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Measure the suite before changing pytest-asyncio
First establish whether asynchronous test setup or event-loop creation is taking a meaningful share of your suite’s time. Record a baseline, identify slow tests and repeated setup, and avoid attributing all runtime to pytest-asyncio: slow application work, external services, fixtures, and test collection may matter more.
- Choose a representative test selection. Use the same tests for every comparison; include enough async tests to exercise the configuration you plan to change.
- Keep conditions consistent. Run comparisons on the same machine and environment, with the same dependency versions, test selection, and warm or cold state. Repeat runs and compare the results rather than relying on one timing.
- Change one setting at a time. Record the pytest-asyncio version and configuration alongside each run. Do not assume a setting improved performance unless your own measurements show it.
- Check correctness as well as duration. Run the full relevant test suite and look for order-dependent failures or state leaking between tests.
The current pytest-asyncio 1.4.0 documentation describes loop scopes and configuration, but does not quantify a speed gain for changing them. Defaults and deprecations can change, so check the documentation for the version installed in your project.
Experiment with a broader event-loop scope
By default, each async test runs in its own event loop, and the default test-loop scope is function. pytest-asyncio supports function, class, module, package, and session scopes. A broader scope can reduce repeated loop setup in some suites, but it also means tests share loop state for longer. Treat it as a benchmarkable configuration choice, not an automatic optimization.
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For a controlled experiment, set the default test-loop scope in your pytest configuration:
[tool.pytest.ini_options]
asyncio_default_test_loop_scope = "session"This example configures a session-scoped loop for tests. Compare it with the function-scoped default using the same benchmark procedure. If sharing causes failures, leaks state, or conflicts with fixture assumptions, use a narrower scope or isolate the tests that require different loop lifetimes. The pytest-asyncio guide to changing the default event-loop scope shows the configuration, and the marker reference documents supported scopes.
Pick scope based on isolation and fixture lifetime
- Function: each async test gets a fresh loop, supporting the strongest test-to-test isolation. It is the documented default for test-loop scope.
- Class, module, package, or session: tests can share a loop over a wider boundary. Consider these only when the tests and async fixtures are compatible with that shared lifetime, then validate behavior and timing.
Fixtures and tests must agree about loop lifetime. A broader default is not a substitute for checking fixture scope, cleanup, and any objects that are bound to a particular loop.
Choose auto or strict mode for plugin ownership
Mode affects how pytest-asyncio handles async tests and fixtures; it is not a speed setting. The current configuration documentation lists auto and strict, and says strict is the default when no mode is specified. Check your installed version and project configuration instead of assuming an implicit default.
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If the project uses asyncio alone and you prefer less explicit marking, configure:
[tool.pytest.ini_options]
asyncio_mode = "auto"Auto mode is intended to be convenient for asyncio-only projects. Confirm that it fits the way your tests and fixtures are declared.
Use strict when async plugin ownership should be explicit
Strict mode is appropriate when another async framework or pytest plugin may also handle asynchronous tests. It preserves explicit ownership rather than having pytest-asyncio automatically take over async tests. The older pytest-asyncio concepts page explains the rationale behind auto and strict; use the current configuration reference for current settings and defaults.
You can select a mode at the command line with --asyncio-mode; the current configuration reference documents the available values and configuration options.
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Do not mistake async tests for parallel test execution
Awaiting concurrent work inside one test is different from scheduling separate test cases concurrently. pytest-asyncio’s guide says parametrized asynchronous cases still run sequentially. Parametrizing a test therefore does not, by itself, make those cases run in parallel. See the guide to parametrizing asynchronous tests.
Update old event-loop customization recipes
If you need tests to use different event loops, consult the current customization guidance rather than copying an older recipe. The pytest-asyncio 1.4.0 guide says overriding event_loop_policy is deprecated and recommends the pytest_asyncio_loop_factories hook instead. Follow the multiple event loops guide for the current approach.
Troubleshoot speed experiments
- No measurable improvement: loop setup may not be a significant cost in this suite. Keep the simpler or more isolated configuration unless measurements justify a change.
- Tests fail only after widening scope: investigate shared state, cleanup, and fixtures that assumed a fresh loop. Return affected tests to a narrower scope or isolate them.
- Async tests or fixtures behave differently after changing mode: verify the configured mode, pytest-asyncio version, and whether another async plugin requires explicit ownership; strict mode may be more suitable for coexisting plugins.
- Different event-loop customization no longer works as expected: check whether an old
event_loop_policyoverride is involved and use the documented loop-factory hook guidance. - Only parametrized cases are slow: parametrization does not make async cases execute concurrently. Identify the work each case performs and distinguish test-level scheduling from concurrency within an individual test.
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