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pybind11: implicitly convert NumPy integer scalars
The current integer caster was unnecessarily strict and rejected various kinds of NumPy integer types when calling C++ functions expecting normal integers. This relaxes the current behavior.
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@ -443,7 +443,14 @@ public:
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(std::is_integral<T>::value && sizeof(py_type) != sizeof(T) &&
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(py_value < (py_type) std::numeric_limits<T>::min() ||
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py_value > (py_type) std::numeric_limits<T>::max()))) {
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#if PY_VERSION_HEX < 0x03000000
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bool type_error = PyErr_ExceptionMatches(PyExc_SystemError);
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#else
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bool type_error = PyErr_ExceptionMatches(PyExc_TypeError);
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#endif
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PyErr_Clear();
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if (type_error && PyNumber_Check(src.ptr()))
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return load(object(PyNumber_Long(src.ptr()), true), false);
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return false;
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}
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@ -124,4 +124,6 @@ test_initializer numpy_array([](py::module &m) {
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return py::array_t<int>({2}, {4}, a.data, obj);
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}
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);
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sm.def("function_taking_uint64", [](uint64_t){ });
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});
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@ -238,3 +238,10 @@ def test_numpy_view(capture):
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assert capture == """
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~ArrayClass()
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"""
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@pytest.requires_numpy
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def test_cast_numpy_int64_to_uint64():
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from pybind11_tests.array import function_taking_uint64
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function_taking_uint64(123)
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function_taking_uint64(np.uint64(123))
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