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Fixed #28194 -- Added support for normalization and cover density to SearchRank.

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Hannes Ljungberg 2020-03-20 22:01:26 +01:00 • committed by Mariusz Felisiak
parent 4ed534758c
commit 0b51a4f894
4 changed files with 106 additions and 3 deletions
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62
tests/postgres_tests/test_search.py
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@ -6,7 +6,7 @@ All text copyright Python (Monty) Pictures. Thanks to sacred-texts.com for the
transcript.
"""
from django.db import connection
from django.db.models import F
from django.db.models import F, Value
from django.test import modify_settings, skipUnlessDBFeature
from . import PostgreSQLSimpleTestCase, PostgreSQLTestCase
@ -449,6 +449,66 @@ class TestRankingAndWeights(GrailTestData, PostgreSQLTestCase):
).filter(rank__gt=0.3)
self.assertSequenceEqual(searched, [self.verse0])
def test_cover_density_ranking(self):
not_dense_verse = Line.objects.create(
scene=self.robin,
character=self.minstrel,
dialogue=(
'Bravely taking to his feet, he beat a very brave retreat. '
'A brave retreat brave Sir Robin.'
)
)
searched = Line.objects.filter(character=self.minstrel).annotate(
rank=SearchRank(
SearchVector('dialogue'),
SearchQuery('brave robin'),
cover_density=True,
),
).order_by('rank', '-pk')
self.assertSequenceEqual(
searched,
[self.verse2, not_dense_verse, self.verse1, self.verse0],
)
def test_ranking_with_normalization(self):
short_verse = Line.objects.create(
scene=self.robin,
character=self.minstrel,
dialogue='A brave retreat brave Sir Robin.',
)
searched = Line.objects.filter(character=self.minstrel).annotate(
rank=SearchRank(
SearchVector('dialogue'),
SearchQuery('brave sir robin'),
# Divide the rank by the document length.
normalization=2,
),
).order_by('rank')
self.assertSequenceEqual(
searched,
[self.verse2, self.verse1, self.verse0, short_verse],
)
def test_ranking_with_masked_normalization(self):
short_verse = Line.objects.create(
scene=self.robin,
character=self.minstrel,
dialogue='A brave retreat brave Sir Robin.',
)
searched = Line.objects.filter(character=self.minstrel).annotate(
rank=SearchRank(
SearchVector('dialogue'),
SearchQuery('brave sir robin'),
# Divide the rank by the document length and by the number of
# unique words in document.
normalization=Value(2).bitor(Value(8)),
),
).order_by('rank')
self.assertSequenceEqual(
searched,
[self.verse2, self.verse1, self.verse0, short_verse],
)
class SearchVectorIndexTests(PostgreSQLTestCase):
def test_search_vector_index(self):