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Prevalence updates failing #1570

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apiology opened this issue Sep 19, 2022 · 1 comment · May be fixed by #1571
Closed

Prevalence updates failing #1570

apiology opened this issue Sep 19, 2022 · 1 comment · May be fixed by #1571
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type: bug Something isn't working

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@apiology
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apiology commented Sep 19, 2022 •
edited

Describe the bug

Automatic prevalence updates have started failing - the first failure started on the auto-update-prevalence-2022-09-17--14-21-18 branch.

Link to microCOVID scenario

https://github.com/microCOVID/microCOVID/actions

To Reproduce

Steps to reproduce the behavior:

  1. Set up per https://github.com/microCOVID/microCOVID/#local-development
  2. Run ./update_prevalence.py
  3. See error:
Traceback (most recent call last):
  File "./update_prevalence.py", line 1685, in <module>
    main()
  File "./update_prevalence.py", line 1608, in main
    app_locations[state.app_key] = state.as_app_data()
  File "./update_prevalence.py", line 692, in as_app_data
    result = super().as_app_data()
  File "./update_prevalence.py", line 627, in as_app_data
    last_week = self.cases_last_week
  File "./update_prevalence.py", line 494, in cases_last_week
    return self.cases_in_cum_cases(self.recent_daily_cumulative_cases[-8:])
  File "./update_prevalence.py", line 419, in recent_daily_cumulative_cases
    raise ValueError(
ValueError: Missing data for Pitcairn Islands, United Kingdom on 2022-09-18 - Counter({datetime.date(2022, 9, 13): 4, datetime.date(2022, 9, 12): 4, datetime.date(2022, 9, 11): 4, datetime.date(2022, 9, 10): 4, datetime.date(2022, 9, 9): 4, datetime.date(2022, 9, 8): 4, datetime.date(2022, 9, 7): 4, datetime.date(2022, 9, 6): 4, datetime.date(2022, 9, 5): 4, datetime.date(2022, 9, 4): 4, datetime.date(2022, 9, 3): 4, datetime.date(2022, 9, 2): 4})

Expected behavior

Prevalence updates successfully.

Is this a regression?

Yes; last success was 2022-09-14

Additional context / screenshots

image
@apiology apiology added the type: bug Something isn't working label Sep 19, 2022
apiology added a commit to apiology/microCOVID that referenced this issue Sep 21, 2022
@apiology
Cleanly drop state data upon failures and continue processing
f395e2f 
Fixes microCOVID#1570

This will drop a state-level locale from the dataset if we encounter
an error while processing data within it.  microCOVID#1570 was caused by the
upstream JHU data no longer sending data from Pitcairn Islands, which
is considered a state-level locale under the UK in the JHU dataset.
@apiology apiology mentioned this issue Sep 21, 2022
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@apiology
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Perhaps related to this upstream issue CSSEGISandData/COVID-19#6096

Fixed upstream in CSSEGISandData/COVID-19@789b82d - prevalence just ran successfully and the site is now up to date.

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Cleanly drop state data upon failures and continue processing apiology/microCOVID
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@apiology