Playwright or NumPy First? What Beginners Should Pick

Playwright — Learning Path:
Week 1: Setup, selectors, first test
Week 2: Assertions, fixtures, hooks
Week 3: Page objects, API testing
Week 4: CI with GitHub Actions

Daily focus:
• 1 hour theory + docs
• 2 hours writing and debugging tests
• 30 min reading Playwright patterns
• 30 min reviewing your code

Week 1 Review:
□ Can I install Playwright?
□ Can I write reliable selectors?
□ Can I run my first test?

Week 2 Review:
□ Do I understand assertions?
□ Can I use fixtures?
□ Can I use hooks (beforeEach)?

Week 3 Review:
□ Can I implement Page Object Model?
□ Can I test APIs?
□ Can I mock network requests?

Week 4 Review:
□ Can I run tests in GitHub Actions?
□ Do I generate readable reports?
□ Are tests documented?

NumPy — Learning Path:
Week 1: ndarray basics, indexing, dtypes
Week 2: vectorization, broadcasting, aggregations
Week 3: reshaping, slicing, boolean masks
Week 4: real dataset project

Daily focus:
• 1 hour theory + docs
• 2 hours coding in notebooks
• 30 min reading NumPy patterns
• 30 min reviewing your code

Week 1 Review:
□ Can I create arrays with different shapes and dtypes?
□ Do I understand indexing and slicing?
□ Can I reshape and transpose?

Week 2 Review:
□ Can I replace a loop with NumPy vectorization?
□ Do I understand broadcasting?
□ Can I aggregate (sum, mean, std) without loops?

Week 3 Review:
□ Can I use boolean masks?
□ Do I understand axis-based operations?
□ Can I reshape and stack arrays?

Week 4 Review:
□ Have I analyzed a real CSV dataset?
□ Is my code documented?
□ Have I shared it on GitHub?

Playwright vs NumPy — Side by Side:
Playwright:
  Purpose: Test web apps
  Output: Test suites
  Role: QA Automation Engineer
  Tool: Code editor + browser

NumPy:
  Purpose: Numerical computing
  Output: Arrays and analysis
  Role: Data Analyst / ML Engineer
  Tool: Python + Jupyter notebook

Decision Guide — Playwright vs NumPy:
Want to test web apps? → Playwright
Want to work in data/ML? → NumPy
Want to automate anything? → Playwright
Want to build models? → NumPy
Already know JavaScript? → Playwright
Already know Python + math? → NumPy
Not sure yet? → NumPy first (foundational for data)

Action Plan — Which First?
Step 1 — Clarify your goal: test or data?
Step 2 — If testing: learn JavaScript, then Playwright.
Step 3 — If data: learn Python, then NumPy.
Step 4 — If both: NumPy first, then Playwright.
Step 5 — Build a project: test suite or data analysis.
Step 6 — Document and share on GitHub.
Step 7 — Apply for roles that match your path.

Portfolio Review — What Hiring Managers Want:
☐ A real project (test suite or data analysis)
☐ Clean, well-documented code
☐ Test reports or analysis notebook
☐ README with problem, approach, results
☐ CI pipeline (Playwright) or notebook (NumPy)
☐ Git history showing iterative work
☐ A short writeup or blog post