command line to rebuild index

cookbook/management/commands/rebuildindex.py

@@ -0,0 +1,27 @@
+from django.conf import settings
+from django.contrib.postgres.search import SearchVector
+from django.core.management.base import BaseCommand, CommandError
+from django_scopes import scopes_disabled
+from django.utils.translation import gettext_lazy as _
+
+from cookbook.models import Recipe
+
+
+# can be executed at the command line with 'python manage.py rebuildindex'
+class Command(BaseCommand):
+    help = _('Rebuilds full text search index on Recipe')
+
+    def handle(self, *args, **options):
+        if settings.DATABASES['default']['ENGINE'] not in ['django.db.backends.postgresql_psycopg2', 'django.db.backends.postgresql']:
+            self.stdout.write(self.style.WARNING(_('Only Postgress databases use full text search, no index to rebuild')))
+
+        try:
+            with scopes_disabled():
+                search_vector = (
+                    SearchVector('name', weight='A')
+                    + SearchVector('description', weight='B'))
+                Recipe.objects.all().update(search_vector=search_vector)
+
+                self.stdout.write(self.style.SUCCESS(_('Recipe index rebuild complete.')))
+        except:
+            self.stdout.write(self.style.ERROR(_('Recipe index rebuild failed.')))

cookbook/managers.py

@@ -20,9 +20,12 @@ class RecipeSearchManager(models.Manager):
             + SearchVector(StringAgg('steps__ingredients__food__name', delimiter=' '), weight='B', config='english')
             + SearchVector(StringAgg('keywords__name', delimiter=' '), weight='B', config='english'))
         search_rank = SearchRank(search_vectors, search_query)
-        # trigram_similarity = TrigramSimilarity(
+        # the results from trigram were really, really bad
-        #     'headline', search_text
+        # trigram = (
-        # )
+        #     TrigramSimilarity('name', search_text)
+        #     + TrigramSimilarity('description', search_text)
+        #     + TrigramSimilarity('steps__ingredients__food__name', search_text)
+        #     + TrigramSimilarity('keywords__name', search_text))
         return (
             self.get_queryset()
             .annotate(search=search_vectors, rank=search_rank)