8000 ENH: fix printing structured dtypes with a non-legacy dtype member by ngoldbaum · Pull Request #24758 · numpy/numpy · GitHub
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ENH: fix printing structured dtypes with a non-legacy dtype member #24758

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Merged
merged 2 commits into from
Sep 26, 2023
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ENH: fix printing structured dtypes with a non-legacy dtype member #24758

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ENH: fix printing structured dtypes with a non-legacy dtype member
ngoldbaum Sep 20, 2023
d50991b
MAINT: use _legacy attribute to check for legacy dtype
ngoldbaum Sep 25, 2023
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6 changes: 5 additions & 1 deletion numpy/core/_dtype.py
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Original file line number Diff line number Diff line change
Expand Up @@ -126,6 +126,9 @@ def _scalar_str(dtype, short):
else:
return "'%sU%d'" % (byteorder, dtype.itemsize / 4)

elif not type(dtype)._legacy:
return f"'{byteorder}{type(dtype).__name__}{dtype.itemsize * 8}'"
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Yes, I am fine with this, although don't have _legacy now to do this?

I am confused about this type of string, though, can't we use the repr? {byteorder}{TypeName}{itemsize} doesn't need to be much of a reasonable repr?

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I'm fine with just using the repr here and in the other path, I agree that the bitsize isn't particularly useful and if someone thinks it's worth including they can include it in the repr. Mind if I take care of that in a followup?

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Sure, I am fine with that, since its all in flux somewhat alpha stage anyway. Thanks @ngoldbaum lets just put it in.


# unlike the other types, subclasses of void are preserved - but
# historically the repr does not actually reveal the subclass
elif issubclass(dtype.type, np.void):
Expand Down Expand Up @@ -350,8 +353,9 @@ def _name_get(dtype):
# user dtypes don't promise to do anything special
return dtype.type.__name__

if dtype.kind == '\x00':
if not type(dtype)._legacy:
name = type(dtype).__name__

elif issubclass(dtype.type, np.void):
# historically, void subclasses preserve their name, eg `record64`
name = dtype.type.__name__
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6 changes: 6 additions & 0 deletions numpy/core/tests/test_custom_dtypes.py
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Expand Up @@ -51,6 +51,12 @@ def test_repr(self):
def test_dtype_name(self):
assert SF(1.).name == "_ScaledFloatTestDType64"

def test_sfloat_structured_dtype_printing(self):
dt = np.dtype([("id", int), ("value", SF(0.5))])
# repr of structured dtypes need special handling because the
# implementation bypasses the object repr
assert "('value', '_ScaledFloatTestDType64')" in repr(dt)
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@seberg seberg Sep 25, 2023 •
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A bit confusing, I woul;d have thout if the test above does SF(1.).name == "_ScaledFloatTestDType64" we get _ScaledFloatTestDType6464 here :).

EDIT: Ahh, nvm. I guess this and the above are actually very similar in what they use/define as "name". Hmmmm...


@pytest.mark.parametrize("scaling", [1., -1., 2.])
def test_sfloat_from_float(self, scaling):
a = np.array([1., 2., 3.]).astype(dtype=SF(scaling))
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