4541 Introduced clean_up_docket_judges command to clean up assigned_to and referred_to #4555
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mlissner
requested changes
Oct 12, 2024
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| async_to_sync(lookup_judge_by_full_name)( | ||
| d.referred_to_str, d.court_id, d.date_filed | ||
| ) | ||
| if d.referred_to_str | ||
| else None | ||
| ) | ||
| new_assigned = ( | ||
| async_to_sync(lookup_judge_by_full_name)( | ||
| d.assigned_to_str, d.court_id, d.date_filed | ||
| ) | ||
| if d.assigned_to_str | ||
| else None |
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Could you use lru_cache here to avoid zillions of DB lookups? Maybe set a maxsize of, say 30k so that we catch most judge names?
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As described in #4541, this PR introduces the
clean_up_docket_judgescommand to clean upassigned_toandreferred_tofields when their correspondingassigned_to_strandreferred_to_strvalues have changed, and we don't have the new judges in database.This works by checking all the dockets in the database where
referred_toandassigned_toare notnull. Then, the docketassigned_to_strandreferred_to_strvalues are used to perform a Judge lookup usinglookup_judge_by_full_name.If the current
assigned_toandreferred_tovalues are different from the ones returned by the lookup (which includes aNonevalue in case the Judge is not found), the docket is updated.Since this
save()will trigger an Elasticsearch update, it's better to do it slowly. I set a default sleep of 0.1 seconds between each update. We can monitor how this performs and adjust the wait time between iterations accordingly.The command can be run as:
manage.py clean_up_docket_judges --iteration-wait 0.1