Fixed error with SciPy sparse arrays with zeros

Author: ankane

pgvector/sparsevec.py

@@ -119,14 +119,14 @@ def _from_sparse(self, arr: sparray | spmatrix, /) -> None:
         else:
             indices = value.col.tolist()
 
-        # spipy 1.12+
-        if hasattr(value, 'has_canonical_format') and value.has_canonical_format:
-            self._indices = indices
-            self._values = [float(v) for v in value.data]
-        else:
-            elements = sorted(zip(indices, value.data))
-            self._indices = [v[0] for v in elements]
-            self._values = [float(v[1]) for v in elements]
+        elements = [v for v in zip(indices, value.data) if v[1] != 0]
+
+        # has_canonical_format added in spipy 1.12+
+        if not hasattr(value, 'has_canonical_format') or not value.has_canonical_format:
+            elements.sort()
+
+        self._indices = [v[0] for v in elements]
+        self._values = [float(v[1]) for v in elements]
 
     def _from_dense(self, value: list[float] | ndarray, /) -> None:
         self._dim = len(value)

tests/test_sparse_vector.py

@@ -54,7 +54,7 @@ def test_coo_array(self) -> None:
         if np is None or sparse is None:
             pytest.skip('NumPy and SciPy required')
 
-        arr = sparse.coo_array(([3, 1, 2], ([4, 0, 2],)), shape=(6,))
+        arr = sparse.coo_array(([2, 3, 1, 0], ([2, 4, 0, 3],)), shape=(6,))
         vec = SparseVector(arr)
         assert vec.to_list() == [1, 0, 2, 0, 3, 0]
         assert vec.indices() == [0, 2, 4]