Why markers categorize and control tests in PyTest - Automation Benefits in Action

Use pytest markers to categorize and selectively run tests

Preconditions (2)

Step 1: Create three test functions: test_login, test_logout, test_profile

Step 2: Add a marker 'smoke' to test_login and test_logout

Step 3: Add a marker 'regression' to test_profile

Step 4: Run pytest with the option to only run tests marked 'smoke'

Step 5: Observe that only test_login and test_logout run

Step 6: Run pytest with the option to skip tests marked 'smoke'

Step 7: Observe that only test_profile runs

✅ Expected Result: Tests run according to the markers specified in the pytest command line options

Automation Requirements - pytest

Assertions Needed:

Verify that tests with 'smoke' marker run when selected

Verify that tests with 'smoke' marker are skipped when excluded

Best Practices:

Use @pytest.mark.<name> to mark tests

Use pytest command line options -m to select or exclude markers

Keep markers descriptive and consistent

Automated Solution

PyTest

import pytest

@pytest.mark.smoke
 def test_login():
     assert True

@pytest.mark.smoke
 def test_logout():
     assert True

@pytest.mark.regression
 def test_profile():
     assert True

# To run smoke tests only, use command:
# pytest -m smoke

# To skip smoke tests, use command:
# pytest -m "not smoke"

This script defines three test functions. Two are marked with @pytest.mark.smoke and one with @pytest.mark.regression. Markers help group tests.

Using pytest -m smoke runs only tests marked 'smoke'. Using pytest -m "not smoke" skips those tests.

This shows how markers categorize tests and control which tests run.

Common Mistakes - 3 Pitfalls

Not registering custom markers in pytest.ini

Using markers inconsistently or with typos

Running pytest without specifying markers when needed

Bonus Challenge

Add a new marker 'slow' to one test and run tests excluding 'slow' tests

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