-
Notifications
You must be signed in to change notification settings - Fork 1.6k
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
why dagster automatically convert job config of timestamp string into datetime #27855
Comments
this is the stacktrace of bug: File "/media/mathews/LENOVO/orchastack/quant-wp/quantenv/lib/python3.12/site-packages/dagster/_core/execution/plan/execute_plan.py", line 245, in dagster_event_sequence_for_step |
What's the issue?
why dagster automatically convert job config of timestamp string into datetime?
I config a job with string of datetime, because dagster does not support datetime as config field.
but either start the job from UI or from graph api, the job runs with error:
Error 1: Invalid scalar at path root:end_time. Value "2025-02-13 15:00:00" of type "<class 'datetime.datetime'>" is not valid for expected type "String".
Error 2: Invalid scalar at path root:start_time. Value "2023-08-05 09:00:00" of type "<class 'datetime.datetime'>" is not valid for expected type "String".
my config in UI is :
{'symbol':'000034', 'start_time':'2023-08-05T09:00:00', 'end_time':'2025-02-13T15:00:00'}
and run from graph api with config:
run_job(
"job_bar_data",
{
"start_time": "2023-08-05T09:00:00",
"end_time": "2025-02-13T15:00:00",
"symbol": "000034",
"period": "1",
},
)
obviously, dagster automatically convert the start_time and end_time string into datetime.datetime.
this is just really acceptable, as dagster doesn't support datetime as config field.
please fix the bug.
What did you expect to happen?
No response
How to reproduce?
No response
Dagster version
1.9.9, 1.10.0
Deployment type
None
Deployment details
No response
Additional information
No response
Message from the maintainers
Impacted by this issue? Give it a 👍! We factor engagement into prioritization.
The text was updated successfully, but these errors were encountered: