8000 BUG: Enforce integer limitation in concatenate by seberg · Pull Request #29231 · numpy/numpy · GitHub
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BUG: Enforce integer limitation in concatenate #29231

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Merged
merged 2 commits into from
Jun 19, 2025
Merged

BUG: Enforce integer limitation in concatenate #29231

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a9e2fd6
BUG: Enforce integer limitation in concatenate
seberg Jun 19, 2025
54ed723
skip 32bit systems
seberg Jun 19, 2025
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11 changes: 9 additions & 2 deletions numpy/_core/src/multiarray/multiarraymodule.c
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Original file line number Diff line number Diff line change
Expand Up @@ -668,10 +668,17 @@ PyArray_ConcatenateInto(PyObject *op,
}

/* Convert the input list into arrays */
narrays = PySequence_Size(op);
if (narrays < 0) {
Py_ssize_t narrays_true = PySequence_Size(op);
if (narrays_true < 0) {
return NULL;
}
else if (narrays_true > NPY_MAX_INT) {
PyErr_Format(PyExc_ValueError,
"concatenate() only supports up to %d arrays but got %zd.",
NPY_MAX_INT, narrays_true);
return NULL;
}
narrays = (int)narrays_true;
arrays = PyArray_malloc(narrays * sizeof(arrays[0]));
if (arrays == NULL) {
PyErr_NoMemory();
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14 changes: 14 additions & 0 deletions numpy/_core/tests/test_shape_base.py
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Original file line number Diff line number Diff line change
@@ -1,3 +1,5 @@
import sys

import pytest

import numpy as np
Expand Down Expand Up @@ -29,6 +31,7 @@
assert_raises,
assert_raises_regex,
)
from numpy.testing._private.utils import requires_memory


class TestAtleast1d:
Expand Down Expand Up @@ -290,6 +293,17 @@ def test_exceptions(self):
# No arrays to concatenate raises ValueError
assert_raises(ValueError, concatenate, ())

@pytest.mark.slow
@pytest.mark.skipif(sys.maxsize < 2**32, reason="only problematic on 64bit platforms")
@requires_memory(2 * np.iinfo(np.intc).max)
def test_huge_list_error(self):
a = np.array([1])
max_int = np.iinfo(np.intc).max
arrs = (a,) * (max_int + 1)
msg = fr"concatenate\(\) only supports up to {max_int} arrays but got {max_int + 1}."
with pytest.raises(ValueError, match=msg):
np.concatenate(arrs)

def test_concatenate_axis_None(self):
a = np.arange(4, dtype=np.float64).reshape((2, 2))
b = list(range(3))
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