FastAPI Blog & Product System

A robust, scalable backend API built with FastAPI and Python, designed to power modern web applications. This project features a complete user management system, content creation workflows (blogs/articles), product handling, and real-time communication capabilities.

It is designed to serve as a solid foundation for backend engineering, with a focus on clean architecture, authentication, and database relationships.

🚀 Tech Stack

Backend

• Framework: FastAPI - High performance, easy to learn, fast to code, ready for production.
• Language: Python 3.9+
• Database: SQLite (Development) with SQLAlchemy ORM.
• Authentication: OAuth2 with Password (and Hashing) + JWT Tokens.
• Real-time: WebSockets.
• Validation: Pydantic models.

Frontend

• React: The project structure includes a React App folder for the frontend application. The backend is pre-configured with CORS to allow requests from a React app running on http://localhost:3000.
• Demo Client: A lightweight HTML/JS client (client.py) is included to demonstrate real-time WebSocket chat functionality.

✨ Key Features

🔐 Authentication & Security

• User Registration & Login: Secure user creation with password hashing (bcrypt).
• JWT Tokens: API endpoints are secured using JSON Web Tokens.
• Permissions: Resource access control (e.g., only authors can delete their posts).

📝 Content Management

• Articles & Blogs: logic for creating, reading, updating, and deleting (CRUD) textual content.
• Database Relationships: One-to-Many relationship between Users and Articles (Users can own multiple articles).
• Image Uploads: Dedicated endpoint (/upload) to handle file uploads, serving them statically from the /files directory.

💬 Real-Time Chat

• WebSockets: Implemented a two-way interactive chat endpoint (/chat) that broadcasts messages to all connected clients.
• Middleware: Custom middleware to track and log process duration for every request.

🛒 Products

• Product API: Endpoints to handle product data, demonstrating validation and complex query parameters.

📂 Project Structure

.
├── Get Method/
│   ├── main.py             # Application entry point
│   ├── auth/               # Authentication logic (JWT, OAuth2)
│   ├── db/                 # Database models and session handling
│   │   ├── models.py       # SQLAlchemy Database Tables (Users, Articles)
│   │   └── database.py     # Database connection
│   ├── Routers/            # API Route handlers (clean separation of concerns)
│   │   ├── blog_get.py     # Blog retrieval logic
│   │   ├── blog_post.py    # Blog creation logic
│   │   ├── user.py         # User management endpoints
│   │   ├── article.py      # Article management endpoints
│   │   └── ...
│   ├── templates/          # Jinja2 templates for server-side rendering
│   └── client.py           # WebSocket client demo
├── React App/              # Frontend React Application (Placeholder/Repository)
├── .gitignore              # Git configuration
└── requirements.txt        # Python dependencies

🗄️ Database Schema

The application uses a relational database model:

• Users Table (users)

  • id: Integer, Primary Key
  • username: String
  • email: String
  • password: String (Hashed)
  • items: Relationship to Articles

• Items/Articles Table (items)

  • id: Integer, Primary Key
  • title: String
  • content: String
  • published: Boolean
  • user_id: Foreign Key to Users table

🔧 Setup & Running

1. Clone the repository

2. Create a virtual environment

   python -m venv venv
   source venv/bin/activate  # On Windows: venv\Scripts\activate

3. Install dependencies

   pip install -r requirements.txt

4. Run the Backend Navigate to the source directory:

   cd "Get Method"
   uvicorn main:app --reload

   The API will be available at http://localhost:8000.

5. Explore the API Open your browser and navigate to http://localhost:8000/docs to see the interactive Swagger UI documentation. You can test all endpoints directly from there.

6. Run WebSocket Demo Open http://localhost:8000/ or the specific chat endpoint to test real-time messaging.

🔮 Future Improvements

• Complete the React frontend implementation in the React App directory.
• Migrate database to PostgreSQL for production.
• Add Unit Tests using pytest (some structure already exists in test_main.py).