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Advanced API Testing Framework

API Tests

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

Technology Stack

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

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

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

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

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
  1. Create and activate virtual environment:
python -m venv venv
venv\Scripts\activate  # Windows
source venv/bin/activate  # macOS/Linux
  1. Install dependencies:
pip install -r requirements.txt

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

Test Results

Test Report Summary

Test Report Details

All tests passing with response times under 3 seconds.

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

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.

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

Author

Artur Dmytriyev
QA Automation Engineer