DEPS: Update reprs with numpy NEP51 scalar repr #54268
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mroeschke
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| @@ -5250,7 +5250,8 @@ def _raise_scalar_data_error(cls, data): | |||
| # in order to keep mypy happy | |||
| raise TypeError( | |||
| f"{cls.__name__}(...) must be called with a collection of some " | |||
| f"kind, {repr(data)} was passed" | |||
| f"kind, {repr(data) if not isinstance(data, np.generic) else str(data)} " | |||
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does str work unconditionally?
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Yeah according to the linked PR seems so
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Oh sorry, str works unconditionally for numpy scalars but repr vs str would make this display differently for other scalars e.g. python strings
pandas/core/arrays/masked.py
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| @@ -160,6 +161,9 @@ def _empty(cls, shape: Shape, dtype: ExtensionDtype): | |||
| ) | |||
| return result | |||
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| def _formatter(self, boxed: bool = False) -> Callable[[Any], str | None]: | |||
| return super()._formatter(boxed=True) | |||
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we're ignoring the boxed keyword?
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Yeah since I think we'll need to always return str given the NEP 51 change. Actually probably just simpler to return str here
| name = type(self).__name__ | ||
| repr_str = f"{name}({repr(left)}, {repr(right)}, closed={repr(self.closed)})" | ||
| repr_str = f"{name}({disp(left)}, {disp(right)}, closed={repr(self.closed)})" |
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maybe the thing to do is unpack numpy scalars at an earlier stage?
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But we should still store numpy scalars for left/right on Interval right?
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i was thinking store native scalars
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Hmm might make sense, not sure if there's any larger ramifications of that chance. Might be better to experiment in a follow up?
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This will get the CI back to green? |
Yup. I guess we can merge to get back to green and follow up if needed. |
xref numpy/numpy#22449