Building Scalable Test Automation Frameworks with GenAI

Create a first draft of a web and api test automation framework using a page object model, guided by ChatGPT, with two tests across five pages and api categories.

Create a structured test automation framework skeleton by organizing config, data, pages, and apis folders, with a base page and page objects for home, contact, and product pages.

Build a Python-based test framework by reading config.yaml with a config reader in utils, enabling environment QA and base URL management for pytest-driven API tests.

Centralize configuration with config.yaml and context.py, integrate Context Viewer, implement fixtures and an api client fixture returning a session, and build a browser context with Playwright pages to streamline pytest.

Run web test cases with a page object model and pytest, using ChatGPT-assisted locators, monitor an 80% pass rate, and prepare API tests for later.

Learn to run web tests in headless mode for CI pipelines, toggle headless with a command line argument, and enable parallel execution using pytest config.

Enable framework to run tests on pull request by configuring a GitHub actions yaml workflow, creating .github/workflow directory, installing playwright browsers, and running web and api tests in headless ci.

Create a git workflow to prepare a repository, generate a .gitignore with ChatGPT, stage and commit changes, set the main branch, add origin, push, and troubleshoot a 403 error.

Create a feature branch, commit changes to the YAML workflow, push and open a pull request into main. Then troubleshoot GitHub actions and Python/Ubuntu compatibility issues during CI checks.

Execute test cases in GitHub Actions for a GenAI powered test automation framework, installing dependencies and chromium, running API, web, and headless UI tests via pull requests.

generate pytest html reports for api and web tests and upload them as artifacts in github actions. ensure reports are produced even if tests fail and are accessible for stakeholders.