Further Learning¶
This page gives you a clear path to keep learning after this guide.
Official Sources¶
Start with official documentation first:
- Python Documentation
- pytest Documentation
- Playwright Python Documentation
- Pydantic Documentation
- Ruff Documentation
- uv Documentation
Learning Path (12 Weeks)¶
Weeks 1-2: Python Core¶
- Re-read fundamentals: data types, loops, functions, modules
- Solve small algorithm tasks every day
- Write code with type hints from the start
Weeks 3-4: OOP and Error Handling¶
- Build small classes (API client, logger wrapper, config loader)
- Practice custom exceptions
- Add logs with
DEBUG,INFO,WARNING,ERROR
Weeks 5-6: pytest Deep Practice¶
- Write unit tests for every new function
- Use fixtures and
parametrize - Learn mocking with
pytest-mock - Keep coverage at 100%
Weeks 7-8: API Automation¶
- Build reusable API client classes
- Add response schema validation with Pydantic
- Test positive and negative scenarios
Weeks 9-10: UI Automation¶
- Build Page Object Model with Playwright
- Use stable selectors (
data-testid) - Practice wait strategies to avoid flaky tests
Weeks 11-12: Quality and CI/CD¶
- Configure Ruff and mypy in strict mode
- Add pre-commit hooks
- Build CI pipeline with all checks
- Publish test and coverage reports
Practice Checklist¶
Use this checklist every week:
- I solved at least 10 Python exercises
- I wrote tests for all new code
- I ran lint + type checks locally
- I reviewed one flaky test and improved it
- I read one official doc chapter
- I updated one example in my knowledge base
What to Build Next¶
Build mini-projects to grow faster:
- API Test Framework (pytest + requests + pydantic)
- UI Test Framework (pytest + Playwright + POM)
- Shared Utility Package (logging, config, retry, assertions)
- CI/CD Template Project with quality gates
Interview Growth Plan¶
Every week:
- Practice 3 Python coding tasks
- Explain one design decision out loud (why this pattern, why this tool)
- Review one failure from your real tests and explain root cause
- Prepare one STAR story about automation impact
Keep Your Knowledge Base Fresh¶
Update this guide monthly:
- Add one new practical example per section
- Remove outdated tools or syntax
- Record mistakes from real projects and how you fixed them
- Add new interview questions you faced
Final Advice¶
Consistency is more important than speed.
If you learn and practice a little every day, your Python automation skills will grow steadily and stay strong.