🏗️ Project Structure

adaptive-api-framework/
│
├── core/
│   ├── api_client.py        # Centralized HTTP client
│   ├── auth_handler.py      # Authentication & headers handling
│   ├── config.py            # Application configuration
│   └── path_resolver.py     # Reliable path resolution
│
├── auth/
│   ├── generatic_auth.py    # Generic Auth Handler with abstract method
│   └── github_pat_handler.py # Specified Auth (Github PAT token)
│
├── tests/
│   ├── conftest.py          # Pytest fixtures & setup
│   └── test_*.py            # API test cases
│
├── utils/
│   └── logger.py            # Logging utility
│
├── .config/
│   └── .env                 # Environment variables (not committed)
│
├── requirements.txt
└── README.md

🔌 API Client Layer

The framework uses a single API client abstraction responsible for:

• Executing HTTP requests
• Managing base URLs
• Injecting headers and authentication
• Handling timeouts and request configuration

Benefits:

• No duplicated request logic
• Easier debugging
• Clean extension points for retries, hooks, and tracing

🔐 Authentication Strategy

• Token-based authentication (e.g., GitHub Personal Access Token)
• Credentials sourced strictly from environment variables
• Authentication logic fully decoupled from tests

Designed for future support of:

• OAuth-based authentication
• Multiple authentication strategies per environment

⚙️ Configuration Management

• Environment variables loaded using python-dotenv
• Centralized configuration access via AppConfig
• Supports multiple environments (test, staging, production)

Example .env

BASE_URL=https://api.github.com
TIMEOUT=10
PAT_KEY=your_github_token_here

🧪 Test Execution (Pytest)

• Pytest is used as the test runner

• Fixtures manage shared dependencies (API client, auth context)

• Tests focus on:

  • Status code validation
  • Response structure checks
  • Core content verification

Run tests

pytest -v

🧠 Validation Strategy

Planned validation layers include:

• Status code assertions
• Response schema validation
• Business rule validations
• Negative and edge-case testing
• Rate-limit and error handling scenarios

🧩 Logging & Observability

The framework is structured to support:

• Structured request/response logging
• Debug-level tracing
• Failure diagnostics
• Optional integration with reporting tools

Logging is currently minimal by design and will evolve in later phases.

🚀 Execution & Scalability Roadmap

Planned enhancements include:

• Parallel test execution
• Environment-based test selection
• Retry mechanisms
• Tag-based execution
• CI/CD pipeline integration
• Test reporting and metrics

🛣️ Development Roadmap (High Level)

• Phase 1: Core foundation & API client abstraction ✅
• Phase 2: Validation layers & test organization ✅
• Phase 3: Reliability (logging, reporting) ✅
• Phase 4: CI/CD & scalability
• Phase 5: Advanced features (contract testing, observability)

🚧 Project Status

• Development: Active
• Documentation: Stable (long-term)

📄 Disclaimer

This project is built for architectural learning and professional growth. It evolves incrementally to mirror real-world automation framework development, rather than presenting a prematurely “complete” solution.

🙌 Author

Prasad Helaskar Automation Tester | Python | API & UI Automation

A modular and professional API testing suite built with Python, Pytest, and Requests. Validates CRUD operations, authentication, and filtering for teacher management systems with detailed HTML reporting and dynamic data generation.