Conclusion

FastAPI is a modern Python web framework that combines speed, simplicity, and scalability, making it an excellent choice for building web applications, especially RESTful APIs. By following the steps outlined in this article, you can quickly get started with FastAPI and begin building powerful web applications with ease.

FAQ

Q: What is FastAPI?
A: FastAPI is a modern web framework for building APIs with Python. It is designed to be fast, easy to use, and highly efficient, making it ideal for building web applications and microservices.

Q: How does FastAPI compare to other Python web frameworks?
A: FastAPI offers performance comparable to Node.js and Go frameworks while maintaining the ease of development and productivity benefits of Python. It also provides automatic interactive API documentation and validation, which is not available in many other frameworks.

Q: Can I use FastAPI for building frontend applications?
A: While FastAPI is primarily designed for building backend APIs, you can certainly use it to serve HTML pages and static assets for frontend applications. You can use templates or frontend frameworks like React or Vue.js to build the frontend and integrate it with your FastAPI backend.

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Tags: python