ZEKA REST Microservice

A production-ready REST microservice for managing customers and orders with MongoDB integration, built with Python and FastAPI principles. Features comprehensive API endpoints, Docker containerization, and CI/CD workflows.

🎯 Overview

ZEKA REST Microservice is a scalable backend solution designed to handle customer and order management operations. It demonstrates best practices in microservice architecture, including:

• RESTful API Design: Standard HTTP methods for CRUD operations
• Database Integration: MongoDB with connection pooling
• Containerization: Docker and Docker Compose support
• Testing: Comprehensive test suite with pytest
• CI/CD Pipeline: GitHub Actions workflow for automated testing
• Environment Management: Environment variable configuration

⚙️ Tech Stack

Component	Technology	Version
Runtime	Python	3.8+
Database	MongoDB	4.0+
Web Framework	Flask/FastAPI-like	-
Containerization	Docker	Latest
Testing	Pytest	Latest
CI/CD	GitHub Actions	-

📋 Features

✅ Customer Management

• Create new customers (name, email)
• Retrieve all customers
• Customer validation and error handling

✅ Order Management

• Create orders for customers
• Track items and amounts
• Link orders to customers
• Order history tracking

✅ Infrastructure

• Docker containerization for easy deployment
• Docker Compose for local development
• Environment configuration via .env files
• Automated CI/CD workflows

✅ Testing & Quality

• Unit tests with pytest
• Test isolation and fixtures
• Continuous Integration pipeline

🚀 Quick Start

Prerequisites

• Python 3.8+
• MongoDB (local or Atlas)
• pip (Python package manager)
• Docker (optional, for containerization)

Local Development Setup

1. Clone the Repository

git clone https://github.com/Vinay0905/REST_microservice.git
cd REST_microservice

2. Create Environment Configuration

Create a .env file in the project root:

MONGODB_URI="mongodb+srv://<user>:<pass>@zeka.7ijqrc1.mongodb.net/?retryWrites=true&w=majority"
MONGODB_DB="ZEKA"
PYTHON_ENV="development"
PORT=8000

3. Set Up Virtual Environment

# Create virtual environment
python -m venv venv

# Activate virtual environment
# On Windows:
venv\Scripts\activate
# On macOS/Linux:
source venv/bin/activate

# Install dependencies
pip install -r requirements.txt

4. Run the Application

python run.py

The server will start at http://localhost:8000

Docker Setup

Using Docker Compose (Recommended)

# Build and start services
docker-compose up -d

# View logs
docker-compose logs -f app

# Stop services
docker-compose down

Using Docker Directly

# Build image
docker build -t zeka-rest-api .

# Run container
docker run -p 8000:8000 --env-file .env zeka-rest-api

📚 API Documentation

Base URL

http://localhost:8000/api

Endpoints

Customers

Create Customer

POST /api/customers
Content-Type: application/json

{
  "name": "John Doe",
  "email": "john@example.com"
}

Response (201 Created)

{
  "_id": "507f1f77bcf86cd799439011",
  "name": "John Doe",
  "email": "john@example.com",
  "created_at": "2024-01-15T10:30:00Z"
}

Get All Customers

GET /api/customers

Response (200 OK)

[
  {
    "_id": "507f1f77bcf86cd799439011",
    "name": "John Doe",
    "email": "john@example.com",
    "created_at": "2024-01-15T10:30:00Z"
  }
]

Orders

Create Order

POST /api/orders
Content-Type: application/json

{
  "customer_id": "507f1f77bcf86cd799439011",
  "item": "Laptop",
  "amount": 999.99
}

Response (201 Created)

{
  "_id": "507f1f77bcf86cd799439012",
  "customer_id": "507f1f77bcf86cd799439011",
  "item": "Laptop",
  "amount": 999.99,
  "created_at": "2024-01-15T11:00:00Z"
}

🧪 Testing

Run the test suite:

# Run all tests
pytest

# Run with verbose output
pytest -v

# Run specific test file
pytest tests/test_customers.py

# Run with coverage report
pytest --cov=app

Test files are located in the tests/ directory.

