apache/beam · error · TypeError

repeat(repeats=) value must be an int or a DeferredSeries (e

Error message

repeat(repeats=) value must be an int or a DeferredSeries (encountered {type(repeats)}).

What it means

DeferredSeries.repeat only supports an integer repeat count or a DeferredSeries of counts. Python lists (or other iterables) are rejected: a per-element list of counts makes the operation order-sensitive, which Beam's distributed model cannot guarantee. Lists trigger a WontImplementError (order-sensitive) while any other non-int, non-DeferredSeries type triggers this TypeError.

Source

Thrown at sdks/python/apache_beam/dataframe/frames.py:2455

              'repeat', lambda series: series.repeat(repeats), [self._expr],
              requires_partition_by=partitionings.Arbitrary(),
              preserves_partition_by=partitionings.Arbitrary()))
    elif isinstance(repeats, frame_base.DeferredBase):
      return frame_base.DeferredFrame.wrap(
          expressions.ComputedExpression(
              'repeat',
              lambda series, repeats_series: series.repeat(repeats_series),
              [self._expr, repeats._expr],
              requires_partition_by=partitionings.Index(),
              preserves_partition_by=partitionings.Arbitrary()))
    elif isinstance(repeats, list):
      raise frame_base.WontImplementError(
          "repeat(repeats=) repeats must be an int or a DeferredSeries. "
          "Lists are not supported because they make this operation sensitive "
          "to the order of the data.",
          reason="order-sensitive")
    else:
      raise TypeError(
          "repeat(repeats=) value must be an int or a "
          f"DeferredSeries (encountered {type(repeats)}).")

  if hasattr(pd.Series, 'compare'):

    @frame_base.with_docs_from(pd.Series)
    @frame_base.args_to_kwargs(pd.Series)
    @frame_base.populate_defaults(pd.Series)
    def compare(self, other, align_axis, **kwargs):

      if align_axis in ('index', 0):
        preserves_partition = partitionings.Singleton()
      elif align_axis in ('columns', 1):
        preserves_partition = partitionings.Arbitrary()
      else:
        raise ValueError(
            "align_axis must be one of ('index', 0, 'columns', 1). "
            f"got {align_axis!r}.")

View on GitHub (pinned to 12126d8942)

Solutions

Pass a plain Python int if all elements repeat the same number of times: s.repeat(3).
Convert the counts into a DeferredSeries aligned with s, e.g. s.repeat(expressions.../ s2) where s2 is a DeferredSeries, instead of a list.
Cast the value to int if it is a numeric type like numpy.int64 or float with integral value.
Do the repeat before building the Beam DataFrame (on plain pandas) or with a different Beam transform (FlatMap).

Example fix

// before
df.repeat([1, 2, 3])
// after
counts = beam.dataframe.from_pandas(pd.Series([1, 2, 3]), ...)  # as DeferredSeries
df.repeat(counts)
// or, uniform repeat
df.repeat(3)

Defensive patterns

Strategy: type-guard

Validate before calling

if not isinstance(repeats, (int, DeferredSeries)):
    raise TypeError('repeats must be int or DeferredSeries')
if isinstance(repeats, bool):
    raise TypeError('bool is not a valid repeats value')

Type guard

def is_valid_repeats(repeats) -> bool:
    return (isinstance(repeats, int) and not isinstance(repeats, bool)) or isinstance(repeats, DeferredSeries)

Try / catch

try:
    out = s.repeat(repeats)
except (TypeError, frame_base.WontImplementError):
    out = s.repeat(int(repeats)) if np.isscalar(repeats) else None

Prevention

Use a scalar int for uniform repeats.
Convert count lists to a DeferredSeries before calling repeat.
Cast numpy integer types to int.
Remember lists are banned because they are order-sensitive in Beam.

When it happens

Trigger: Calling series.repeat([...]) with a list of counts; calling series.repeat('3') or series.repeat(3.0) with a non-int scalar; passing a plain pandas Series instead of a DeferredSeries.

Common situations: Porting pandas code that repeats rows per-element lists into Beam DataFrames; accidentally passing a numpy array or float where an int is expected.

Understand the failure class

Background: Type mismatch errors: IllegalArgumentException, TypeError and type guards across 150 open-source libraries — this error's family across 150 libraries.

Related errors

AI-assisted analysis of apache/beam@12126d8942 (2026-09-13). Data as JSON: /api/errors/0d6684a6cbac201d. Report an issue: GitHub.