Comments (2)
This would be a cool feature, here's 2 ideas I have for it:
- A "start from step " option that starts any workflow from a given step
- A "mark step as completed" option which might be cleaner. Ie after manual intervention, you mark the step as successful and the dependency chain continues as normal.
1 has additional use cases beyond failures, ie you have bad data from one point on so there's no explicit failure, but you dont want to run the whole job again. 2 is probably the simplest fix simply for manually correcting errors like in your use case.
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I think we'd want to do a slight variant on 2. Instead of marking as completed, we should add a fourth task state representing a skipped job. Job states currently include waiting, running, and failed. These states are used to determine what actions are possible at any given time: https://github.com/thieman/dagobah/blob/master/dagobah/core/components.py#L49
I think the clarity of adding a fourth state would be worth the extra effort. It would be weird to get a job completed email that told you Task 7 was completed when in fact you skipped it.
You should be able to manually mark a task as skipped in the UI and then retry the job. Skipped tasks should be counted as "completed" for the purposes of graph traversal and job completion.
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Related Issues (20)
- error when start dagobah
- Installation issue, missing gpost HOT 1
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- get_status method for job HOT 2
- Changing code to use py-dag as a package instead of the internal file HOT 2
- RuntimeError: can't start new thread
- How to run and debug the whole project? HOT 1
- Is it distributed?
- Timezone cron / scheduler
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- Run Dagobah from folder HOT 1
- Address jump HOT 6
- [CLOSED] reformat code
- [CLOSED] Reformat code
- [CLOSED] Reformat code
- [CLOSED] update setup requirements
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- [CLOSED] Close SSH connection for remote tasks
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