A modern FastAPI application demonstrating REST API development with Python, featuring a patient management system with realistic healthcare data.

This repository showcases a complete FastAPI learning journey, building a patient management REST API from scratch. Perfect for developers learning modern Python web development, API design, and data validation patterns.

🔑 Key Learning Areas:

• Building RESTful APIs with FastAPI
• Data validation using Pydantic models
• Working with JSON datasets
• API documentation and testing
• Modern Python development practices

FastAPI/ ├── main.py # FastAPI application with all endpoints ├── patient_dataset.json # Sample patient data (50+ records) ├── 00_Introduction.md # API fundamentals and concepts ├── 01_Pydantic.md # Pydantic usage and validation guide ├── LICENSE # MIT License └── README.md # This documentation 

• Python 3.8 or higher
• pip or uv (recommended for faster installs)

# 1️⃣ Clone the repository git clone https://github.com/Sourabh-Kumar04/FastAPI.git cd FastAPI # 2️⃣ Install uv (if not already installed) curl -LsSf https://astral.sh/uv/install.sh | sh # 3️⃣ Install dependencies uv add fastapi uvicorn # 4️⃣ Run the development server uv run uvicorn main:app --reload

# Clone and setup git clone https://github.com/Sourabh-Kumar04/FastAPI.git cd FastAPI # Create virtual environment python -m venv venv source venv/bin/activate # On Windows: venv\Scripts\activate # Install dependencies pip install fastapi uvicorn # Run the server uvicorn main:app --reload

Once running, access your API at:

• 🔥 Interactive API Docs (Swagger UI): http://localhost:8000/docs
• 📖 Alternative Docs (ReDoc): http://localhost:8000/redoc
• ⚡ API Base: http://localhost:8000

curl http://localhost:8000/view

curl http://localhost:8000/patient/1

# Sort by age (oldest first) curl "http://localhost:8000/sort?sort_by=age&order=desc" # Sort alphabetically by name curl "http://localhost:8000/sort?sort_by=name&order=asc"

import requests # Base URL base_url = "http://localhost:8000" # Get all patients response = requests.get(f"{base_url}/view") patients = response.json() print(f"Total patients: {len(patients)}") # Get specific patient patient_response = requests.get(f"{base_url}/patient/5") if patient_response.status_code == 200: patient = patient_response.json() print(f"Patient: {patient['name']}, Age: {patient['age']}") else: print("Patient not found") # Get sorted patients sorted_response = requests.get(f"{base_url}/sort", params={ "sort_by": "age", "order": "desc" }) sorted_patients = sorted_response.json() print(f"Oldest patient: {sorted_patients[0]['name']} ({sorted_patients[0]['age']} years)")

The patient_dataset.json contains 50+ realistic patient records for testing and development purposes.

Each patient record includes:

{ "id": 1, "name": "Sumer Saini", "age": 55, "gender": "Male", "contact": "+915335225484", "email": "sahotakiaan@shroff.info", "address": "H.No. 452, Hora Marg, Hindupur 334089", "blood_group": "A+", "medical_history": [ "Cardiac issues", "COVID-19", "Hypertension" ], "admission_date": "2025-07-09", "discharge_date": "2025-07-19", "doctor_assigned": "Dr. Rohit Nair", "current_status": "Discharged" }

This repository includes comprehensive learning materials:

API Fundamentals & System Design

• What are REST APIs and why they matter
• HTTP methods and status codes
• Monolithic vs Microservice architectures
• API integration with Machine Learning systems
• Testing tools and best practices

Advanced Data Validation with Pydantic

• Pydantic models and type hints
• Data validation and serialization
• Nested models and complex data structures
• Environment variables and settings management
• Custom validators and error handling

• FastAPI Framework: Route definition, request handling, response formatting
• Pydantic Integration: Automatic data validation, type conversion, error messages
• API Design: RESTful principles, endpoint organization, query parameters
• Data Handling: JSON processing, sorting algorithms, error handling
• Development Tools: Virtual environments, package management, development servers

Use the built-in Swagger UI at http://localhost:8000/docs to:

• View all available endpoints
• Test API calls directly in the browser
• See request/response schemas
• Understand parameter requirements

# Test all endpoints curl http://localhost:8000/ curl http://localhost:8000/about curl http://localhost:8000/view curl http://localhost:8000/patient/10 curl "http://localhost:8000/sort?sort_by=name&order=asc"

# Make changes to main.py # Server automatically reloads (thanks to --reload flag) # Test changes at http://localhost:8000/docs # Check logs in terminal for any errors

# Using uv (recommended) uv add package-name # Using pip pip install package-name pip freeze > requirements.txt

1. Database Integration

   • Replace JSON file with PostgreSQL or SQLite
   • Add SQLAlchemy ORM for database operations
   • Implement connection pooling

2. Advanced Features

   • POST endpoint to create new patients
   • PUT endpoint to update patient information
   • DELETE endpoint to remove patients
   • Search functionality with filters

3. Authentication & Security

   • JWT token-based authentication
   • Role-based access control (Admin, Doctor, Nurse)
   • API rate limiting and security headers

4. Production Deployment

   • Docker containerization
   • Environment configuration
   • Logging and monitoring
   • CI/CD pipeline with GitHub Actions

• Explore the interactive docs thoroughly
• Try modifying the patient data structure
• Add new endpoints for specific use cases
• Experiment with different query parameters
• Study the error handling patterns

Feel free to contribute to this learning project! Here's how:

1. Fork the repository
2. Create a feature branch (git checkout -b feature/new-endpoint)
3. Make your changes and test them
4. Commit your changes (git commit -am 'Add new search endpoint')
5. Push to the branch (git push origin feature/new-endpoint)
6. Create a Pull Request

• Check the existing issues on GitHub
• Create a new issue with detailed description
• Include steps to reproduce the problem

• FastAPI Documentation: https://fastapi.tiangolo.com/
• Pydantic Documentation: https://docs.pydantic.dev/
• Python Type Hints: https://docs.python.org/3/library/typing.html
• HTTP Status Codes: https://httpstatuses.com/
• REST API Design: https://restfulapi.net/

• FastAPI official tutorial
• REST API design principles
• Python async/await concepts
• JSON data handling in Python

This project is licensed under the MIT License - see the LICENSE file for details.

What this means:

• ✅ Commercial use allowed
• ✅ Modification allowed
• ✅ Distribution allowed
• ✅ Private use allowed
• ❗ License and copyright notice required

Sourabh Kumar
CS Student @University of Delhi | AWS AIML Scholar'24

Passionate about AI/ML and software development, exploring modern web technologies and building practical applications for learning and growth.

• 🌐 GitHub: @Sourabh-Kumar04
• 🎓 University: University of Delhi (Computer Science)

If this repository helped you learn FastAPI or understand API development:

• ⭐ Star this repository to show your support
• 🍴 Fork it to create your own version
• 📢 Share it with fellow developers
• 💡 Contribute improvements or new features
• 🐛 Report issues to help others