Fixed error with unordered SciPy sparse arrays - resolves #160

Co-authored-by: Christopher Krah <chris@plexito.de>

Author: ankane

CHANGELOG.md

@@ -1,5 +1,6 @@
 ## 0.5.1 (unreleased)
 
+- Fixed error with unordered SciPy sparse arrays
 - Fixed error with `Bit` constructor for NumPy 1.24-1.26
 
 ## 0.5.0 (2026-07-06)

pgvector/sparsevec.py

@@ -115,10 +115,14 @@ def _from_sparse(self, arr: sparray | spmatrix, /) -> None:
 
         if hasattr(value, 'coords'):
             # scipy 1.13+
-            self._indices = value.coords[-1].tolist()
+            indices = value.coords[-1].tolist()
         else:
-            self._indices = value.col.tolist()
-        self._values = [float(v) for v in value.data]
+            indices = value.col.tolist()
+
+        elements = sorted(zip(indices, value.data))
+
+        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(np.array([1, 0, 2, 0, 3, 0]))
+        arr = sparse.coo_array(([3, 1, 2], ([4, 0, 2],)), shape=(6,))
         vec = SparseVector(arr)
         assert vec.to_list() == [1, 0, 2, 0, 3, 0]
         assert vec.indices() == [0, 2, 4]