Adding new subdivision or plat alternatename re-saves all matching zo…

…oniverse subjects.

apps/plat/models.py

@@ -108,6 +108,11 @@ def save(self, *args, **kwargs):
                 ))
         ParcelJoinCandidate.objects.bulk_create(join_cands, batch_size=5000)
 
+        print(self.alternate_name)
+        for z in ZooniverseSubject.objects.filter(workflow=self.workflow, addition_final__iexact=self.alternate_name):
+            # print(z.pk, z.addition_final)
+            z.save()
+
 
 class Subdivision(models.Model):
     '''This is presumed to be a modern Subdivision GIS layer (as opposed to a plat map), but there may be other uses'''
@@ -135,6 +140,7 @@ def save(self, *args, **kwargs):
         self.name_standardized = self.standardize_addition(
             self.name)
 
+
 class SubdivisionAlternateName(models.Model):
     workflow = models.ForeignKey(
         'zoon.ZooniverseWorkflow', null=True, on_delete=models.SET_NULL)
@@ -195,7 +201,8 @@ def save(self, *args, **kwargs):
         ParcelJoinCandidate.objects.bulk_create(join_cands, batch_size=5000)
 
         # Re-save all zooniverse subjects with this alternate name
+        # TODO: Do this in a more bulky way
         print(self.alternate_name)
-        for z in ZooniverseSubject.objects.filter(workflow=self.workflow, addition_final=self.alternate_name):
+        for z in ZooniverseSubject.objects.filter(workflow=self.workflow, addition_final__iexact=self.alternate_name):
             # print(z.pk, z.addition_final)
             z.save()

apps/zoon/management/commands/load_zooniverse_export.py

@@ -215,7 +215,9 @@ def consolidate_responses(self, workflow, question_lookup: dict):
             lambda x: json.dumps(x))
 
         # S3 lookups, not image links
-        subject_df['image_ids'] = subject_df['subject_data_flat__image_ids'].apply(lambda x: json.dumps(split(x)))
+        # TODO: Not sure what is up with the split here -- in Anoka County, early data comes back as a single string.
+        # Might be error in building of Zooniverse manifest, or might be early data only, as this got changed later.
+        subject_df['image_ids'] = subject_df['subject_data_flat__image_ids'].apply(lambda x: json.dumps(x.split(',') if x is not None else ''))
 
         subject_df.drop(columns=['subject_data_flat__image_ids'], inplace=True)
         subject_df.drop(columns=image_cols, inplace=True)