An-DJ commented on PR #1885:
URL: https://github.com/apache/fury/pull/1885#issuecomment-2453037302
@chaokunyang This UT is strange.
```
@pytest.mark.parametrize("language", [Language.XLANG, Language.PYTHON])
def test_array_serializer(language):
fury = Fury(language=language, ref_tracking=True,
require_class_registration=False)
for typecode in PyArraySerializer.typecode_dict.keys():
arr = array.array(typecode, list(range(10)))
# additional code to print array attribute
print(arr.itemsize, arr.typecode)
# end
assert ser_de(fury, arr) == arr
for dtype in Numpy1DArraySerializer.dtypes_dict.keys():
arr = np.array(list(range(10)), dtype=dtype)
new_arr = ser_de(fury, arr)
assert np.array_equal(new_arr, arr)
np.testing.assert_array_equal(new_arr, arr)
```
I test it on Ubuntu 20.04 and Windows 10, but there are different result:
```
# Ubuntu
pyfury/tests/test_serializer.py::test_array_serializer[Language.XLANG] 2 h
4 i
8 l
4 f
8 d
PASSED
pyfury/tests/test_serializer.py::test_array_serializer[Language.PYTHON] 2 h
4 i
8 l
4 f
8 d
PASSED
```
```
# Windows
=================== 1 failed, 1 passed, 3 warnings in 0.88s
===================
FAILED [ 50%]
2 h
4 i
4 l
```
The point is that `l` type could be 4 or 8 bit on different platform.
In addition, in `_util.pyx`, there are also failed converted between `const
int64_t` and `long`:
```
cdef inline uint8_t* get_address(v):
view = memoryview(v)
cdef str dtype = view.format
cdef:
# ...
const int64_t[:] signed_long_data
# ...
uint8_t* ptr
if dtype == "b":
signed_char_data = v
ptr = <uint8_t*>(&signed_char_data[0])
elif dtype == "l": # here
signed_long_data = v
ptr = <uint8_t*>(&signed_long_data[0])
else:
raise Exception(f"Unsupported buffer of type {type(v)} and format
{dtype}")
return ptr
```
Could you plz give me some advice?
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