GH-50906: [Python] Reshape 1D tensors to 2D in SparseCSR/CSC matrix conversion by pratyushadk · Pull Request #50907 · apache/arrow

pratyushadk · 2026-08-18T19:06:59Z

Rationale for this change

Calling SparseCSRMatrix.from_tensor() or SparseCSCMatrix.from_tensor() with a 1D Arrow tensor currently raises a NotImplemented error from the C++ layer. A 1D vector has a natural sparse representation as a single-row matrix — the same way scipy treats 1D input to csr_array. This change adds that support at the Python layer by reshaping the tensor to [1, n] before passing it to the C++ backend.

What changes are included in this PR?

python/pyarrow/tensor.pxi

SparseCSRMatrix.from_tensor and SparseCSCMatrix.from_tensor now check if the input tensor is 1D. If so, it is reshaped to [1, n] (a single-row matrix) before being passed to the C++ conversion layer.

python/pyarrow/tests/test_sparse_tensor.py

Two new tests: test_sparse_csr_matrix_from_1d and test_sparse_csc_matrix_from_1d. Each verifies creation from a 1D numpy array (from_dense_numpy), creation from a 1D Arrow tensor (from_tensor), and that the resulting shape is (1, n) with the correct non-zero count.

Are these changes tested?

Yes. The two new tests cover both from_dense_numpy and from_tensor paths for CSR and CSC. The existing sparse tensor test suite is unchanged.

Are there any user-facing changes?

SparseCSRMatrix.from_tensor, SparseCSRMatrix.from_dense_numpy, SparseCSCMatrix.from_tensor, and SparseCSCMatrix.from_dense_numpy now accept 1D tensors and numpy arrays. Previously these raised a NotImplemented error.

GitHub Issue: GH-50906: [Python] Reshape 1D tensors to 2D in SparseCSR/CSC matrix conversion #50906

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github-actions · 2026-08-18T19:07:41Z

⚠️ GitHub issue #50906 has been automatically assigned in GitHub to PR creator.

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rok · 2026-08-24T16:42:17Z

@pratyushadk I've renamed the issue and the PR to reflect that this should be implemented in Python. Let's move the discussion here.
Please update this PR with the Python solution.
Please do not copy paste agent output here. The goal is that you understand what you're doing and that you learn from it.

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pratyushadk · 2026-08-24T17:33:38Z

@rok Thanks for the direction. I'm new to open source and your feedback really helped me understand where the fix actually belongs. Updated the PR with the Python reshape approach. Looking forward to contributing more in the future!

rok · 2026-08-24T17:35:14Z

+def test_sparse_csr_matrix_from_1d():
+    array = np.array([1, 0, 2, 0, 0, 3, 0, 4], dtype=np.int64)
+    tensor = pa.Tensor.from_numpy(array)
+
+    sparse = pa.SparseCSRMatrix.from_dense_numpy(array)
+    assert sparse.shape == (1, 8)
+    assert sparse.non_zero_length == 4
+
+    sparse = pa.SparseCSRMatrix.from_tensor(tensor)
+    assert sparse.shape == (1, 8)
+    assert sparse.non_zero_length == 4
+
+    dense = sparse.to_tensor()
+    assert dense.shape == (1, 8)
+    assert np.array_equal(np.array(dense).ravel(), array)
+
+
+def test_sparse_csc_matrix_from_1d():
+    array = np.array([1, 0, 2, 0, 0, 3, 0, 4], dtype=np.int64)
+    tensor = pa.Tensor.from_numpy(array)
+
+    sparse = pa.SparseCSCMatrix.from_dense_numpy(array)
+    assert sparse.shape == (1, 8)
+    assert sparse.non_zero_length == 4
+
+    sparse = pa.SparseCSCMatrix.from_tensor(tensor)
+    assert sparse.shape == (1, 8)
+    assert sparse.non_zero_length == 4


Please make these parametric so they can be expressed as a single test and compare pyarrow's behavior to scipy's.

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rok · 2026-08-24T17:53:36Z

+        csr_array, csc_array, coo_array, csr_matrix, csc_matrix, coo_matrix
+    )
 except ImportError:
    coo_matrix = None
    csr_matrix = None
+    csc_matrix = None
    csr_array = None
+    csc_array = None


You don't seem to be using csc_array. Please remove the import.

rok · 2026-08-24T17:54:38Z

+    if sc_class is None:
+        pytest.skip('scipy not available')


Elsewhere in this file we use:

@pytest.mark.skipif(not coo_matrix, reason="requires scipy")

as a test decorator. Let's do the same here.

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rok · 2026-08-24T18:29:43Z

 except ImportError:
    coo_matrix = None
    csr_matrix = None
+    csc_matrix = None


Could we use csc_array and avoid even this new import?

Yes, I removed that new import. Thanks for pointing it out!

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rok · 2026-08-24T18:52:30Z

+    sparse_tensor = pa_class.from_tensor(tensor)
+    assert np.array_equal(sparse_tensor.to_tensor().to_numpy(),
+                          scipy_matrix.toarray())


This is redundant too.

rok · 2026-08-24T18:53:28Z

+@pytest.mark.skipif(not csr_matrix, reason="requires scipy")
+@pytest.mark.parametrize('pa_class', [
+    pa.SparseCSRMatrix,
+    pa.SparseCSCMatrix,
+])


We've lost csc and csr scipy objects. Try introducing csr_array and csc_array.

I added csr_array and csc_array coverage by checking the type returned from to_scipy() for both CSR and CSC.

For the 1D dense-input reference, I retained csr_matrix and csc_matrix: csc_array does not accept 1D input (ValueError: CSC arrays don't support 1D input. Use 2D), while csr_array preserves it as 1D (n,). The matrix classes normalize the input to (1, n), matching Arrow's result. I also removed the redundant from_dense_numpy check.

…trix conversion

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pratyushadk requested a review from pitrou as a code owner August 18, 2026 19:07

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pratyushadk force-pushed the GH-50906-csx-1d-tensor-support branch from fd4c81d to 0e17ebe Compare August 24, 2026 16:05

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rok changed the title ~~GH-50906: [C++] Support 1D tensors in SparseCSR/CSC matrix conversion~~ GH-50906: [Python Support 1D tensors in SparseCSR/CSC matrix conversion Aug 24, 2026

rok changed the title ~~GH-50906: [Python Support 1D tensors in SparseCSR/CSC matrix conversion~~ GH-50906: [Python] Support 1D tensors in SparseCSR/CSC matrix conversion Aug 24, 2026

rok changed the title ~~GH-50906: [Python] Support 1D tensors in SparseCSR/CSC matrix conversion~~ GH-50906: [Python] Reshape 1D tensors to 2D in SparseCSR/CSC matrix conversion Aug 24, 2026

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…trix conversion

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pratyushadk commented Aug 18, 2026 •

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