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Fixed #28194 -- Added support for normalization and cover density to SearchRank.
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@ -208,7 +208,10 @@ class SearchRank(Func):
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function = 'ts_rank'
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output_field = FloatField()
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def __init__(self, vector, query, weights=None):
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def __init__(
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self, vector, query, weights=None, normalization=None,
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cover_density=False,
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):
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if not hasattr(vector, 'resolve_expression'):
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vector = SearchVector(vector)
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if not hasattr(query, 'resolve_expression'):
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@ -218,6 +221,12 @@ class SearchRank(Func):
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if not hasattr(weights, 'resolve_expression'):
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weights = Value(weights)
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expressions = (weights,) + expressions
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if normalization is not None:
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if not hasattr(normalization, 'resolve_expression'):
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normalization = Value(normalization)
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expressions += (normalization,)
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if cover_density:
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self.function = 'ts_rank_cd'
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super().__init__(*expressions)
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@ -118,7 +118,7 @@ See :ref:`postgresql-fts-search-configuration` for an explanation of the
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``SearchRank``
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==============
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.. class:: SearchRank(vector, query, weights=None)
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.. class:: SearchRank(vector, query, weights=None, normalization=None, cover_density=False)
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So far, we've returned the results for which any match between the vector and
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the query are possible. It's likely you may wish to order the results by some
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@ -137,6 +137,32 @@ order by relevancy::
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See :ref:`postgresql-fts-weighting-queries` for an explanation of the
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``weights`` parameter.
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Set the ``cover_density`` parameter to ``True`` to enable the cover density
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ranking, which means that the proximity of matching query terms is taken into
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account.
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Provide an integer to the ``normalization`` parameter to control rank
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normalization. This integer is a bit mask, so you can combine multiple
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behaviors::
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>>> from django.db.models import Value
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>>> Entry.objects.annotate(
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... rank=SearchRank(
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... vector,
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... query,
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... normalization=Value(2).bitor(Value(4)),
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... )
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... )
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The PostgreSQL documentation has more details about `different rank
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normalization options`_.
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.. _different rank normalization options: https://www.postgresql.org/docs/current/textsearch-controls.html#TEXTSEARCH-RANKING
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.. versionadded:: 3.1
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The ``normalization`` and ``cover_density`` parameters were added.
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``SearchHeadline``
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==================
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@ -160,6 +160,14 @@ Minor features
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* :lookup:`search` lookup now supports query expressions.
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* The new ``cover_density`` parameter of
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:class:`~django.contrib.postgres.search.SearchRank` allows ranking by cover
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density.
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* The new ``normalization`` parameter of
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:class:`~django.contrib.postgres.search.SearchRank` allows rank
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normalization.
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:mod:`django.contrib.redirects`
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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@ -6,7 +6,7 @@ All text copyright Python (Monty) Pictures. Thanks to sacred-texts.com for the
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transcript.
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"""
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from django.db import connection
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from django.db.models import F
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from django.db.models import F, Value
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from django.test import modify_settings, skipUnlessDBFeature
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from . import PostgreSQLSimpleTestCase, PostgreSQLTestCase
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@ -449,6 +449,66 @@ class TestRankingAndWeights(GrailTestData, PostgreSQLTestCase):
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).filter(rank__gt=0.3)
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self.assertSequenceEqual(searched, [self.verse0])
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def test_cover_density_ranking(self):
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not_dense_verse = Line.objects.create(
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scene=self.robin,
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character=self.minstrel,
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dialogue=(
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'Bravely taking to his feet, he beat a very brave retreat. '
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'A brave retreat brave Sir Robin.'
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)
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)
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searched = Line.objects.filter(character=self.minstrel).annotate(
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rank=SearchRank(
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SearchVector('dialogue'),
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SearchQuery('brave robin'),
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cover_density=True,
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),
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).order_by('rank', '-pk')
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self.assertSequenceEqual(
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searched,
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[self.verse2, not_dense_verse, self.verse1, self.verse0],
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)
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def test_ranking_with_normalization(self):
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short_verse = Line.objects.create(
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scene=self.robin,
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character=self.minstrel,
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dialogue='A brave retreat brave Sir Robin.',
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)
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searched = Line.objects.filter(character=self.minstrel).annotate(
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rank=SearchRank(
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SearchVector('dialogue'),
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SearchQuery('brave sir robin'),
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# Divide the rank by the document length.
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normalization=2,
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),
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).order_by('rank')
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self.assertSequenceEqual(
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searched,
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[self.verse2, self.verse1, self.verse0, short_verse],
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)
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def test_ranking_with_masked_normalization(self):
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short_verse = Line.objects.create(
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scene=self.robin,
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character=self.minstrel,
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dialogue='A brave retreat brave Sir Robin.',
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)
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searched = Line.objects.filter(character=self.minstrel).annotate(
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rank=SearchRank(
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SearchVector('dialogue'),
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SearchQuery('brave sir robin'),
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# Divide the rank by the document length and by the number of
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# unique words in document.
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normalization=Value(2).bitor(Value(8)),
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),
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).order_by('rank')
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self.assertSequenceEqual(
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searched,
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[self.verse2, self.verse1, self.verse0, short_verse],
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)
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class SearchVectorIndexTests(PostgreSQLTestCase):
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def test_search_vector_index(self):
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