Most Python portfolios look the same: a to-do app, a Titanic notebook, and not much else. Hiring managers screening backend and AI candidates want something sharper, and well-chosen FastAPI projects deliver it. The framework has moved from side-project favourite to production default, with the 2025 Stack Overflow Developer Survey showing FastAPI up five percentage points in a single year.
This guide gives you 15 FastAPI projects with source code, ordered from beginner to advanced, plus a clear way to present them. New to the language? Start with Scaler’s Python developer roadmap. If you are still asking what is fast api, the next section answers it in under a minute.
What Is FastAPI and Why Build FastAPI Projects With It?
According to the official FastAPI documentation, FastAPI is a modern Python web framework for building APIs. Created by Sebastián Ramírez and released in 2018, it runs on Starlette for async request handling and uses Pydantic to turn type hints into validation and OpenAPI docs, so a basic FastAPI example needs only a few lines.
Python itself rose about seven points to roughly 58% in the same survey, and FastAPI has become a common choice for model serving and AI backends. Netflix built its incident-management tool Dispatch on it. For you, that means FastAPI projects double as proof of API design, async Python, databases and deployment in a single repository.
Here is the smallest useful FastAPI example. Save it as main.py, run fastapi dev main.py, and open /docs for interactive Swagger UI.
from fastapi import FastAPI
from pydantic import BaseModel
app = FastAPI()
class Task(BaseModel):
title: str
done: bool = False
@app.post(“/tasks”)
def create_task(task: Task):
return task
Transform Your Career
Choose from our industry-leading programs designed for career success
Modern Software and AI Engineering Program
Master full-stack development with AI integration
+1000 more AI Forward Deployed Engineer with Specialisation in AI applications
Build and deploy AI solutions for real-world business problems
+1000 more Modern Data Science and ML with specialisation in AI
Advanced data science techniques with AI specialization
+1000 more Advanced AIML with Specialisation in Agentic AI
Deep dive into AIML with focus on Agentic systems
+1000 more DevOps, Cloud & AI Platform Engineering
Build and manage AI-powered cloud infrastructure
+1000 more AI Engineering Advanced Certification by IIT-Roorkee
Premier AI engineering certification from IIT-Roorkee
FastAPI Projects at a Glance: A Quick FastAPI List
Use this FastAPI list to pick two or three FastAPI projects from different levels instead of attempting all 15.
| # | Project | Level | Key tools |
| 1 | To-Do List API | Beginner | Pydantic, Uvicorn |
| 2 | URL Shortener | Beginner | Redis, PostgreSQL |
| 3 | Weather or Currency API Wrapper | Beginner | httpx, caching |
| 4 | Expense Tracker | Beginner | SQLModel, SQLite |
| 5 | Inventory API | Beginner | Pagination, filters |
| 6 | RealWorld Blog Backend | Intermediate | PostgreSQL, Docker |
| 7 | JWT Auth Service | Intermediate | OAuth2, JWT |
| 8 | WebSocket Chat App | Intermediate | WebSockets, Redis |
| 9 | E-Commerce Backend | Intermediate | SQLAlchemy 2.0, Redis |
| 10 | Full-Stack React App | Intermediate | React, Docker Compose |
| 11 | Monitored API | Intermediate | Prometheus, Grafana |
| 12 | File Processing Service | Intermediate | UploadFile, BackgroundTasks |
| 13 | ML Model Serving API | Advanced | Hugging Face, Docker |
| 14 | RAG Chatbot Backend | Advanced | Embeddings, vector DB |
| 15 | LangGraph Agent Service | Advanced | LangGraph, tracing |
Beginner FastAPI Projects With Source Code
Start here to learn routing, validation and databases. If Python syntax still slows you down, take Scaler’s free Python for Beginners course.
To-Do List API
Build full CRUD endpoints with Pydantic models, path and query parameters, and proper status codes, first in memory and then on a database. It teaches request validation, which every backend interview touches.
Source code: The official FastAPI tutorial walks through the same endpoints step by step.
URL Shortener
Generate short codes, redirect users, and cache hot links in Redis. Add JWT login and rate limiting to turn a weekend build into a service that handles abuse.
Source code: FastURL uses FastAPI, PostgreSQL, Redis, and JWT.
Weather or Currency API Wrapper
Call a third-party API with httpx, cache the responses, and expose clean endpoints. You practise async calls, timeouts and error handling without needing a database.
Source code: fastapi-cache by long2ice supplies the caching layer.
Expense Tracker With SQLModel
Store expenses, filter by category and return monthly totals. SQLModel, from the FastAPI author, merges SQLAlchemy and Pydantic models into one class. Refresh DBMS fundamentals if joins and indexes feel rusty.
Source code: SQLModel docs include a FastAPI walkthrough.
Inventory Management API
Create products and stock levels, then add a paginated fastapi list endpoint with search and sorting. Pagination is an interview staple and a common gap in beginner repos.
Source code: fastapi-pagination by uriyyo handles the heavy lifting.
Intermediate FastAPI Projects With Source Code
These FastAPI projects add authentication, real-time traffic and production concerns, the topics that appear in backend interviews alongside system design fundamentals.
