Advanced API Testing Framework

Professional API testing framework using Python, Pytest, and JSONPlaceholder API. Demonstrates advanced testing concepts including layered validation, schema validation, and performance testing.

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Technology Stack

• Python 3.11+
• Pytest - Testing framework
• Requests - HTTP client library
• JSONSchema - Schema validation
• Pytest-HTML - Test reporting

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Features

• Centralized API client with session management
• Reusable validation utilities
• JSON schema validation
• Response time assertions
• Layered validation approach (status → structure → content)
• Comprehensive test data management
• HTML test reporting
• Clear separation of concerns (utils, tests, data)
• CI/CD pipeline with GitHub Actions

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Test Coverage

Users CRUD Operations:

• GET all users with pagination validation
• GET single user by ID with schema validation
• POST create new user
• PUT update existing user
• DELETE user
• Negative test: 404 for non-existent user

Posts Operations:

• GET all posts
• GET posts filtered by user ID
• GET single post with schema validation
• GET post comments (nested resources)
• POST create new post
• Negative test: 404 for invalid post ID

Total: 12 automated tests

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Project Structure

QA_API_Advanced/
├── data/
│   └── test_data.py           # Test data and JSON schemas
├── reports/
│   └── test_report.html       # Generated HTML test report
├── screenshots/
│   ├── test_report_summary.png
│   └── test_report_details.png
├── tests/
│   ├── test_users_crud.py     # User endpoint tests
│   └── test_posts.py          # Post endpoint tests
├── utils/
│   ├── api_client.py          # HTTP client wrapper
│   ├── api_endpoints.py       # Endpoint configuration
│   └── validators.py          # Response validation utilities
├── conftest.py                # Pytest fixtures
├── requirements.txt           # Python dependencies
└── README.md

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Setup Instructions

Prerequisites:

• Python 3.11 or higher
• pip (Python package manager)
• Git

Installation:

1. Clone the repository:

git clone https://github.com/arturdmt-alt/QA_API_Advanced.git
cd QA_API_Advanced

2. Create and activate virtual environment:

python -m venv venv
venv\Scripts\activate  # Windows
source venv/bin/activate  # macOS/Linux

3. Install dependencies:

pip install -r requirements.txt

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Running Tests

Run all tests:

pytest tests/ -v

Run specific test file:

pytest tests/test_users_crud.py -v

Generate HTML report:

pytest tests/ --html=reports/test_report.html --self-contained-html

Run with verbose output:

pytest tests/ -v -s

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Test Results

All tests passing with response times under 3 seconds.

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Technical Approach

Layered Validation Strategy

Tests follow a defensive validation pattern:

1. Status Code - Verify HTTP status before processing response
2. Response Time - Ensure API meets performance requirements
3. Content Type - Validate response format (JSON)
4. Structure - Verify expected fields exist
5. Data Types - Validate field types (int, str, list)
6. Content - Verify actual values

This approach provides clear error messages and catches issues early.

API Client Pattern

Centralized HTTP client provides:

• Consistent headers across all requests
• Session reuse for performance
• Timeout handling to prevent hanging tests
• Context manager support for proper cleanup

Schema Validation

JSON Schema validation ensures:

• API contract compliance
• Early detection of breaking changes
• Documentation of expected response structure

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Challenges and Solutions

Challenge 1: Response Time Variability

Problem: Initial tests failed due to network latency causing response times to exceed 2000ms limit.

Solution: Adjusted timeout threshold to 3000ms for public API testing. In production environment with internal APIs, lower thresholds (500-1000ms) would be more appropriate.

Challenge 2: Mock API Limitations

Problem: JSONPlaceholder is a fake API that doesn't persist data, limiting certain test scenarios.

Solution: Documented limitation and focused on testing API contract and response validation rather than data persistence. For real-world projects, would use test database with proper cleanup.

Challenge 3: Test Data Management

Problem: Hardcoded test data scattered across test files made maintenance difficult.

Solution: Centralized all test data in data/test_data.py including valid data, invalid data, edge cases, and JSON schemas. Single source of truth for test data.

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API Used

This project uses JSONPlaceholder - a free fake REST API for testing and prototyping.

Endpoints tested:

• /users - User management
• /posts - Blog posts
• /comments - Post comments

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Author

Artur Dmytriyev
QA Automation Engineer

• GitHub: github.com/arturdmt-alt
• LinkedIn: linkedin.com/in/arturdmytriyev