Employee Eligibility Service for External API

A professional Python service template designed to interact with an external API for employee financial data and eligibility calculations. This service follows best practices in software architecture, including versioned namespaces, modular components, and extensible design.

Table of Contents

• Overview
• Architecture
• Project Structure
• Installation
• Configuration
• Usage
• API Reference
• Extending the Service
• Testing
• Deployment
• Contributing
• License

Overview

This service provides a clean, maintainable interface for checking employee eligibility based on financial data retrieved from an external API. Key features include:

• Versioned Architecture: Supports multiple API versions (currently v1 implemented, v2 ready)
• Modular Design: Separated concerns with client, parser, rules, and service layers
• Pluggable Authentication: Ready for API keys, JWT, or OAuth
• Robust Error Handling: Comprehensive error handling with retries and logging
• Mock Data: Includes mock API responses for development and testing
• Type Hints & Documentation: Fully typed with detailed docstrings

The service is currently set up with placeholder implementations and mock data, making it ready for integration with the real API when available.

Architecture

The service follows a layered architecture pattern:

┌─────────────────┐
│   main.py       │  ← Entry point with examples
└─────────────────┘
         │
    ┌────────────┐
    │  Service   │  ← Facade orchestrating components
    └────────────┘
         │
    ┌────┼────┼────┐
    │    │    │    │
┌─────┐ ┌─────┐ ┌─────┐
│Client│ │Parser│ │Rules│  ← Core components
└─────┘ └─────┘ └─────┘
         │
    ┌────────────┐
    │   Utils    │  ← Shared utilities (config, logging, exceptions)
    └────────────┘

Component Responsibilities

• Client: Handles HTTP communication, authentication, retries, and error handling
• Parser: Validates and parses JSON responses into Python data structures
• Rules: Contains business logic for eligibility calculations
• Service: Orchestrates the flow between components, providing a clean API
• Utils: Shared utilities for configuration, logging, and custom exceptions

Project Structure

service-for-API/
├── main.py                    # Example usage script
├── services/
│   ├── v1/                    # API Version 1 implementation
│   │   ├── client.py          # HTTP client with mocks
│   │   ├── parser.py          # JSON parser and validation
│   │   ├── rules.py           # Business rules for eligibility
│   │   └── service.py         # Service facade
│   └── v2/                    # API Version 2 (placeholder)
│       ├── client.py
│       ├── parser.py
│       ├── rules.py
│       └── service.py
├── utils/
│   ├── config.py              # Configuration settings
│   ├── logger.py              # Centralized logging
│   └── exceptions.py          # Custom exceptions
├── TODO.md                    # Development tasks
└── README.md                  # This file

Installation

1. Clone the repository:

   git clone <repository-url>
   cd service-for-API

2. Create a virtual environment (recommended):

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

3. Install dependencies:

   pip install requests

   Note: Only requests is required for the current implementation. Additional dependencies may be needed for authentication or other features.

Configuration

Configuration is managed through utils/config.py. Key settings include:

Environment Variables

Set these in your environment or .env file:

# API Configuration
API_BASE_URL=https://api.example.com
API_VERSION=v1

# Request Settings
REQUEST_TIMEOUT=30
RETRY_ATTEMPTS=3
RETRY_BACKOFF_FACTOR=0.3

# Logging
LOG_LEVEL=INFO

# Authentication (when real API is available)
AUTH_TYPE=api_key  # Options: api_key, jwt, oauth, None
API_KEY=your_api_key_here
JWT_TOKEN=your_jwt_token_here
OAUTH_CLIENT_ID=your_client_id
OAUTH_CLIENT_SECRET=your_client_secret

Authentication Setup

The service supports multiple authentication methods:

• API Key: Set AUTH_TYPE=api_key and provide API_KEY
• JWT: Set AUTH_TYPE=jwt and provide JWT_TOKEN
• OAuth: Set AUTH_TYPE=oauth and provide client credentials (not yet implemented)

Usage

Basic Example

from services.v1.service import EmployeeService

# Initialize service
service = EmployeeService()

try:
    # Check employee eligibility
    eligible, reasons = service.check_employee_eligibility("123")

    if eligible:
        print("Employee is eligible")
    else:
        print(f"Not eligible: {', '.join(reasons)}")

    # Get financial summary
    summary = service.get_employee_financial_summary("123")
    print(f"Total loans: {summary['total_loans']}")

finally:
    service.close()

Running the Demo

Execute the main script to see examples with mock data:

python main.py

This will demonstrate eligibility checks for sample employees and show how the service handles various scenarios.