📁 Project Structure

REST_microservice/
├── app/                          # Application code
│   ├── __init__.py
│   ├── models.py                # Data models
│   ├── routes.py                # API endpoints
│   └── database.py              # Database configuration
├── tests/                       # Test suite
│   ├── test_customers.py
│   ├── test_orders.py
│   └── conftest.py             # Pytest fixtures
├── .github/
│   └── workflows/               # CI/CD workflows
│       └── tests.yml           # Automated testing pipeline
├── .env.example                 # Environment template
├── .dockerignore                # Docker ignore rules
├── .gitignore                   # Git ignore rules
├── Dockerfile                   # Docker image definition
├── docker-compose.yml           # Docker Compose configuration
├── requirements.txt             # Python dependencies
├── pytest.ini                   # Pytest configuration
├── run.py                       # Application entry point
└── README.md                    # This file

🔧 Configuration

Environment Variables

Variable	Description	Required
MONGODB_URI	MongoDB connection string	Yes
MONGODB_DB	Database name	Yes
PYTHON_ENV	Environment (development/production)	No
PORT	Server port	No (default: 8000)
LOG_LEVEL	Logging level	No (default: INFO)

MongoDB Atlas Setup

1. Create a MongoDB Atlas account at mongodb.com/atlas
2. Create a cluster
3. Get connection string: mongodb+srv://<username>:<password>@<cluster>.mongodb.net/?retryWrites=true&w=majority
4. Add to .env file

🔄 CI/CD Pipeline

The project includes GitHub Actions workflows for:

• Automated Testing: Runs on every push and pull request
• Code Quality: Checks for code standards
• Docker Build: Builds and pushes Docker images (on release)

Workflow file: .github/workflows/tests.yml

📦 Dependencies

Key dependencies in requirements.txt:

Flask/FastAPI-like framework
PyMongo - MongoDB driver
pytest - Testing framework
python-dotenv - Environment configuration
requests - HTTP client

View full list: pip freeze

🐛 Troubleshooting

MongoDB Connection Error

Problem: MongoAuthenticationError

Solution:

• Verify MongoDB URI in .env file
• Check MongoDB credentials
• Ensure IP is whitelisted in MongoDB Atlas
• Verify network connectivity

Port Already in Use

Problem: Address already in use on port 8000

Solution:

# Kill process using port 8000
# On macOS/Linux:
lsof -ti:8000 | xargs kill -9

# On Windows (PowerShell):
netstat -ano | findstr :8000
taskkill /PID <PID> /F

Virtual Environment Issues

Problem: No module named 'app'

Solution:

# Ensure venv is activated
source venv/bin/activate  # macOS/Linux
venv\Scripts\activate     # Windows

# Reinstall requirements
pip install -r requirements.txt

🤝 Contributing

Contributions are welcome! Please follow these steps:

1. Fork the repository
2. Create a feature branch: git checkout -b feature/your-feature
3. Commit changes: git commit -am 'Add new feature'
4. Push to branch: git push origin feature/your-feature
5. Submit a pull request

Contribution Guidelines

• Follow PEP 8 Python style guide
• Write tests for new features
• Update documentation
• Keep commits clear and descriptive

📝 License

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

👨‍💻 Author

Vinay0905

• GitHub: @Vinay0905
• Focus: Backend Development, Microservices, Python

🙏 Acknowledgments

• MongoDB documentation and community
• Python community best practices
• GitHub Actions for CI/CD
• Contributors and testers

📞 Support

For issues or questions:

1. Check existing GitHub Issues
2. Create a new issue with detailed information
3. Include steps to reproduce for bugs
4. Provide environment details

📈 Roadmap

Version 1.1

• Add authentication (JWT)
• Implement pagination
• Add logging
• Request validation schemas

Version 1.2

• GraphQL endpoint
• Redis caching
• Advanced filtering
• API rate limiting

Version 2.0

• Kubernetes deployment
• Message queue integration
• Analytics dashboard
• Payment processing

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Happy coding! 🚀