pola-rs/polars · error · ValueError

`dtype` must be of type

Error message

`dtype` must be of type {Date, Datetime, Time}

What it means

Expr.str.strptime() dispatches on `dtype`: Date calls to_date, Datetime calls to_datetime, Time calls to_time. Any other dtype (String, Int64, etc.) has no string-parsing path, so Polars raises this ValueError. It means you passed a dtype the method cannot convert to.

Solutions

1. Pass pl.Date, pl.Datetime, or pl.Time as dtype.
2. If you need a different target type, parse to Date/Datetime first, then cast with .cast(...).
3. Fix the variable feeding dtype so it resolves to one of the three temporal dtypes.

Example fix

// before
df.select(pl.col('s').str.strptime(pl.Utf8, '%Y-%m-%d'))
// after
df.select(pl.col('s').str.strptime(pl.Date, '%Y-%m-%d'))

if dtype not in (pl.Date, pl.Datetime, pl.Time):
    raise ValueError(f'dtype must be Date/Datetime/Time, got {dtype}')

def is_temporal_dtype(dtype) -> bool:
    return dtype in (pl.Date, pl.Datetime, pl.Time)

try:
    expr = pl.col('s').str.strptime(dtype, fmt)
except ValueError:
    expr = pl.col('s').str.strptime(pl.Datetime, fmt)

When it happens

Trigger: Calling Expr.str.strptime(pl.Int64, fmt) or strptime(pl.Utf8, ...) — any dtype outside {Date, Datetime, Time}, often from parameterizing dtype generically.

Common situations: Passing the source column dtype by mistake instead of the target dtype; dtype chosen via config/dict lookup; assuming strptime converts to numeric types.

Related errors

• arr.dot query vector must be one-dimensional
• can not match overlapping patterns when leftmost == True
• cannot compare datetime.datetime to Series of type
• cannot construct PySeries for type
• cannot convert DataFrame to

AI-assisted analysis of pola-rs/polars@fe841f959e (2026-09-18). Data as JSON: /api/errors/6b68152f636136ee. Report an issue: GitHub.

Appendix: source

Thrown at py-polars/src/polars/expr/string.py:330

        if dtype == Date:
            return self.to_date(format, strict=strict, exact=exact, cache=cache)
        elif dtype == Datetime:
            time_unit = getattr(dtype, "time_unit", None)
            time_zone = getattr(dtype, "time_zone", None)
            return self.to_datetime(
                format,
                time_unit=time_unit,
                time_zone=time_zone,
                strict=strict,
                exact=exact,
                cache=cache,
                ambiguous=ambiguous,
            )
        elif dtype == Time:
            return self.to_time(format, strict=strict, cache=cache)
        else:
            msg = "`dtype` must be of type {Date, Datetime, Time}"
            raise ValueError(msg)

    @unstable()
    def to_decimal(self, *, scale: int) -> Expr:
        """
        Convert a String column into a Decimal column.

        .. engine-support:: in-memory, streaming, distributed

        .. warning::
            This functionality is considered **unstable**. It may be changed
            at any point without it being considered a breaking change.

        .. versionchanged:: 1.33.0
            Parameter `inference_length` was removed and `scale` was made non-optional.

        Parameters
        ----------
        scale

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