Modern API Suite

A comprehensive collection of FastAPI applications demonstrating modern web API development, including an e-commerce product management system and a machine learning-powered car price prediction API.

🚀 Projects Overview

1. FastAPI Ecommerce API (FastAPI/fastapi-ecommerce/)

A full-featured e-commerce product management API with CRUD operations, advanced validation, and business logic.

Key Features:

• Complete product CRUD operations
• Advanced filtering, sorting, and pagination
• Pydantic-based data validation with business rules
• JSON file-based persistence
• Comprehensive error handling
• Automatic API documentation

2. Car Price Prediction API (model/car-price-api/)

Machine learning API for predicting used car prices using Random Forest regression, with both REST API and Streamlit web interface.

Key Features:

• ML model serving via REST API
• Streamlit web application for user interaction
• One-hot encoding for categorical features
• CORS-enabled for web integration
• Pre-trained model with Cardekho dataset

📁 Project Structure

FastAPI project/
├── FastAPI/
│   └── fastapi-ecommerce/
│       ├── requirements.txt
│       └── app/
│           ├── main.py              # Main FastAPI application
│           ├── schema/
│           │   └── product.py       # Pydantic models
│           ├── service/
│           │   └── products.py      # Business logic
│           └── data/
│               └── products.json    # Sample product data
├── model/
│   └── car-price-api/
│       ├── main.py                  # FastAPI app
│       ├── schema.py                # Pydantic models
│       ├── model.py                 # ML prediction logic
│       ├── streamlit_app.py         # Web UI
│       ├── train.py                 # Model training
│       ├── requirements.txt
│       ├── random_forest_model.pkl  # Trained model
│       ├── feature_columns.pkl      # Feature metadata
│       └── cardekho_data (1).csv    # Training data
└── README.md

🛠️ Installation & Setup

Prerequisites

• Python 3.8+
• pip package manager

Ecommerce API Setup

cd FastAPI/fastapi-ecommerce

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

# Install dependencies
pip install fastapi uvicorn pydantic python-dotenv

# Run the application
uvicorn app.main:app --reload

Car Price Prediction API Setup

cd model/car-price-api

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

# Install dependencies
pip install -r requirements.txt

# Run the API
uvicorn main:app --reload

# Run the Streamlit app (in another terminal)
streamlit run streamlit_app.py

📖 API Documentation

Ecommerce API Endpoints

Products Management

• GET / - API root with health check
• GET /products - List products with filtering options
  • Query parameters: name, sort_by_price, order, limit, offset
• GET /products/{product_id} - Get specific product
• POST /products - Create new product
• PUT /products/{product_id} - Update product
• DELETE /products/{product_id} - Delete product

Example Requests

Get all products:

curl http://localhost:8000/products

Create a product:

curl -X POST "http://localhost:8000/products" \
  -H "Content-Type: application/json" \
  -d '{
    "sku": "TEST-001-001",
    "name": "Test Product",
    "description": "A test product",
    "category": "electronics",
    "brand": "TestBrand",
    "price": 100.0,
    "stock": 10,
    "is_active": true,
    "rating": 4.5,
    "image_urls": ["https://example.com/image.jpg"],
    "dimensions_cm": {"length": 10, "width": 5, "height": 2},
    "seller": {
      "id": "123e4567-e89b-12d3-a456-426614174000",
      "name": "Test Seller",
      "email": "test@teststore.in",
      "website": "https://teststore.in"
    }
  }'

Car Price Prediction API Endpoints

• GET / - Health check
• POST /predict - Predict car price

Example Request

curl -X POST "http://localhost:8000/predict" \
  -H "Content-Type: application/json" \
  -d '{
    "Car_Name": "swift",
    "Year": 2014,
    "Present_Price": 5.59,
    "Kms_Driven": 27000,
    "Fuel_Type": "Petrol",
    "Seller_Type": "Dealer",
    "Transmission": "Manual",
    "Owner": 0
  }'

🎯 Features & Validation

Ecommerce API Features

• Data Validation: SKU format, email domains, business rules
• Business Logic: Stock management, discount validation
• Computed Fields: Final price calculation, volume computation
• Error Handling: Comprehensive HTTP exceptions
• Filtering: Name search, price sorting, pagination

Car Price Prediction Features

• ML Model: Random Forest regression
• Preprocessing: Automatic one-hot encoding
• Feature Engineering: Categorical variable handling
• Web Interface: Streamlit-based user interface

🔧 Development

Running Tests

# For ecommerce API
cd FastAPI/fastapi-ecommerce
python -m pytest

# For car price API
cd model/car-price-api
python -m pytest

API Documentation Access

• Ecommerce API: http://localhost:8000/docs
• Car Price API: http://localhost:8000/docs

🤝 Contributing

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

📄 License

This project is released for research and educational use.

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Built with:

• FastAPI - Modern Python web framework
• Pydantic - Data validation
• scikit-learn - Machine learning
• Streamlit - Web app framework