Book API Testing Framework

Key Features

• Custom APIClient with built-in retry logic and comprehensive logging
• Reusable Validators for status codes, error messages, and response validation
• DRY Architecture using pytest fixtures and base classes
• Parallel Execution with pytest-xdist and worker-safe test data
• Rich Reporting with HTML and Allure integration
• Comprehensive Logging for all requests, responses, and assertions

• CI/CD Workflows: Automated Code Analysis and Test Execution via GitHub Actions

Quick Start

1. Install dependencies:
   pip install -r requirements.txt
2. Start your Book API server:
   http://localhost:3000
3. Run all tests:
   pytest
4. Run tests in parallel:
   pytest -n auto --dist loadfile
5. Run smoke tests quickly:
   pytest -m smoke -n auto --dist loadfile
6. Generate Allure report:
   allure serve test-results/allure-results
7. To generate a static Allure HTML report:
   allure generate test-results/allure-results --clean -o test-results/allure-report

Best Practices

• Parameterization: Use @pytest.mark.parametrize for edge cases
• Traceability: All requests and assertions are logged with detailed info
• Dependencies: Test ordering managed with pytest-dependency
• Retry Logic: Built-in handling for transient HTTP errors (429, 5xx)
• Parallel Safety: Unique test data per worker prevents collisions

Tech Stack

• Python 3.8+ - Modern Python features
• pytest - Advanced testing framework
• requests - HTTP library with session management
• urllib3 - Retry logic and connection pooling
• allure-pytest - Rich test reporting
• pytest-xdist - Parallel test execution

Pytest Markers

• smoke: Quick smoke tests for core functionality
• regression: Comprehensive regression tests for business logic
• negative: Error handling and negative scenario tests

Run specific test types:

pytest -m regression

Combine markers for flexible execution:

pytest -m "smoke or regression"
pytest -m "regression and not negative"

Parallel execution with markers:

pytest -m smoke -n auto --dist loadfile

Test Case Mapping & Result Collection

• Test Case Mapping: Each test function is mapped to a unique test case ID using test-plan-suite.json for traceability and reporting.
• Result Collection: Test results are collected for each test case, including outcome, duration (ms), and iteration details. Results are aggregated and written to test-results/test-results-report.json after each run, supporting both serial and parallel execution.

CI/CD & GitHub Actions

• Code Analysis: Automated linting and static analysis on every push and pull request.
• Test Execution: Runs all tests and generates reports for every push and pull request, including parallel execution and publishing Allure/HTML reports.