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Confusing ndarray repr: always shows dtype as if in native byteorder #19059
Description
>>> from numpy import array, dtype
# The repr of a dtype object distinguishes non-native byteorder.
>>> dtype('<u2')
dtype('uint16')
>>> dtype('>u2')
dtype('>u2')
# But arrays always use the repr of the native endianness
>>> array([0], dtype='<u2')
array([0], dtype=uint16)
>>> array([0], dtype='>u2')
array([0], dtype=uint16) # <-- this is confusingThis isn't strictly speaking a bug, but using the byteorder-sensitive repr of the dtype instead would make it easier to tell when you have an endianness issue in e.g. this StackOverflow question.
Reacted by Miro Hrončok
Activity
Zac-HD commentedon Aug 22, 2021
@mattip - any tips on where I should be looking to fix this?
Twenty minutes with
grepand examining various__repr__-related code snippets didn't get me anywhere, though I can see from https://github.com/numpy/numpy/blob/main/numpy/core/_dtype.py that it might be tricky if I can't simply have thearrayrepr defer to thedtyperepr...seberg commentedon Mar 14, 2023
Closed by gh-23295