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feat(python): Use a contravariant typevar for df.cast #19499

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feat(python): Use a contravariant typevar for df.cast #19499

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1 change: 1 addition & 0 deletions py-polars/polars/_typing.py
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Original file line number Diff line number Diff line change
Expand Up @@ -92,6 +92,7 @@ def __arrow_c_stream__(self, requested_schema: object | None = None) -> object:
# selector type, and related collection/sequence
SelectorType: TypeAlias = "_selector_proxy_"
ColumnNameOrSelector: TypeAlias = Union[str, SelectorType]
ColumnNameOrSelectorOrDataType = TypeVar("ColumnNameOrSelectorOrDataType", bound=ColumnNameOrSelector | PolarsDataType, contravariant=True)

# User-facing string literal types
# The following all have an equivalent Rust enum with the same name
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3 changes: 2 additions & 1 deletion py-polars/polars/dataframe/frame.py
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Expand Up @@ -139,6 +139,7 @@
ClosedInterval,
ColumnFormatDict,
ColumnNameOrSelector,
ColumnNameOrSelectorOrDataType,
ColumnTotalsDefinition,
ColumnWidthsDefinition,
ComparisonOperator,
Expand Down Expand Up @@ -7620,7 +7621,7 @@ def drop_in_place(self, name: str) -> Series:
def cast(
self,
dtypes: (
Mapping[ColumnNameOrSelector | PolarsDataType, PolarsDataType]
Mapping[ColumnNameOrSelectorOrDataType, PolarsDataType]
| PolarsDataType
),
*,
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3 changes: 2 additions & 1 deletion py-polars/polars/lazyframe/frame.py
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Expand Up @@ -99,6 +99,7 @@
AsofJoinStrategy,
ClosedInterval,
ColumnNameOrSelector,
ColumnNameOrSelectorOrDataType,
CsvQuoteStyle,
EngineType,
ExplainFormat,
Expand Down Expand Up @@ -2932,7 +2933,7 @@ def cache(self) -> LazyFrame:
def cast(
self,
dtypes: (
Mapping[ColumnNameOrSelector | PolarsDataType, PolarsDataType]
Mapping[ColumnNameOrSelectorOrDataType, PolarsDataType]
| PolarsDataType
),
*,
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7 changes: 7 additions & 0 deletions py-polars/tests/unit/operations/test_cast.py
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Expand Up @@ -674,6 +674,13 @@ def test_cast_consistency() -> None:
).to_dict(as_series=False) == {"a": [0.0], "b": ["0.0"], "c": ["0.0"]}


def test_cast_schema() -> None:
schema = pl.Schema({"v": pl.UInt8()})
df = pl.DataFrame({"v": [1, 2, 3]}).cast(schema)
assert df.collect_schema() == schema
assert df["v"].eq(pl.Series("v", [1, 2, 3], dtype=pl.UInt8())).all()


def test_cast_int_to_string_unsets_sorted_flag_19424() -> None:
s = pl.Series([1, 2]).set_sorted()
assert s.flags["SORTED_ASC"]
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