[
https://issues.apache.org/jira/browse/BEAM-6588?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Robert Bradshaw updated BEAM-6588:
----------------------------------
Description:
If a type hint is specified for an input to beam.Filter, it attempts to infer
the output type (as Iterable[input_type], consistent with FlatMap), but that
inference appears to have a bug in it.
With the code:
{code:python}
@beam.typehints.with_input_types(int)
def OddFilter(data):
return data % 2 == 0
def pipeline(root):
base = root | beam.Create(xrange(100))
next = base | beam.Filter(OddFilter)
{code}
The following error is returned:
{code:python}
File "/google3/experimental/testproj/test_beam.py", line 26, in pipeline
next = base | beam.Filter(OddFilter)
File "/google3/third_party/py/apache_beam/transforms/core.py", line 1147, in
Filter
get_type_hints(wrapper).set_output_types(typehints.Iterable[output_hint])
File "/google3/third_party/py/apache_beam/typehints/typehints.py", line 951,
in __getitem__
type_param, error_msg_prefix='Parameter to an Iterable hint'
File "/google3/third_party/py/apache_beam/typehints/typehints.py", line 359,
in validate_composite_type_param
type_param.__class__.__name__))
TypeError: Parameter to an Iterable hint must be a non-sequence, a type, or a
TypeConstraint. (<type 'int'>,) is an instance of tuple.
{code}
Explicitly specifying the output type (as beam.typehints.Iterable[int]) works
fine. The code in core.py seems to be correct, but I'm guessing it needs a
derefence of the tuple to actually extract the type:
http://google3/third_party/py/apache_beam/transforms/core.py?l=1145&rcl=228573657
was:
If a type hint is specified for an input to beam.Filter, it attempts to infer
the output type (as Iterable[input_type], consistent with FlatMap), but that
inference appears to have a bug in it.
With the code:
@beam.typehints.with_input_types(int)
def OddFilter(data):
return data % 2 == 0
def pipeline(root):
base = root | beam.Create(xrange(100))
next = base | beam.Filter(OddFilter)
The following error is returned:
File "/google3/experimental/testproj/test_beam.py", line 26, in pipeline
next = base | beam.Filter(OddFilter)
File "/google3/third_party/py/apache_beam/transforms/core.py", line 1147, in
Filter
get_type_hints(wrapper).set_output_types(typehints.Iterable[output_hint])
File "/google3/third_party/py/apache_beam/typehints/typehints.py", line 951,
in __getitem__
type_param, error_msg_prefix='Parameter to an Iterable hint'
File "/google3/third_party/py/apache_beam/typehints/typehints.py", line 359,
in validate_composite_type_param
type_param.__class__.__name__))
TypeError: Parameter to an Iterable hint must be a non-sequence, a type, or a
TypeConstraint. (<type 'int'>,) is an instance of tuple.
Explicitly specifying the output type (as beam.typehints.Iterable[int]) works
fine. The code in core.py seems to be correct, but I'm guessing it needs a
derefence of the tuple to actually extract the type:
http://google3/third_party/py/apache_beam/transforms/core.py?l=1145&rcl=228573657
> Error in inferring output typehints for beam.Filter
> ---------------------------------------------------
>
> Key: BEAM-6588
> URL: https://issues.apache.org/jira/browse/BEAM-6588
> Project: Beam
> Issue Type: New Feature
> Components: sdk-py-core
> Reporter: Robert Bradshaw
> Assignee: Ahmet Altay
> Priority: Major
>
> If a type hint is specified for an input to beam.Filter, it attempts to infer
> the output type (as Iterable[input_type], consistent with FlatMap), but that
> inference appears to have a bug in it.
> With the code:
> {code:python}
> @beam.typehints.with_input_types(int)
> def OddFilter(data):
> return data % 2 == 0
> def pipeline(root):
> base = root | beam.Create(xrange(100))
> next = base | beam.Filter(OddFilter)
> {code}
> The following error is returned:
> {code:python}
> File "/google3/experimental/testproj/test_beam.py", line 26, in pipeline
> next = base | beam.Filter(OddFilter)
> File "/google3/third_party/py/apache_beam/transforms/core.py", line 1147,
> in Filter
> get_type_hints(wrapper).set_output_types(typehints.Iterable[output_hint])
> File "/google3/third_party/py/apache_beam/typehints/typehints.py", line
> 951, in __getitem__
> type_param, error_msg_prefix='Parameter to an Iterable hint'
> File "/google3/third_party/py/apache_beam/typehints/typehints.py", line
> 359, in validate_composite_type_param
> type_param.__class__.__name__))
> TypeError: Parameter to an Iterable hint must be a non-sequence, a type, or a
> TypeConstraint. (<type 'int'>,) is an instance of tuple.
> {code}
> Explicitly specifying the output type (as beam.typehints.Iterable[int]) works
> fine. The code in core.py seems to be correct, but I'm guessing it needs a
> derefence of the tuple to actually extract the type:
> http://google3/third_party/py/apache_beam/transforms/core.py?l=1145&rcl=228573657
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