57 lines
1.7 KiB
Python
57 lines
1.7 KiB
Python
import sqlalchemy as sa
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from sqlalchemy_utils import aggregated, TSVectorType
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from tests import TestCase
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def tsvector_reduce_concat(vectors):
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return sa.sql.expression.cast(
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sa.func.coalesce(
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sa.func.array_to_string(sa.func.array_agg(vectors), ' ')
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),
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TSVectorType
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)
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class TestSearchVectorAggregates(TestCase):
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dns = 'postgres://postgres@localhost/sqlalchemy_utils_test'
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def create_models(self):
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class Catalog(self.Base):
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__tablename__ = 'catalog'
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id = sa.Column(sa.Integer, primary_key=True)
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name = sa.Column(sa.Unicode(255))
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@aggregated('products', sa.Column(TSVectorType))
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def product_search_vector(self):
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return tsvector_reduce_concat(
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sa.func.to_tsvector(Product.name)
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)
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products = sa.orm.relationship('Product', backref='catalog')
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class Product(self.Base):
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__tablename__ = 'product'
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id = sa.Column(sa.Integer, primary_key=True)
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name = sa.Column(sa.Unicode(255))
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price = sa.Column(sa.Numeric)
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catalog_id = sa.Column(sa.Integer, sa.ForeignKey('catalog.id'))
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self.Catalog = Catalog
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self.Product = Product
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def test_assigns_aggregates_on_insert(self):
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catalog = self.Catalog(
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name=u'Some catalog'
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)
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self.session.add(catalog)
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self.session.commit()
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product = self.Product(
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name=u'Product XYZ',
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catalog=catalog
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)
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self.session.add(product)
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self.session.commit()
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self.session.refresh(catalog)
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assert catalog.product_search_vector == "'product':1 'xyz':2"
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