Now overloads with ambiguous self are handled properly, refs #11347
#17239
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Diff from mypy_primer, showing the effect of this PR on open source code: pandas (https://github.com/pandas-dev/pandas)
+ pandas/core/dtypes/dtypes.py:1173: error: Unused "type: ignore" comment [unused-ignore]
+ pandas/core/nanops.py:519: error: Unused "type: ignore" comment [unused-ignore]
+ pandas/core/nanops.py:534: error: Unused "type: ignore" comment [unused-ignore]
+ pandas/core/nanops.py:575: error: Unused "type: ignore" comment [unused-ignore]
+ pandas/core/nanops.py:590: error: Unused "type: ignore" comment [unused-ignore]
+ pandas/core/nanops.py:1145: error: Unused "type: ignore" comment [unused-ignore]
+ pandas/core/nanops.py:1191: error: Unused "type: ignore" comment [unused-ignore]
+ pandas/core/missing.py:258: error: Unused "type: ignore" comment [unused-ignore]
+ pandas/io/formats/format.py:1573: error: Item "Sequence[float]" of "ndarray[Any, Any] | Sequence[float]" has no attribute "round" [union-attr]
+ pandas/io/formats/format.py:1584: error: No overload variant of "__getitem__" of "Sequence" matches argument type "ndarray[Any, dtype[bool_]]" [call-overload]
+ pandas/io/formats/format.py:1584: note: Possible overload variants:
+ pandas/io/formats/format.py:1584: note: def __getitem__(self, int, /) -> float
+ pandas/io/formats/format.py:1584: note: def __getitem__(self, slice, /) -> Sequence[float]
+ pandas/io/formats/format.py:1586: error: No overload variant of "__getitem__" of "Sequence" matches argument type "ndarray[Any, dtype[bool_]]" [call-overload]
+ pandas/io/formats/format.py:1586: note: Possible overload variants:
+ pandas/io/formats/format.py:1586: note: def __getitem__(self, int, /) -> float
+ pandas/io/formats/format.py:1586: note: def __getitem__(self, slice, /) -> Sequence[float]
tornado (https://github.com/tornadoweb/tornado)
+ tornado/test/iostream_test.py:820: error: Unused "type: ignore" comment [unused-ignore]
pandas-stubs (https://github.com/pandas-dev/pandas-stubs)
+ tests/test_timefuncs.py:1213: error: Expression is of type "Any", not "TimestampSeries" [assert-type]
+ tests/test_series.py:1458: error: Expression is of type "Any", not "DataFrame" [assert-type]
+ tests/test_series.py:1464: error: Expression is of type "Any", not "DataFrame" [assert-type]
+ tests/test_series.py:3187: error: Expression is of type "Any", not "Series[type[object]]" [assert-type]
+ tests/test_plotting.py:598: error: Expression is of type "Any", not "Series[Any]" [assert-type]
+ tests/test_plotting.py:602: error: Expression is of type "Any", not "Axes" [assert-type]
+ tests/test_indexes.py:360: error: Expression is of type "IntervalIndex[Any]", not "IntervalIndex[Interval[int]]" [assert-type]
+ tests/test_indexes.py:395: error: Expression is of type "IntervalIndex[Any]", not "IntervalIndex[Interval[int]]" [assert-type]
+ tests/test_indexes.py:403: error: Expression is of type "IntervalIndex[Any]", not "IntervalIndex[Interval[float]]" [assert-type]
+ tests/test_indexes.py:447: error: Expression is of type "IntervalIndex[Any]", not "IntervalIndex[Interval[int]]" [assert-type]
+ tests/test_indexes.py:490: error: Expression is of type "IntervalIndex[Any]", not "IntervalIndex[Interval[int]]" [assert-type]
+ tests/test_indexes.py:506: error: Expression is of type "IntervalIndex[Any]", not "IntervalIndex[Interval[int]]" [assert-type]
+ tests/test_indexes.py:517: error: Expression is of type "IntervalIndex[Any]", not "IntervalIndex[Interval[float]]" [assert-type]
+ tests/test_indexes.py:555: error: Expression is of type "IntervalIndex[Any]", not "IntervalIndex[Interval[int]]" [assert-type]
+ tests/test_indexes.py:610: error: Expression is of type "IntervalIndex[Any]", not "IntervalIndex[Interval[int]]" [assert-type]
mkdocs (https://github.com/mkdocs/mkdocs)
+ mkdocs/tests/config/config_options_tests.py:1679: error: Expression is of type "Any", not "dict[str, dict[Any, Any]]" [assert-type]
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@flaeppe can you please analyze the output? |
sobolevn
reviewed
May 13, 2024
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Yes, it's just a rebase of your old PR. I've only tried to check the pandas changes, but I'm suspecting that now getting the following changes is incorrect: + pandas/io/formats/format.py:1573: error: Item "Sequence[float]" of "ndarray[Any, Any] | Sequence[float]" has no attribute "round" [union-attr]
+ pandas/io/formats/format.py:1584: error: No overload variant of "__getitem__" of "Sequence" matches argument type "ndarray[Any, dtype[bool_]]" [call-overload]
+ pandas/io/formats/format.py:1584: note: Possible overload variants:
+ pandas/io/formats/format.py:1584: note: def __getitem__(self, int, /) -> float
+ pandas/io/formats/format.py:1584: note: def __getitem__(self, slice, /) -> Sequence[float]
+ pandas/io/formats/format.py:1586: error: No overload variant of "__getitem__" of "Sequence" matches argument type "ndarray[Any, dtype[bool_]]" [call-overload]
+ pandas/io/formats/format.py:1586: note: Possible overload variants:
+ pandas/io/formats/format.py:1586: note: def __getitem__(self, int, /) -> float
+ pandas/io/formats/format.py:1586: note: def __getitem__(self, slice, /) -> Sequence[float]It's within the following function and stems from this line: https://github.com/pandas-dev/pandas/blob/283a2dcb2f91db3452a9d2ee299632a109b224f4/pandas/io/formats/format.py#L1561 I haven't been able to find a reproducible case but essentially what is happening here is that there's a narrowing of a union, via a helper similar to something like this: def helper(val: Any) -> np.ndarray: ...
percentiles: np.ndarray | Sequence[float]
percentiles = helper(percentiles)
reveal_type(percentiles) # Revealed type is "np.ndarray | Sequence[float]"There's a couple of Here's a related issue and comments: #2008 (comment) |
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Correct me if I'm wrong, but if I'm reading the comments in #2008 and the Always narrow types section in #16472 (comment) correctly I don't think issue mentioned in the above comment #17239 (comment) is caused by the changes here. |
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Haven't looked into the PR yet, but I'm wondering if this now complies with the recently added chapter in the spec (see python/typing#1667) |
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self-annotated methods #11347selfare handled properly #11366This is simply a rebase of #11366 (See #11366 (comment) CC @sobolevn), I kept the changes intact.