Multiply your Testing Effectiveness with Parameterized Testing, v1
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The document outlines the benefits of parameterized testing in automated workflows, emphasizing developer efficiency and code quality. It discusses integrating testing into development pipelines, ensuring tests cover new features while maintaining legacy functionality. Various strategies for implementing parameterization in tests using pytest are also provided to facilitate rapid development and maintainability.
![@pytest.mark.parametrize('a_card', [
Card('first task', 'brian', False),
Card(),
Card(summary='do something'),
Card(owner='brian'),
Card(done=True)],ids=repr)
def test_add(empty_db, a_card):
id = cards.add_card(a_card)
c2 = cards.get_card(id)
assert a_card == c2
function parametrization](https://image.slidesharecdn.com/pythonpdx26sept2019parametrization-190927200719/85/Multiply-your-Testing-Effectiveness-with-Parameterized-Testing-v1-20-320.jpg)
![@pytest.fixture(params=[
Card('first task', 'brian', False),
Card(),
Card(summary='do something'),
Card(owner='brian'),
Card(done=True)], ids=repr)
def a_card(request):
return request.param
def test_add(empty_db, a_card):
id = cards.add_card(a_card)
c2 = cards.get_card(id)
assert a_card == c2
fixture parametrization](https://image.slidesharecdn.com/pythonpdx26sept2019parametrization-190927200719/85/Multiply-your-Testing-Effectiveness-with-Parameterized-Testing-v1-21-320.jpg)
![def pytest_generate_tests(metafunc):
if "a_card" in metafunc.fixturenames:
metafunc.parametrize("a_card", [
Card('first task', 'brian', False),
Card(),
Card(summary='do something'),
Card(owner='brian'),
Card(done=True)], ids = repr)
def test_add(empty_db, a_card):
id = cards.add_card(a_card)
c2 = cards.get_card(id)
assert a_card == c2
pytest_generate_tests](https://image.slidesharecdn.com/pythonpdx26sept2019parametrization-190927200719/85/Multiply-your-Testing-Effectiveness-with-Parameterized-Testing-v1-22-320.jpg)
Multiply your Testing Effectiveness with Parameterized Testing, v1
- 1. Multiply your Testing Effectiveness with Parameterized Testing Brian Okken
- 2. The Immense Value of Automated Tests and How to Avoid Writing Them Alternate title Brian Okken
- 3. Brian Okken weekly Python podcasts A book I work here new meetup there, Python PDX West Oct 8, 6 pm Python-PDX-West
- 4. Outline • A development workflow • which includes a build pipeline • which includes tests • that I don’t want to spend too much time writing • so most of my test cases use parametrization* *one of many techniques I use to avoid writing tests
- 5. Target Workflow Time main dev / fix / feature branches Merge Request / Pipeline Runs Drawing elements: Vincent Driessen License: Creative Commons Merge Request / Pipeline Runs • Branch off main • Solo or collaborating • Tests and code merge together • Pipeline does magic
- 6. Developer Workflow • Write some code & some tests. • Commit code regularly • Merge Request / Pull Request • Pipeline does most of the work, build, test, etc. • Reviewers get notified. • Reviewers think my code is awesome & accept it. • Merge finishes • Fist bumps, high fives, etc. • Repeat
- 7. After merge, I know • I didn't break anything that used to work. • New features are tested with new tests. • Future changes won’t break current features. • Team understands code and tests. • The code is ready for users. • I can refactor my code if I'm not proud of it and know the tests will make sure everything is ok.
- 8. Reviewer knows, before the review ✓ Static analysis ✓ Style guide checks ✓ Code coverage has not dropped. ✓ Tests all pass ✓ Legacy functionality working. ✓ New tests pass.
- 9. Reviewer Focus • Just the code + test for this feature. • Do I understand the code and the tests? • Enough to maintain it if the original dev is on vacation? • Are the tests sufficient for the new functionality?
- 10. Team Lead / Manager View • Awesome code keeps popping out • The tests have our backs. • We’re moving fast. • Big refactoring/rewrites are low risk. • I can understand the tests. • Maybe even write some tests myself.
- 11. Tests in a Pipeline • fail fast • negative feedback as fast as possible • feeds into a deploy stage, maybe smoke tests longer running tests quick but thorough new tests static analysis 13
- 12. Tests to support this • Customer focused • Developer focused • Feature / functionality focused • Risk focused • Complete but not crazy complete • Have to be readable, fast to write, easy to maintain
- 13. Parametrization • Many test cases with one test function. • pytest has a few strategies for this. • function parametrization • fixture parametrization • a hook function: pytest_generate_tests() 17
- 14. cards $ cards ID owner done summary ---- ------- ------ ———— $ cards add prepare for talk $ cards add give talk $ cards ID owner done summary ---- ------- ------ ---------------- 1 prepare for talk 2 give talk $ cards update -o okken 1 $ cards update -o okken 2 $ cards finish 1 $ cards ID owner done summary ---- ------- ------ ---------------- 1 okken x prepare for talk 2 okken give talk
- 15. a test import cards from cards import Card def test_add(tmp_path): cards.set_db_path(tmp_path) cards.connect() a_card = Card('first task', 'brian', False) id = cards.add_card(a_card) c2 = cards.get_card(id) cards.disconnect() assert a_card == c2
- 16. push setup/teardown into fixtures @pytest.fixture(scope='session') def db(tmp_path_factory): d = tmp_path_factory.mktemp('cards_db') cards.set_db_path(d) cards.connect() yield cards.disconnect() @pytest.fixture(scope='function') def empty_db(db): cards.delete_all() def test_add(empty_db): a_card = Card('first task', 'brian') id = cards.add_card(a_card) c2 = cards.get_card(id) assert a_card == c2
- 17. so we can focus on this test def test_add(empty_db): a_card = Card('first task', 'brian', False) id = cards.add_card(a_card) c2 = cards.get_card(id) assert a_card == c2
- 18. so we can focus on this test def test_add(empty_db): a_card = Card('first task', 'brian', False) id = cards.add_card(a_card) c2 = cards.get_card(id) assert a_card == c2 @dataclass class Card: summary: str = None owner: str = None done: bool = None id: int = field(default=None, compare=False) But what about all the other kinds of cards?
- 20. @pytest.mark.parametrize('a_card', [ Card('first task', 'brian', False), Card(), Card(summary='do something'), Card(owner='brian'), Card(done=True)],ids=repr) def test_add(empty_db, a_card): id = cards.add_card(a_card) c2 = cards.get_card(id) assert a_card == c2 function parametrization
- 21. @pytest.fixture(params=[ Card('first task', 'brian', False), Card(), Card(summary='do something'), Card(owner='brian'), Card(done=True)], ids=repr) def a_card(request): return request.param def test_add(empty_db, a_card): id = cards.add_card(a_card) c2 = cards.get_card(id) assert a_card == c2 fixture parametrization
- 22. def pytest_generate_tests(metafunc): if "a_card" in metafunc.fixturenames: metafunc.parametrize("a_card", [ Card('first task', 'brian', False), Card(), Card(summary='do something'), Card(owner='brian'), Card(done=True)], ids = repr) def test_add(empty_db, a_card): id = cards.add_card(a_card) c2 = cards.get_card(id) assert a_card == c2 pytest_generate_tests
- 24. Thank You • twitter: @brianokken • book: Python Testing with pytest • pragprog.com/book/bopytest/python-testing-with-pytest • also: pytestbook.com • podcasts • testandcode.com • pythonbytes.fm • https://www.me • meetup • meetup.com/Python-PDX-West/ • First one: Tuesday, Oct 8, Hillsboro