Persist task_run_count using state context #1556
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jlowin
reviewed
Sep 27, 2019
| @@ -280,6 +280,9 @@ def __init__( | |||
| ): | |||
| super().__init__(message=message, result=result, cached_inputs=cached_inputs) | |||
| self.start_time = pendulum.instance(start_time or pendulum.now("utc")) | |||
| run_count = prefect.context.get("task_run_count") | |||
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This "feels" like a very fragile thing but I can't think of a better way to do it
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Yea that's fair; this field is populated in every task runner pipeline step (which is where all state transitions occur), but I understand your point. I think the way to think about it is that this will be populated within a "run context" but not otherwise, and this key is always present within a run context.
jlowin
approved these changes
Sep 28, 2019
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Please describe your work and make sure your PR:
CHANGELOG.md(if appropriate)docs/outline.tomlfor API reference docs (if appropriate)Note that your PR will not be reviewed unless all three boxes are checked.
What does this PR change?
This PR persists
task_run_countwithin the newly introducedstate.contextattribute for communicating the current run count across multiple state transitions (e.g., Retrying -> Paused -> Resume -> Running -> Failed -> Retrying -> etc.). Note that this PR only attaches this data toScheduledstates, as attaching it to other states causes the run count to effectively "freeze" across runs.Why is this PR important?
Closes #1177