Flaky test detection and retry in PyTest - Build an Automation Script

Detect flaky test and retry on failure using pytest

Preconditions (2)

Step 1: Create a test function that randomly fails

Step 2: Add a decorator to retry the test up to 3 times on failure

Step 3: Run the test suite

Step 4: Observe if the test retries when it fails

Step 5: Verify the test passes if it succeeds within retries or fails after retries

✅ Expected Result: The flaky test retries up to 3 times on failure and passes if any retry succeeds; otherwise, it fails after all retries.

Automation Requirements - pytest with pytest-rerunfailures plugin

Assertions Needed:

Test passes if it succeeds within retry attempts

Test fails if all retry attempts fail

Best Practices:

Use pytest-rerunfailures plugin for retry logic

Keep flaky test logic simple and isolated

Use explicit assertions for pass/fail

Avoid hardcoding retry logic inside test functions

Automated Solution

PyTest

import random
import pytest

@pytest.mark.flaky(reruns=3, reruns_delay=1)
def test_flaky_behavior():
    # Simulate flaky behavior: 50% chance to fail
    assert random.choice([True, False]), "Random failure to simulate flakiness"

This test uses the @pytest.mark.flaky decorator from the pytest-rerunfailures plugin to retry the test up to 3 times if it fails.

The test function test_flaky_behavior randomly fails half the time by asserting a random boolean.

If the test fails, pytest automatically retries it up to 3 times with a 1-second delay between retries.

This approach cleanly separates retry logic from test logic and uses a well-supported plugin.

Common Mistakes - 3 Pitfalls

Using time.sleep inside test to wait for retry

Hardcoding retry logic inside the test function with loops

Not installing or enabling pytest-rerunfailures plugin

Bonus Challenge

Now add data-driven testing with 3 different flaky scenarios using pytest parametrize

Show Hint

Practice

1. What is the main purpose of marking a test as flaky in pytest using @pytest.mark.flaky(reruns=N)?

easy

A. To skip the test permanently

B. To automatically retry the test N times if it fails

C. To mark the test as slow and run it last

D. To run the test only once without retries

Solution

1. Step 1: Understand the flaky test concept

   Flaky tests fail randomly due to timing or environment issues, so retries help reduce false failures.

2. Step 2: Analyze the effect of @pytest.mark.flaky(reruns=N)

   This decorator tells pytest to rerun the test up to N times if it fails, increasing chances of passing despite flakiness.

3. Final Answer:

   To automatically retry the test N times if it fails -> Option B

4. Quick Check:

   Flaky test retry = reruns N times [OK]

Hint: Retries mean automatic rerun on failure [OK]

Common Mistakes:

• Confusing flaky with skipped tests
• Thinking flaky marks slow tests
• Assuming flaky disables retries

2. Which of the following is the correct syntax to retry a flaky test 3 times in pytest?

easy

A. @pytest.flaky(tries=3)

B. @pytest.retry(3)

C. @pytest.mark.retry(3)

D. @pytest.mark.flaky(reruns=3)

Solution

1. Step 1: Recall the correct decorator name and parameter

   The correct decorator is @pytest.mark.flaky with parameter reruns to specify retry count.

2. Step 2: Match syntax with options

   @pytest.mark.flaky(reruns=3) uses @pytest.mark.flaky(reruns=3), which is the correct syntax for retrying 3 times.

3. Final Answer:

   @pytest.mark.flaky(reruns=3) -> Option D

4. Quick Check:

   Decorator name + reruns param = correct syntax [OK]

Hint: Use @pytest.mark.flaky with reruns param [OK]

Common Mistakes:

• Using @pytest.retry instead of @pytest.mark.flaky
• Using wrong parameter names like tries
• Missing the mark prefix

3. Given this pytest test code snippet, what will be the output if the test randomly fails once and passes on retry?

import pytest

@pytest.mark.flaky(reruns=2)
def test_random():
    import random
    assert random.choice([True, False])

medium

A. Test may pass after 1 or 2 retries if random returns True

B. Test always fails because random.choice is unpredictable

C. Test runs only once and fails if random returns False

D. Test is skipped due to flaky mark

Solution

1. Step 1: Understand the flaky decorator effect

   The test will rerun up to 2 times if it fails, allowing multiple chances to pass.

2. Step 2: Analyze the random assertion

   The assertion randomly passes or fails. If it fails once, retry can pass if random returns True on retry.

3. Final Answer:

   Test may pass after 1 or 2 retries if random returns True -> Option A

4. Quick Check:

   Retries allow passing despite random failure [OK]

Hint: Retries give multiple chances to pass random failures [OK]

Common Mistakes:

• Assuming flaky skips tests
• Thinking test always fails on first try
• Ignoring retry count effect

4. You wrote this flaky test with retry but it never retries on failure. What is the error?

import pytest

@pytest.mark.flaky(rerun=3)
def test_example():
    assert False

medium

A. The test must return True to retry

B. The decorator should be @pytest.retry, not @pytest.mark.flaky

C. The parameter name should be 'reruns', not 'rerun'

D. The test cannot retry if it always fails

Solution

1. Step 1: Check the decorator parameter spelling

   The correct parameter for retry count is reruns, not rerun.

2. Step 2: Understand impact of wrong parameter

   Using rerun is ignored by pytest, so no retries happen despite failures.

3. Final Answer:

   The parameter name should be 'reruns', not 'rerun' -> Option C

4. Quick Check:

   Correct param spelling = reruns [OK]

Hint: Check exact parameter spelling: reruns, not rerun [OK]

Common Mistakes:

• Misspelling reruns parameter
• Using wrong decorator name
• Expecting retries on always failing test

5. You want to reduce false failures from a flaky test that sometimes fails due to timing issues. Which approach best combines flaky test detection and retry in pytest?

hard

A. Use @pytest.mark.flaky(reruns=3) and add explicit wait in test code

B. Use @pytest.mark.skip to ignore the flaky test

C. Remove retries and fix test to always pass

D. Use @pytest.mark.flaky(reruns=0) to disable retries

Solution

1. Step 1: Understand flaky test retry purpose

   Retries help reduce false failures by rerunning tests that fail randomly.

2. Step 2: Combine retry with test stabilization

   Adding explicit waits addresses timing issues, improving test stability alongside retries.

3. Step 3: Evaluate other options

   Skipping ignores tests, removing retries loses retry benefit, and reruns=0 disables retries.

4. Final Answer:

   Use @pytest.mark.flaky(reruns=3) and add explicit wait in test code -> Option A

5. Quick Check:

   Retries + waits = best flaky test handling [OK]

Hint: Combine retries with waits to fix flaky timing issues [OK]

Common Mistakes:

• Skipping flaky tests instead of fixing
• Disabling retries by setting reruns=0
• Ignoring timing issues causing flakiness