The new TrigramSimilarity feature of the django.contrib.postgres was great for a problem I had. I use it for a search bar to find hard to spell latin names. The problem is that there are over 2 million names, and the search takes longer then I want.
I'd like to create a index on the trigrams as descibed in the postgres documentation.
But I am not sure how to do this in a way that the Django API would make use of it. For the postgres text search there is a description on how to create an index, but not for the trigram similarity.
This is what I have right now:
class NCBI_names(models.Model):
tax_id = models.ForeignKey(NCBI_nodes, on_delete=models.CASCADE, default = 0)
name_txt = models.CharField(max_length=255, default = '')
name_class = models.CharField(max_length=32, db_index=True, default = '')
class Meta:
indexes = [GinIndex(fields=['name_txt'])]
In the view's get_queryset
method:
class TaxonSearchListView(ListView):
#form_class=TaxonSearchForm
template_name='collectie/taxon_list.html'
paginate_by=20
model=NCBI_names
context_object_name = 'taxon_list'
def dispatch(self, request, *args, **kwargs):
query = request.GET.get('q')
if query:
try:
tax_id = self.model.objects.get(name_txt__iexact=query).tax_id.tax_id
return redirect('collectie:taxon_detail', tax_id)
except (self.model.DoesNotExist, self.model.MultipleObjectsReturned) as e:
return super(TaxonSearchListView, self).dispatch(request, *args, **kwargs)
else:
return super(TaxonSearchListView, self).dispatch(request, *args, **kwargs)
def get_queryset(self):
result = super(TaxonSearchListView, self).get_queryset()
#
query = self.request.GET.get('q')
if query:
result = result.exclude(name_txt__icontains = 'sp.')
result = result.annotate(similarity=TrigramSimilarity('name_txt', query)).filter(similarity__gt=0.3).order_by('-similarity')
return result