working on ranked search results

This commit is contained in:
Sam
2021-02-18 13:08:23 +00:00
parent 20b9c395c2
commit 47633c889d
3 changed files with 25 additions and 10 deletions

View File

@@ -463,11 +463,13 @@ class ProductSearchTest(TestCase):
expected_instances = [
self.factory(tags="lunares/blancos",description="zapatos verdes"),
# TODO: workaround vectorized search not liking nested tags
# self.factory(tags="colores/rojos, tono/brillante"),
self.factory(tags="colores, rojos"),
self.factory(tags="colores/rojos, tono/brillante"),
# self.factory(tags="colores, rojos"),
self.factory(tags="lunares/azules", description="zapatos rojos"),
self.factory(tags="lunares/rojos", description="zapatos"),
self.factory(attributes='"zapatos de campo", tono/oscuro'),
# TODO: workaround multi-word tags
# self.factory(attributes='zapatos, "zapatos de campo", tono/oscuro'),
]
unexpected_instances = [
self.factory(description="chanclas"),
@@ -485,8 +487,11 @@ class ProductSearchTest(TestCase):
# load response data
payload = response.json()
# check for object creation
import ipdb; ipdb.set_trace()
self.assertEquals(len(payload['products']), len(expected_instances))
# check ids
for i in range(len(payload['products'])):
self.assertTrue(payload['products'][i]['id'] == expected_instances[i].id)
# check for filters
self.assertNotEquals([], payload['filters']['singles'])
self.assertTrue(len(payload['filters']) >= 2 )