Improved sparsevec tests [skip ci]

Author: ankane

pgvector/utils/sparsevec.py

@@ -108,6 +108,7 @@ def from_binary(cls, value):
         dim, nnz, unused = unpack_from('>iii', value)
         indices = unpack_from(f'>{nnz}i', value, 12)
         values = unpack_from(f'>{nnz}f', value, 12 + nnz * 4)
+        # TODO convert indices and values to lists in 0.4.0
         return cls._from_parts(int(dim), indices, values)
 
     @classmethod

tests/test_psycopg.py

@@ -110,12 +110,19 @@ def test_sparsevec(self):
     def test_sparsevec_binary_format(self):
         embedding = SparseVector([1.5, 0, 2, 0, 3, 0])
         res = conn.execute('SELECT %b::sparsevec', (embedding,), binary=True).fetchone()[0]
+        assert res.dimensions() == 6
+        # TODO convert indices and values to lists in 0.4.0
+        assert res.indices() == (0, 2, 4)
+        assert res.values() == (1.5, 2, 3)
         assert res.to_list() == [1.5, 0, 2, 0, 3, 0]
         assert np.array_equal(res.to_numpy(), np.array([1.5, 0, 2, 0, 3, 0]))
 
     def test_sparsevec_text_format(self):
         embedding = SparseVector([1.5, 0, 2, 0, 3, 0])
         res = conn.execute('SELECT %t::sparsevec', (embedding,)).fetchone()[0]
+        assert res.dimensions() == 6
+        assert res.indices() == [0, 2, 4]
+        assert res.values() == [1.5, 2, 3]
         assert res.to_list() == [1.5, 0, 2, 0, 3, 0]
         assert np.array_equal(res.to_numpy(), np.array([1.5, 0, 2, 0, 3, 0]))