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Whether you’re working on a personal project or building an enterprise-grade application, being able to quickly set up a REST API can save valuable time and resources.

In this blog post, we’ll explore how you can build REST API in 5 Minutes with FastAPI, and we’ll delve into why it’s a game-changer for developers.

Maybe we know FastAPI is a web framework of Python. The meaning of its name expresses what is more special about this framework than others. The very new features of Python async and await are here. The API is really fast like nodeJS and Go (They claimed).
The more interesting thing is the implementation time of the REST API. The first endpoint will take at most five minutes to implement including the API docs.
What I have discussed here is that you can find all those things in FastAPI official documentation. It is much richer than other web frameworks in Python.

Almost everything you can find there.

Let’s try to create your virtual environment.

 

Python3 -m venv myenv

 

What Makes FastAPI Stand Out?

Before diving into the steps of building a REST API, let’s first understand why FastAPI has become one of the most popular frameworks among developers:

  1. Blazing Fast Performance: FastAPI is one of the fastest Python frameworks available, rivaling the performance of Node.js and Go. This is thanks to its use of asynchronous programming and the Starlette framework underneath. It’s built on top of Starlette for the web parts and Pydantic for the data parts, making it incredibly efficient.

  2. Automatic Interactive Documentation: FastAPI automatically generates interactive API documentation (with Swagger UI and ReDoc) based on the structure of your API. This feature is particularly beneficial for larger teams, where clear communication of API endpoints is crucial.

  3. Easy Integration with Other Tools: FastAPI integrates smoothly with other Python libraries and tools. It works perfectly with SQLAlchemy for database management, Pydantic for data validation, and OAuth2 for security, among others.

  4. Developer-Friendly: With its support for Python-type hints, FastAPI provides enhanced editor support for auto-completion, type checking, and more. This makes the development process faster and reduces the risk of runtime errors.

  5. Built-In Validation: FastAPI uses Pydantic models to validate request data, which reduces the need for boilerplate code and ensures that your API endpoints are robust and error-free.

 

Exploring FastAPI’s Effective Sides Beyond Basics

FastAPI isn’t just about quickly building APIs; it offers several other advantages that can significantly enhance your development process:

1. Asynchronous Capabilities

In a world where web applications need to handle a large number of concurrent users, asynchronous programming is essential. FastAPI’s design embraces async/await syntax, allowing you to write code that can handle multiple requests simultaneously without blocking operations.

Example:

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

 

2. Dependency Injection

FastAPI’s dependency injection system is a powerful feature that allows you to inject dependencies into your endpoints. This is useful for handling complex logic, such as database connections, user authentication, or external API calls, without cluttering your endpoint logic.

Example:

from fastapi import Depends def get_db(): db = "database_connection" try: yield db finally: pass # Cleanup code @app.get("/items/{item_id}") def read_item(item_id: int, db=Depends(get_db)): return {"item_id": item_id, "db": db}

 

3. Security and Authentication

FastAPI makes it easy to implement security measures like OAuth2, JWT tokens, and API keys. You can secure your endpoints with minimal code, ensuring your API remains safe from unauthorized access.

Example:

 

from fastapi.security import OAuth2PasswordBearer oauth2_scheme = OAuth2PasswordBearer(tokenUrl="token") @app.get("/users/me") async def read_users_me(token: str = Depends(oauth2_scheme)): return {"token": token}

 

4. Data Validation and Serialization with Pydantic

Pydantic is at the core of FastAPI’s data validation and serialization. You can define Pydantic models that describe the shape of your request and response data, and FastAPI will automatically validate incoming requests and serialize outgoing responses.

Example:

 

from pydantic import BaseModel

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

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

 

Conclusion

FastAPI isn’t just another Python web framework; it’s a strategic tool for developers who need to build efficient, scalable, and maintainable APIs quickly. Its combination of speed, ease of use, and robust features like automatic documentation, asynchronous capabilities, and built-in validation make it a go-to choice for both small and large projects.

Whether you’re a seasoned developer or just starting, FastAPI offers a seamless experience that can help you accelerate your development process without compromising on performance or security. With just a few lines of code, you can have a fully functioning API ready to serve your application’s needs.

So why wait?

Start exploring FastAPI today and see how it can transform the way you build web applications.

Md. Raisul Islam
Author: Md. Raisul Islam
09/05/2023
Software Development Engineer

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