kit-eco.social/consumocuidado-server
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fixed vector search not finding nested tags

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This commit is contained in:
Sam
2021-02-18 13:22:08 +00:00
parent 47633c889d
commit 978a7c9520
3 changed files with 18 additions and 20 deletions
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1
products/tests.py
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@@ -487,7 +487,6 @@ class ProductSearchTest(TestCase):
# load response data # load response data
payload = response.json() payload = response.json()
# check for object creation # check for object creation
import ipdb; ipdb.set_trace()
self.assertEquals(len(payload['products']), len(expected_instances)) self.assertEquals(len(payload['products']), len(expected_instances))
# check ids # check ids
for i in range(len(payload['products'])): for i in range(len(payload['products'])):

29
products/utils.py
View File

@@ -57,7 +57,7 @@ def extract_search_filters(result_set):
return filter_dict return filter_dict
def find_related_products(keyword): def find_related_products_v1(keyword):
# search in tags # search in tags
tags = Product.tags.tag_model.objects.filter(name__icontains=keyword) tags = Product.tags.tag_model.objects.filter(name__icontains=keyword)
# search in category # search in category
@@ -75,23 +75,22 @@ def find_related_products(keyword):
return products_qs return products_qs
def alt_rank_find_related_products(keyword): def find_related_products_v2(keyword):
# TODO: figure out why it includes unrelated instances fields=('name', 'description', 'tags__label', 'attributes__label', 'category__name')
fields=('name', 'description', 'tags__name', 'attributes__name', 'category__name')
vector = SearchVector(*fields)
query = SearchQuery(keyword)
products_qs = Product.objects.annotate(
rank=SearchRank(vector, query)
).order_by('-rank')
import ipdb; ipdb.set_trace()
return products_qs
def alt_find_related_products(keyword):
fields=('name', 'description', 'tags__name', 'attributes__name', 'category__name')
vector = SearchVector(*fields) vector = SearchVector(*fields)
products_qs = Product.objects.annotate( products_qs = Product.objects.annotate(
search=vector search=vector
).filter(search=keyword) ).filter(search=keyword)
return products_qs return products_qs
def alt_rank_find_related_products(keyword):
# TODO: figure out why it includes unrelated instances
fields=('name', 'description', 'tags__label', 'attributes__label', 'category__name')
vector = SearchVector(*fields)
query = SearchQuery(keyword)
products_qs = Product.objects.annotate(
rank=SearchRank(vector, query)
).order_by('-rank')
return products_qs

8
products/views.py
View File

@@ -23,7 +23,7 @@ from companies.models import Company
from history.models import HistorySync from history.models import HistorySync
from back_latienda.permissions import IsCreator from back_latienda.permissions import IsCreator
from .utils import extract_search_filters, find_related_products, alt_find_related_products, alt_rank_find_related_products from .utils import extract_search_filters, find_related_products_v1, find_related_products_v2, alt_rank_find_related_products
from utils.tag_serializers import TaggitSerializer from utils.tag_serializers import TaggitSerializer
from utils.tag_filters import ProductTagFilter from utils.tag_filters import ProductTagFilter
@@ -155,9 +155,9 @@ def product_search(request):
chunks = query_string.split(' ') chunks = query_string.split(' ')
for chunk in chunks: for chunk in chunks:
# products_qs = find_related_products(chunk) products_qs = find_related_products_v1(chunk)
# products_qs = alt_find_related_products(chunk) # products_qs = find_related_products_v2(chunk)
products_qs = alt_rank_find_related_products(chunk) # products_qs = alt_rank_find_related_products(chunk)
for instance in products_qs: for instance in products_qs:
result_set.add(instance) result_set.add(instance)