pola-rs/polars · error · NotImplementedError

unsupported data type: {dtype!r}

Error message

unsupported data type: {dtype!r}

What it means

On the import side, dtype_to_polars_dtype maps a protocol dtype tuple (kind, bit_width, format_string, endianness) to a Polars dtype through dtype_to_polars_dtype_map[kind][bit_width]. If the kind is recognized but the bit width is absent from the map - e.g. FLOAT16, or uncommon integer widths - the KeyError is re-raised as NotImplementedError.

Source

Thrown at py-polars/src/polars/interchange/utils.py:128

    },
    DtypeKind.STRING: {8: String},
}


def dtype_to_polars_dtype(dtype: Dtype) -> PolarsDataType:
    """Convert interchange protocol data type to Polars data type."""
    kind, bit_width, format_str, _ = dtype

    if kind == DtypeKind.DATETIME:
        return _temporal_dtype_to_polars_dtype(format_str, dtype)
    elif kind == DtypeKind.CATEGORICAL:
        return Enum

    try:
        return dtype_to_polars_dtype_map[kind][bit_width]
    except KeyError as exc:
        msg = f"unsupported data type: {dtype!r}"
        raise NotImplementedError(msg) from exc


def _temporal_dtype_to_polars_dtype(format_str: str, dtype: Dtype) -> PolarsDataType:
    if (match := re.fullmatch(r"ts([mun]):(.*)", format_str)) is not None:
        time_unit = match.group(1) + "s"
        time_zone = match.group(2) or None
        return Datetime(
            time_unit=time_unit,  # type: ignore[arg-type]
            time_zone=time_zone,
        )
    elif format_str == "tdD":
        return Date
    elif format_str == "ttu":
        return Time
    elif (match := re.fullmatch(r"tD([mun])", format_str)) is not None:
        time_unit = match.group(1) + "s"
        return Duration(time_unit=time_unit)  # type: ignore[arg-type]

View on GitHub (pinned to df599052da)

Solutions

1. Have the producer widen/cast exotic columns to supported widths (float16 -> float32, odd ints -> Int64)
2. Upgrade polars in case the dtype was added in a newer release
3. Skip or transform the offending column upstream before interchange conversion

from polars.interchange.utils import dtype_to_polars_dtype

def dtype_importable(dtype) -> bool:
    try:
        dtype_to_polars_dtype(dtype)
    except NotImplementedError:
        return False
    return True

try:
    out = pl.from_dataframe(df)
except NotImplementedError as e:
    if 'unsupported data type' in str(e):
        raise ValueError(
            'producer emits a dtype width polars cannot import '
            '(e.g. float16); widen columns at the source'
        ) from e
    raise

When it happens

Trigger: A producer exposing columns with dtype kinds/widths polars does not carry in its map: 16-bit floats, exotic integer widths, or new kinds added by a newer protocol revision.

Common situations: ML pipelines that store float16 tensors exposed as dataframes; custom producers; producer upgrades that start emitting widths polars has not mapped.

Related errors

• unsupported data type: {dtype}
• non-dictionary categoricals are not yet supported
• non-string categories are not supported
• unsupported null type: {null_type!r}
• data type {dtype!r} not supported by the interchange protoco

AI-assisted analysis of pola-rs/polars@df599052da (2026-08-16). Data as JSON: /api/errors/ddefb6bf02e4ab5f. Report an issue: GitHub.