feat: improving array casting #1865
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FBruzzesi
commented
Jan 25, 2025
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| self: Self, inner: DType | type[DType], width: int | None = None | ||
| self: Self, | ||
| inner: DType | type[DType], | ||
| shape: int | tuple[int, ...] | None = None, |
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This would be a breaking change :(
FBruzzesi
commented
Jan 27, 2025
| @@ -220,7 +224,7 @@ def broadcast_and_extract_dataframe_comparand( | |||
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| if isinstance(other, ArrowSeries): | |||
| len_other = len(other) | |||
| if len_other == 1: | |||
| if len_other == 1 and length != 1: | |||
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Otherwise for list/array types we end up getting the first element
FBruzzesi
commented
Jan 27, 2025
| @@ -111,10 +111,13 @@ def native_to_narwhals_dtype(duckdb_dtype: str, version: Version) -> DType: | |||
| ) | |||
| if match_ := re.match(r"(.*)\[\]$", duckdb_dtype): | |||
| return dtypes.List(native_to_narwhals_dtype(match_.group(1), version)) | |||
| if match_ := re.match(r"(\w+)\[(\d+)\]", duckdb_dtype): | |||
| if match_ := re.match(r"(\w+)((?:\[\d+\])+)", duckdb_dtype): | |||
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Array type in duckdb can also have multiple dimensions, rendering as: INNER[d1][d2][...]
FBruzzesi
commented
Jan 27, 2025
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| duckdb_shape_fmt = "".join(f"[{item}]" for item in dtype.shape) # type: ignore[union-attr] | ||
| while isinstance(dtype.inner, dtypes.Array): # type: ignore[union-attr] | ||
| dtype = dtype.inner # type: ignore[union-attr] | ||
| inner = narwhals_to_native_dtype(dtype.inner, version) # type: ignore[union-attr] | ||
| return f"{inner}{duckdb_shape_fmt}" |
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First creates the shape [d1][d2]... then find the inner type recursively (first being non array)
FBruzzesi
commented
Jan 27, 2025
| @@ -160,7 +160,7 @@ def broadcast_and_extract_dataframe_comparand(index: Any, other: Any) -> Any: | |||
| if isinstance(other, PandasLikeSeries): | |||
| len_other = other.len() | |||
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| if len_other == 1: | |||
| if len_other == 1 and len(index) != 1: | |||
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Similarly as for pyarrow, otherwise for list/array types we end up getting the first element
FBruzzesi
commented
Jan 27, 2025
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| if isinstance(dtype, pyspark_types.ArrayType): # pragma: no cover | ||
| return dtypes.List( | ||
| inner=native_to_narwhals_dtype(dtype.elementType, version=version) | ||
| ) |
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Spark arrays do not have a fixed dimension, so I am converting to a list
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