apache/beam · error · ValueError

DoFn.WatermarkEstimatorParam…

Error message

DoFn.WatermarkEstimatorParam expectedWatermarkEstimatorProvider object.

What it means

ValueError raised by `_WatermarkDoFnParam.__init__` (exposed as `DoFn.WatermarkEstimatorParam`) when the supplied watermark_estimator_provider is not `None` and is not an instance of `WatermarkEstimatorProvider`. Only a provider instance (or None) is accepted for watermark estimator parameters.

Solutions

Pass an instance of a class subclassing `WatermarkEstimatorProvider`, or use the built-in `WatermarkEstimatorParam(lambda state: WatermarkEstimator(...))`-style helper that wraps a callable in a provider.
Pass `None` if no custom estimator is needed.
Ensure an instance (not the class) is passed.

Example fix

// before
param = DoFn.WatermarkEstimatorParam(MyWatermarkEstimator)  # class, not provider
// after
param = DoFn.WatermarkEstimatorParam(MyWatermarkEstimatorProvider())  # WatermarkEstimatorProvider instance

Defensive patterns

Strategy: type-guard

Validate before calling

from apache_beam.transforms.core import WatermarkEstimatorProvider
if provider is not None and not isinstance(provider, WatermarkEstimatorProvider):
    raise TypeError('expected WatermarkEstimatorProvider instance')

Type guard

from apache_beam.transforms.core import WatermarkEstimatorProvider
def is_watermark_provider(x) -> bool:
    return x is None or isinstance(x, WatermarkEstimatorProvider)

Try / catch

try:
    param = DoFn.WatermarkEstimatorParam(provider)
except ValueError as e:
    if 'WatermarkEstimatorProvider' in str(e):
        provider = provider() if isinstance(provider, type) else None

Prevention

Subclass WatermarkEstimatorProvider rather than passing bare estimator functions or classes
Pass None when no custom estimator is needed
Double-check instance vs class when wiring DoFn params

When it happens

Trigger: Writing `DoFn.WatermarkEstimatorParam(MyEstimator)` or passing a class, callable, or estimator function instead of an object implementing `WatermarkEstimatorProvider` when declaring a DoFn with custom watermark estimation.

Common situations: Passing a watermark estimator factory function instead of a provider wrapping it; passing the class rather than an instance; confusion with `WatermarkEstimatorParam` expecting `WatermarkEstimatorProvider` (note the missing space in the message is cosmetic).

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/9d3b99e31745526e. Report an issue: GitHub.

Appendix: source

Thrown at sdks/python/apache_beam/transforms/core.py:526

  def has_callbacks(self):
    # type: () -> bool
    return len(self._callbacks) > 0

  def reset(self):
    # type: () -> None
    del self._callbacks[:]


class _WatermarkEstimatorParam(_DoFnParam):
  """WatermarkEstimator DoFn parameter."""
  def __init__(
      self,
      watermark_estimator_provider: typing.
      Optional[WatermarkEstimatorProvider] = None):
    if (watermark_estimator_provider is not None and not isinstance(
        watermark_estimator_provider, WatermarkEstimatorProvider)):
      raise ValueError(
          'DoFn.WatermarkEstimatorParam expected'
          'WatermarkEstimatorProvider object.')
    self.watermark_estimator_provider = watermark_estimator_provider
    self.param_id = 'WatermarkEstimatorProvider'


class _ContextParam(_DoFnParam):
  def __init__(
      self, context_manager_constructor, args=(), kwargs=None, *, name=None):
    class_name = self.__class__.__name__.strip('_')
    if (not callable(context_manager_constructor) or
        (hasattr(context_manager_constructor, '__enter__') and
         len(inspect.signature(
             context_manager_constructor.__enter__).parameters) == 0)):
      # Context managers constructed with @contextlib.contextmanager can only
      # be used once, and in addition cannot be pickled because they invoke
      # the function on __init__ rather than at __enter__.
      # In addition, other common context managers such as

View on GitHub (pinned to 12126d8942)