Hybrid Test Automation Framework (Conduit & Petstore)

📌 Project Overview

This project is a high-performance Hybrid Test Automation Framework designed to test two distinct service ecosystems:

1. Conduit (Blogging Platform): A social media platform. The framework uses a hybrid (UI + API) approach to ensure speed and reliability.
2. Petstore (Inventory Service): A REST API service for warehouse management, focused on contract validation and negative scenarios.

🚀 Key Engineering Solutions

• Hybrid Testing Approach: API is used for rapid data seeding and authentication via JWT token injection into localStorage. This reduces UI test execution time by 3-4x by bypassing the login UI.
• Page Object Model (POM): A clean architectural separation between page-specific logic and test scenarios.
• Advanced Data-Driven Testing: Extensive use of pytest.mark.parametrize combined with dynamic data generation via the Faker library.
• Modular API Client: A custom wrapper over requests with modular architecture (Users, Articles) and session management.
• Security & RBAC Validation: Automated scenarios for Role-Based Access Control (e.g., verifying that users cannot edit someone else's content).
• Stability Fixes: Implementation of "hard" field clearing (Control+A/Backspace) and smart waits to handle SPA (Angular) race conditions.

🛠 Tech Stack

• Python 3.12
• Playwright (UI Automation)
• Pytest (Test Runner)
• Requests (API Testing)
• Pydantic (Data Modeling & Validation)
• Allure (Reporting)

📊 Reporting & Visibility

The framework integrates with Allure Report to provide deep visibility into test results.

Overview Dashboard

The dashboard provides a high-level summary of test execution, showing a 98%+ pass rate across 600+ test runs (including stability stress-tests).

Behavior-Driven Structure

Tests are structured by Features and Stories to align technical results with business requirements. This view demonstrates the hybrid coverage and security validation scenarios.

⚙️ How to Run

1. Install dependencies:

   pip install -r requirements.txt

2. Install Playwright browsers:

   playwright install

3. Create a .env file based on .env.example

4. Run tests:

   pytest

5. Generate Allure report:

   allure serve allure-results