2.1 KiB
name, group, category, update-time, description, key-word
| name | group | category | update-time | description | key-word | ||||
|---|---|---|---|---|---|---|---|---|---|
| async-logger-shutdown | api | async | 20260512 | Gracefully stop an async logger by waiting for idle or clearing queued work, then waiting for the worker to finish. |
|
Async-logger-shutdown
Gracefully stop an async logger. This is the main high-level shutdown API for async logging because it coordinates drain behavior, closure, and worker completion.
Interface
pub async fn[S] AsyncLogger::shutdown(self : AsyncLogger[S], clear? : Bool = false) -> Unit {}
input
self : AsyncLogger[S]- Async logger that should be shut down.clear : Bool- Whether pending records should be abandoned immediately instead of waiting for idle first.
output
Unit- No return value. The method completes after shutdown coordination finishes.
Explanation
Detailed rules explaining key parameters and behaviors
clear=falsefirst waits for idle, then closes the logger.- If backlog still remains after waiting, shutdown falls back to
close(clear=true). clear=trueimmediately closes and abandons pending records.- The method waits until
is_running()becomesfalsebefore returning.
How to Use
Here are some specific examples provided.
When Need Graceful Service Shutdown
When a service should stop logging only after queued records are drained:
await logger.shutdown()
In this example, the logger waits for normal drain behavior before final closure.
When Need Fast Shutdown Under Pressure
When teardown should prefer speed over preserving backlog:
await logger.shutdown(clear=true)
In this example, pending work is abandoned intentionally so shutdown can complete sooner.
Error Case
e.g.:
-
If
clear=true, pending records are intentionally dropped rather than drained. -
If callers skip
shutdown()and only inspect flags manually, it is easier to leave the worker lifecycle in an unclear state.
Notes
-
Prefer this API over raw
close()in normal application shutdown paths. -
Choose
clear=trueonly when loss of queued records is acceptable.