Flaky is a plugin for nose or pytest that automatically reruns flaky tests.
Ideally, tests reliably pass or fail, but sometimes test fixtures must rely on components that aren't 100% reliable. With flaky, instead of removing those tests or marking them to @skip, they can be automatically retried.
For more information about flaky, see this presentation.
Marking tests flaky
To mark a test as flaky, simply import flaky and decorate the test with @flaky:
from flaky import flaky
@flaky def test_something_that_usually_passes(self): value_to_double = 21 result = get_result_from_flaky_doubler(value_to_double) self.assertEqual(result, value_to_double * 2, 'Result doubled incorrectly.')
By default, flaky will retry a failing test once, but that behavior can be overridden by passing values to the flaky decorator. It accepts two parameters: max_runs, and min_passes; flaky will run tests up to max_runs times, until it has succeeded min_passes times. Once a test passes min_passes times, it's considered a success; once it has been run max_runs times without passing min_passes times, it's considered a failure.
@flaky(max_runs=3, min_passes=2) def test_something_that_usually_passes(self): """This test must pass twice, and it can be run up to three times.""" value_to_double = 21 result = get_result_from_flaky_doubler(value_to_double) self.assertEqual(result, value_to_double * 2, 'Result doubled incorrectly.')
Marking a class flaky
In addition to marking a single test flaky, entire test cases can be marked flaky:
@flaky class TestMultipliers(TestCase): def test_flaky_doubler(self): value_to_double = 21 result = get_result_from_flaky_doubler(value_to_double) self.assertEqual(result, value_to_double * 2, 'Result doubled incorrectly.') @flaky(max_runs=3) def test_flaky_tripler(self): value_to_triple = 14 result = get_result_from_flaky_tripler(value_to_triple) self.assertEqual(result, value_to_triple * 3, 'Result tripled incorrectly.')
The @flaky class decorator will mark test_flaky_doubler as flaky, but it won't override the 3 max_runs for test_flaky_tripler (from the decorator on that test method).
@pytest.mark.flaky can be used in place of
Don't rerun certain types of failures
Depending on your tests, some failures are obviously not due to flakiness. Instead of rerunning after those failures, you can specify a filter function that can tell flaky to fail the test right away.
def is_not_crash(err, *args): return not issubclass(err, ProductCrashedError) @flaky def test_something(): raise ProductCrashedError @flaky(rerun_filter=is_not_crash) def test_something_else(): raise ProductCrashedError
Flaky will run
test_something twice, but will only run
It can also be used to incur a delay between test retries:
import time def delay_rerun(*args): time.sleep(1) return True @flaky(rerun_filter=delay_rerun) def test_something_else(): ...
Activating the plugin
Like any nose plugin, flaky can be activated via the command line:
With pytest, flaky will automatically run. It can, however be disabled via the command line:
pytest -p no:flaky
Command line arguments
No Flaky Report
--no-flaky-report to suppress the report at the end of the run detailing flaky test results.
Shorter Flaky Report
--no-success-flaky-report to suppress information about successful flaky tests.
--force-flaky to treat all tests as flaky.
--min-passes=MIN_PASSES to control the behavior of flaky if
is specified. Flaky decorators on individual tests will override these defaults.
Additional usage examples are in the code - see test/test_nose/test_nose_example.py and test/test_pytest/test_pytest_example.py
To install, simply:
pip install flaky
Flaky is tested with the following test runners and options:
- Nosetests. Doctests cannot be marked flaky.
- Py.test. Works with
pytest-xdistbut not with the
--boxedoption. Doctests cannot be marked flaky.
Create a virtual environment and install packages -
mkvirtualenv flaky pip install -r requirements-dev.txt
Run all tests using -
The tox tests include code style checks via pycodestyle and pylint.
Copyright and License
Copyright 2015 Box, Inc. All rights reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.