diff options
| -rw-r--r-- | numpy/core/src/multiarray/convert_datatype.c | 6 | ||||
| -rw-r--r-- | numpy/core/tests/test_dtype.py | 10 |
2 files changed, 15 insertions, 1 deletions
diff --git a/numpy/core/src/multiarray/convert_datatype.c b/numpy/core/src/multiarray/convert_datatype.c index ce2c73a7a..bc8a3bf88 100644 --- a/numpy/core/src/multiarray/convert_datatype.c +++ b/numpy/core/src/multiarray/convert_datatype.c @@ -1691,8 +1691,12 @@ PyArray_ResultType( all_DTypes[i_all] = &PyArray_PyComplexAbstractDType; } else { - /* N.B.: Could even be an object dtype here for large ints */ + /* This could even be an object dtype here for large ints */ all_DTypes[i_all] = &PyArray_PyIntAbstractDType; + if (PyArray_TYPE(arrs[i]) != NPY_LONG) { + /* Not a "normal" scalar, so we cannot avoid the legacy path */ + all_pyscalar = 0; + } } Py_INCREF(all_DTypes[i_all]); /* diff --git a/numpy/core/tests/test_dtype.py b/numpy/core/tests/test_dtype.py index 32e2c6842..b37bded73 100644 --- a/numpy/core/tests/test_dtype.py +++ b/numpy/core/tests/test_dtype.py @@ -1346,6 +1346,16 @@ class TestPromotion: match=r".* no common DType exists for the given inputs"): np.result_type(1j, rational(1, 2)) + @pytest.mark.parametrize("val", [2, 2**32, 2**63, 2**64, 2*100]) + def test_python_integer_promotion(self, val): + # If we only path scalars (mainly python ones!), the result must take + # into account that the integer may be considered int32, int64, uint64, + # or object depending on the input value. So test those paths! + expected_dtype = np.result_type(np.array(val).dtype, np.array(0).dtype) + assert np.result_type(val, 0) == expected_dtype + # For completeness sake, also check with a NumPy scalar as second arg: + assert np.result_type(val, np.int8(0)) == expected_dtype + @pytest.mark.parametrize(["other", "expected"], [(1, rational), (1., np.float64)]) def test_float_int_pyscalar_promote_rational(self, other, expected): |