Custom markers in PyTest - Test Execution Trace

Test Overview

This test uses a custom marker to categorize a test case. It verifies that the test runs only when the marker is used and that the assertion inside the test passes.

Test Code - pytest

PyTest

import pytest

@pytest.mark.slow
def test_addition():
    result = 2 + 3
    assert result == 5

Execution Trace - 4 Steps

Step	Action	System State	Assertion	Result
1	Pytest starts test collection and identifies test_addition with custom marker 'slow'.	Test suite is ready to run tests with markers.	—	PASS
2	Pytest runs test_addition marked with @pytest.mark.slow.	Inside test_addition function, calculation 2 + 3 is performed.	—	PASS
3	Assertion checks if result equals 5.	Variable result holds value 5.	assert result == 5	PASS
4	Test test_addition completes successfully.	Test marked 'slow' passed.	—	PASS

Failure Scenario

Failing Condition: The assertion fails because the result is not equal to 5.

Execution Trace Quiz - 3 Questions

What does the custom marker '@pytest.mark.slow' do in this test?

A It categorizes the test as slow so it can be selectively run.

B It makes the test run faster.

C It skips the test automatically.

D It changes the assertion behavior.

Key Result

Using custom markers helps organize tests by categories like speed or feature, allowing selective test runs and better test management.

Practice

1. What is the main purpose of using custom markers in pytest?

easy

A. To generate test data automatically

B. To change the Python interpreter version

C. To automatically fix test failures

D. To label tests for grouping and selective running

Solution

1. Step 1: Understand what custom markers do

   Custom markers in pytest are used to tag tests with labels for easier management.

2. Step 2: Identify the purpose of these labels

   These labels help run specific groups of tests selectively using the marker name.

3. Final Answer:

   To label tests for grouping and selective running -> Option D

4. Quick Check:

   Custom markers = test grouping [OK]

Hint: Markers tag tests to run groups easily [OK]

Common Mistakes:

• Thinking markers change Python version
• Assuming markers fix test errors automatically
• Confusing markers with test data generation

2. Which of the following is the correct syntax to mark a test with a custom marker named slow?

easy

A. @pytest.mark.slow\ndef test_example(): pass

B. @pytest.slow.mark\ndef test_example(): pass

C. @pytest.mark[slow]\ndef test_example(): pass

D. @pytest.mark('slow')\ndef test_example(): pass

Solution

1. Step 1: Recall pytest marker syntax

   Custom markers use dot notation: @pytest.mark.markername before the test function.

2. Step 2: Match the correct syntax

   @pytest.mark.slow is the correct way to apply the 'slow' marker.

3. Final Answer:

   @pytest.mark.slow\ndef test_example(): pass -> Option A

4. Quick Check:

   Marker syntax = @pytest.mark.name [OK]

Hint: Use dot notation: @pytest.mark.name [OK]

Common Mistakes:

• Using parentheses instead of dot notation
• Using square brackets instead of dot notation
• Placing marker after function name

3. Given the following test file, what will be the output when running pytest -m slow?

import pytest

@pytest.mark.slow
def test_a():
    assert True

def test_b():
    assert True

@pytest.mark.slow
def test_c():
    assert False

medium

A. Runs all tests; test_c fails

B. Runs only test_b; all pass

C. Runs test_a and test_c; test_c fails, test_a passes

D. Runs test_a and test_b; all pass

Solution

1. Step 1: Understand what pytest -m slow does

   This command runs only tests marked with the 'slow' marker.

2. Step 2: Identify marked tests in the code

   test_a and test_c have @pytest.mark.slow, so only these run.

3. Step 3: Check test results

   test_a passes (assert True), test_c fails (assert False).

4. Final Answer:

   Runs test_a and test_c; test_c fails, test_a passes -> Option C

5. Quick Check:

   pytest -m slow runs marked tests only [OK]

Hint: -m runs only tests with that marker [OK]

Common Mistakes:

• Assuming all tests run with -m option
• Ignoring test failures in marked tests
• Running unmarked tests by mistake

4. What is wrong with this pytest marker usage?

import pytest

@pytest.mark.slow()
def test_example():
    assert True

medium

A. Markers should not have parentheses unless parameters are used

B. Marker name must be uppercase

C. The test function must have parameters

D. pytest.mark cannot be used on test functions

Solution

1. Step 1: Check marker syntax

   Markers without parameters should not have parentheses; @pytest.mark.slow() is incorrect.

2. Step 2: Correct usage

   Use @pytest.mark.slow without parentheses for simple markers.

3. Final Answer:

   Markers should not have parentheses unless parameters are used -> Option A

4. Quick Check:

   Use parentheses only with marker args [OK]

Hint: No parentheses for simple markers [OK]

Common Mistakes:

• Adding empty parentheses to markers
• Using uppercase marker names incorrectly
• Thinking markers require function parameters

5. You want to run tests marked as database but exclude those also marked as slow. Which pytest command achieves this?

hard

A. pytest -m "database or slow"

B. pytest -m "database and not slow"

C. pytest -m "not database and slow"

D. pytest -m "database and slow"

Solution

1. Step 1: Understand marker expressions

   pytest supports boolean expressions with markers: and, or, not.

2. Step 2: Formulate the correct expression

   To run tests marked 'database' but exclude 'slow', use "database and not slow".

3. Final Answer:

   pytest -m "database and not slow" -> Option B

4. Quick Check:

   Use boolean logic in -m to include/exclude markers [OK]

Hint: Use boolean logic: -m "marker and not other" [OK]

Common Mistakes:

• Using 'or' instead of 'and not' to exclude
• Misplacing 'not' before the first marker
• Combining markers without quotes