Blog Backend (RealWorld Conduit)
Implement users, articles, comments, tags and favourites against the RealWorld spec, so any RealWorld frontend can plug into your API. It is the closest thing to a standard benchmark project.
Source code: nsidnev/fastapi-realworld-example-app runs on PostgreSQL with Docker.
JWT and OAuth2 Authentication Service
Build signup, login, token refresh, password reset and role-based access. Auth is the part reviewers probe hardest, so a clean implementation stands out.
Source code: fastapi-users is the reference library to study.
Real-Time Chat App With WebSockets
Create rooms, broadcast messages, and track who is online. Add Redis pub/sub once you need more than one server instance, which is where scaling questions begin.
Source code: The official WebSockets guide has a working chat example.
E-Commerce Backend
Model products, carts, orders, and payments using async SQLAlchemy 2.0, with Redis for sessions and caching. It mirrors the stack real product teams use.
Source code: FastAPI-boilerplate by benavlabs pairs Pydantic V2, SQLAlchemy 2.0, PostgreSQL and Redis.
Full-Stack App With React
Pair a FastAPI backend with a React frontend, PostgreSQL and Docker Compose. Recruiters like seeing both sides connected. Our React roadmap helps if the frontend is new to you.
Source code: fastapi-react is a starter, and the official full-stack-fastapi-template shows a production-style layout.
Monitored and Rate-Limited API
Add Prometheus metrics, structured logging and rate limits to any earlier build, then chart latency in Grafana. Observability separates a demo from a service. The DevOps roadmap covers the tooling.
Source code: prometheus-fastapi-instrumentator exposes metrics in a few lines.
File Upload and Background Processing Service
Accept images or CSVs with UploadFile, process them with BackgroundTasks or Celery, and expose a job-status endpoint. It shows you understand long-running work.
Source code: The official BackgroundTasks guide is the starting point.
Advanced FastAPI Projects With Source Code
AI teams use FastAPI to serve models and agents, so these FastAPI projects carry the most weight for AI engineering roles.
ML Model Serving API
Wrap a Hugging Face BERT model in a /predict endpoint, load it once at startup and containerise it. This is the pattern behind most model deployments, and the MLOps roadmap shows what comes next.
Source code: Deploy-BERT-for-Sentiment-Analysis-with-FastAPI by curiousily is the classic example.
RAG Chatbot Backend
Ingest documents, store embeddings in a vector database, and stream grounded answers from one endpoint. Add an admin view to inspect conversations.
Source code: chatbot-rag by JanDez pairs a FastAPI backend with an admin dashboard.
LangGraph Agent Service
Expose a multi-step agent behind authenticated endpoints, with memory, tracing, and rate limits. Our Agentic AI roadmap covers the concepts first.
Build these with mentor feedback
Tutorial repos teach the pattern, but reviews teach the judgment. Scaler’s AI & Machine Learning Program with Agentic AI covers RAG pipelines, fine-tuning, and production deployment with LangChain, LangGraph, CrewAI, and AutoGen.
Free Courses by top Scaler instructors
How to Showcase FastAPI Projects in Your Portfolio
Finished FastAPI projects only help if reviewers can run and understand them. Follow these steps for every build:
- Test the API with pytest and FastAPI’s TestClient, and show the coverage badge.
- Containerise the app with Docker so one command starts everything.
- Deploy it on a free tier and keep the live /docs link in your README.
- Write a README with an architecture diagram, endpoint table and setup steps.
- Use a current Python version and Pydantic v2, since Pydantic v1 support is being phased out of FastAPI.
- Study the structure in the official full-stack template and the awesome-fastapi-projects list before you refactor.
Conclusion
The best FastAPI projects are the ones you finish, deploy and can explain. Pick one beginner, one intermediate, and one advanced build from this FastAPI list, add tests and a README, and keep the live docs link handy for reviewers.
Backend and AI hiring both reward people who ship working APIs, and these FastAPI projects give you exactly that evidence. For more guides, browse our AI engineer roadmap.
Ready to go beyond side projects?
Scaler’s Software and AI Engineering Programme builds DSA, system design, and backend architecture to the depth product companies test, with an AI Companion in every lab and mentor-reviewed projects over 12 months.
Scaler Alumni and Their Success Stories
Also Explore These Projects to Build Your Portfolio
Frequently Asked Questions
What are good FastAPI projects for beginners?
Start with a to-do API, URL shortener, and expense tracker. These FastAPI projects cover CRUD, validation, and databases without heavy setup.
What is Fast API used for?
FastAPI builds REST APIs, ML model endpoints and real-time services. Any FastAPI example you run gets automatic validation and Swagger docs.
Where can I find FastAPI projects with source code?
Browse the fastapi list on GitHub’s fastapi topic, the awesome-fastapi-projects repo and the official full-stack template.
Is FastAPI good for a portfolio in 2026?
Yes. It was among the fastest-growing frameworks in the 2025 Stack Overflow survey, so FastAPI projects signal current backend skills.
How long does it take to build a FastAPI project?
Beginner builds take a weekend, while advanced FastAPI projects like RAG backends take two to four weeks with tests and deployment.
Should I pick FastAPI, Flask, or Django for projects?
Choose FastAPI for API-first and ML work, and Django for full web apps. FastAPI projects suit typed, async, documented APIs best.
