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Utkarsh Rastogi
Utkarsh Rastogi

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Day 1: What is FastAPI & Why Developers Love It

Welcome to Day 1 of the FastAPI Bootcamp – A Day-by-Day Guide series!

Over the next few days, we’ll dive into FastAPI — one of the most exciting frameworks in the Python ecosystem for building high-performance APIs.


🧠 What is FastAPI?

FastAPI is a modern, fast (high-performance) web framework for building APIs with Python 3.8+ using standard type hints. It’s designed to make it easy to build APIs quickly and efficiently while writing clean, production-ready code.

Built on top of Starlette for web handling and Pydantic for data validation, FastAPI combines speed, simplicity, and powerful features out of the box.


🔥 Top Features of FastAPI

  • ⚡ High Performance: Built on ASGI, FastAPI is one of the fastest Python web frameworks.
  • 🧾 Automatic Documentation: Generates Swagger UI and ReDoc from your code, instantly.
  • ✅ Data Validation: Uses Pydantic to validate and serialize input/output data automatically.
  • 🧠 Type Hints Support: Enables better editor support, autocompletion, and fewer bugs.
  • 🔄 Async-Ready: First-class support for asynchronous endpoints using async/await.
  • 📦 Modular & Scalable: Easy to structure large applications using routers and dependencies.

🤔 Why FastAPI Over Flask or Django?

Here's a quick comparison of FastAPI with other popular Python web frameworks:

Feature FastAPI Flask Django
Performance 🚀 Very High (ASGI + async support) ⚡ Moderate (WSGI, no native async) ⚡ Moderate (WSGI, limited async support)
API Documentation ✅ Built-in (Swagger, ReDoc) ❌ Requires extensions ❌ Requires third-party packages
Type Hinting & Editor Support ✅ First-class support ❌ Minimal ❌ Limited
Input Validation ✅ Automatic via Pydantic ❌ Manual or via extensions ❌ Form-based, not API-focused
Learning Curve 🟢 Moderate (if familiar with typing) 🟢 Beginner-friendly 🔴 Steeper due to full-stack features
Use Case Focus 🔥 API-first design 🔥 Lightweight web services 🏗️ Full-stack web applications
Async Support ✅ Native (ASGI & async/await) ❌ Experimental ⚠️ Partial, improving over time

🌍 Real-World Use Cases

FastAPI is widely used for:

  • Building RESTful APIs
  • Backend services for web/mobile apps
  • Deploying machine learning models
  • Microservices in modern architectures
  • Real-time or async-heavy systems

Big names like Netflix, Uber, and Microsoft are already using FastAPI in production environments.


🧰 Prerequisites for FastAPI on Windows

Before starting, ensure you have:

  • 🐍 Python 3.8+ (I’m using Python 3.12 for this FastAPI series.)
  • 💻 VS Code or any modern code editor
  • 📦 pip (Python package manager)

✅ Check Python Version

Open your terminal (Command Prompt or PowerShell) and run:

python --version

You should see an output like:


version

If not installed, download it from the official site: https://www.python.org/downloads/


⚙️ FastAPI Setup on Windows

📁 Step 1: Create a Project Folder

mkdir fastapi-demo
cd fastapi-demo


🧪 Step 2: Create a Virtual Environment

python -m venv venv
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venv

venv\Scripts\activate
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⚠️ Note: If you get any error while running this command, try using the below command first then use above command again:

Set-ExecutionPolicy -ExecutionPolicy Unrestricted -Scope CurrentUser
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Output

Once activated, your terminal prompt should show (venv) indicating the virtual environment is active.


📦 Step 3: Install FastAPI and Uvicorn

pip install fastapi uvicorn
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🧪 Create Your First FastAPI App

Create a file named main.py and add the following code:

from fastapi import FastAPI

app = FastAPI()

@app.get("/")
def read_root():
    return {"message": "Hello from FastAPI!"}
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Run the app using Uvicorn:

uvicorn main:app --reload
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Explanation:

  • main: the name of your Python file (without .py)
  • app: the FastAPI instance inside your file
  • --reload: enables auto-reload on code changes (great for development)

Command

Open your browser and visit:

Output

Docs


🌍 Real-World Use Cases

FastAPI is ideal for:

  • RESTful APIs & backend services
  • Machine Learning model serving
  • Microservices & async-heavy systems
  • Startups to enterprise-scale applications

🏢 Companies like Netflix, Uber, and Microsoft use it in production!


⚙️ What is Uvicorn?

Uvicorn is a lightning-fast ASGI server used to run FastAPI apps. It supports asynchronous programming, making your APIs scalable and high-performing.

  • 🔹 Built on uvloop and httptools
  • 🔹 Enables async/await support
  • 🔹 Supports hot-reloading during development
  • 🔹 Perfect match for FastAPI's async nature

With FastAPI + Uvicorn, you get near Node.js-level performance — using Python!


✅ Summary

Today you learned:

  • What FastAPI is and why it's gaining popularity
  • Key features that make FastAPI stand out from Flask/Django
  • Real-world use cases and industry adoption
  • How to set up FastAPI on Windows
  • Your first “Hello Message” API in FastAPI

This is just the beginning — more exciting stuff coming up in the next few days!


🙏 Credits

Huge thanks to the FastAPI Official Documentation by Sebastián Ramírez (@tiangolo) — the best place to learn and explore everything about FastAPI.


👨‍💻 About Me

Hey there! I’m Utkarsh Rastogi, an AWS Community Builder and passionate cloud-native enthusiast who loves building scalable backend systems and sharing knowledge with the community.

🔗 Connect with me: Utkarsh Rastogi


💬 Share Your Thoughts – I'd Love Your Feedback!

If you enjoyed today's post or learned something new, I'd truly appreciate it if you leave a comment or share your thoughts 👇

Your feedback, questions, or even a quick “🔥 Loved this!” keeps me motivated to continue this journey and share more in the upcoming #FastAPIDaily posts.

What did you find most helpful?

Anything you'd like explained in the next part?

Suggestions for improvement? I’m all ears! 🙌

Let’s grow and learn together — one FastAPI day at a time 🚀


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Top comments (1)

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Nathan Tarbert

Pretty cool, love when real setup steps and examples come in on day one. Makes me wanna just spin something up now.

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