API Reference

EmployeeService

The main service class providing high-level operations.

Methods

• check_employee_eligibility(employee_id: str) -> Tuple[bool, List[str]]

  • Checks if an employee is eligible based on financial data
  • Returns: (eligible: bool, reasons: List[str])

• get_employee_financial_summary(employee_id: str) -> Dict[str, Any]

  • Retrieves a summary of employee financial data
  • Returns: Dictionary with loan counts, balances, etc.

Data Structures

• EmployeeFinancialData: Parsed financial data containing loans and deductions
• EligibilityResult: Result of eligibility check with boolean and reasons

Extending the Service

Adding New API Versions

1. Create a new directory under services/ (e.g., v3/)
2. Implement the four core files: client.py, parser.py, rules.py, service.py
3. Update config.py to support the new version
4. Modify import statements in calling code

Replacing Mock Data with Real API

1. Update Client (services/v1/client.py):

   • Remove _mock_response() method
   • Replace mock calls with actual requests.get() calls
   • Implement real authentication logic

2. Update Configuration:

   • Set API_BASE_URL to the real endpoint
   • Configure authentication credentials

3. Update Business Rules (services/v1/rules.py):

   • Replace placeholder thresholds with real business requirements
   • Add or modify eligibility criteria

4. Update Parser (services/v1/parser.py):

   • Adjust validation to match real API response format
   • Handle any new fields or data structures

Adding New Features

• Caching: Add caching layer in the service facade
• Metrics: Integrate monitoring/metrics collection
• Async Support: Convert to async/await for better performance
• Database Integration: Add local storage for frequently accessed data

Testing

Running Tests

Currently, the service includes mock data for testing. Run the main script to verify functionality:

python main.py

Test Scenarios

The mock data includes three sample employees with different financial profiles:

• Employee 1: Moderate loans and deductions (likely eligible)
• Employee 2: Single student loan (likely eligible)
• Employee 3: Multiple high-interest loans (likely ineligible)

Adding Unit Tests

Consider adding tests for:

• Client request handling and error scenarios
• Parser validation and data transformation
• Business rule calculations
• Service orchestration

Example test structure:

tests/
├── test_client.py
├── test_parser.py
├── test_rules.py
└── test_service.py

Deployment

Docker Deployment

Create a Dockerfile:

FROM python:3.9-slim

WORKDIR /app
COPY requirements.txt .
RUN pip install -r requirements.txt

COPY . .
CMD ["python", "main.py"]

Production Considerations

• Environment Variables: Use proper secret management for API keys
• Logging: Configure structured logging for production monitoring
• Monitoring: Add health checks and metrics endpoints
• Scaling: Consider async processing for high-volume scenarios
• Security: Implement rate limiting and input validation

Contributing

1. Fork the repository
2. Create a feature branch: git checkout -b feature/your-feature
3. Make your changes with proper tests
4. Update documentation as needed
5. Submit a pull request

Code Standards

• Use type hints throughout
• Include docstrings for all public methods
• Follow PEP 8 style guidelines
• Add inline comments for complex logic

License

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

---

Quick Start Checklist

• Review and update configuration in utils/config.py
• Install dependencies: pip install requests
• Run demo: python main.py
• Review mock data and business rules
• Replace mocks with real API calls when ready
• Update business rules with actual requirements
• Add proper authentication
• Implement comprehensive testing
• Set up monitoring and logging for production

For questions or support, please refer to the inline documentation in each module or create an issue in the repository.