diff options
Diffstat (limited to 'numpy')
| -rw-r--r-- | numpy/core/tests/test_regression.py | 7 | ||||
| -rw-r--r-- | numpy/ctypeslib.py | 15 |
2 files changed, 16 insertions, 6 deletions
diff --git a/numpy/core/tests/test_regression.py b/numpy/core/tests/test_regression.py index c5289f6ac..ce0df2695 100644 --- a/numpy/core/tests/test_regression.py +++ b/numpy/core/tests/test_regression.py @@ -2500,3 +2500,10 @@ class TestRegression(object): t = T() #gh-13659, would raise in broadcasting [x=t for x in result] np.array([t]) + + def test_to_ctypes(self): + #gh-14214 + arr = np.zeros((2 ** 31 + 1,), 'b') + assert(arr.size * arr.itemsize > 2 ** 31) + c_arr = np.ctypeslib.as_ctypes(arr) + assert_equal(c_arr._length_, arr.size) diff --git a/numpy/ctypeslib.py b/numpy/ctypeslib.py index e49f8394f..e7c5c78d3 100644 --- a/numpy/ctypeslib.py +++ b/numpy/ctypeslib.py @@ -92,11 +92,11 @@ else: # Adapted from Albert Strasheim def load_library(libname, loader_path): """ - It is possible to load a library using + It is possible to load a library using >>> lib = ctypes.cdll[<full_path_name>] # doctest: +SKIP But there are cross-platform considerations, such as library file extensions, - plus the fact Windows will just load the first library it finds with that name. + plus the fact Windows will just load the first library it finds with that name. NumPy supplies the load_library function as a convenience. Parameters @@ -110,12 +110,12 @@ else: Returns ------- ctypes.cdll[libpath] : library object - A ctypes library object + A ctypes library object Raises ------ OSError - If there is no library with the expected extension, or the + If there is no library with the expected extension, or the library is defective and cannot be loaded. """ if ctypes.__version__ < '1.0.1': @@ -535,7 +535,10 @@ if ctypes is not None: if readonly: raise TypeError("readonly arrays unsupported") - dtype = _dtype((ai["typestr"], ai["shape"])) - result = as_ctypes_type(dtype).from_address(addr) + # can't use `_dtype((ai["typestr"], ai["shape"]))` here, as it overflows + # dtype.itemsize (gh-14214) + ctype_scalar = as_ctypes_type(ai["typestr"]) + result_type = _ctype_ndarray(ctype_scalar , ai['shape']) + result = result_type.from_address(addr) result.__keep = obj return result |