Hi all,
I wonder if anyone can shed some light on an issue I'm having with type
checking and the Beam python SDK.
Without changing any python code, I'm finding that running my pipeline with
or without the option no_pipeline_type_check starts the pipeline without
issue; no type check errors are raised and the pipeline begins processing.
However, if I allow pipeline type checking, I get a coder error later at
runtime:
File "apache_beam/coders/coder_impl.py", line 271, in
apache_beam.coders.coder_impl.CallbackCoderImpl.estimate_size
File "/my/path/lib/python3.6/site-packages/apache_beam/coders/coders.py",
line 189, in estimate_size
return len(self.encode(value))
File “/my/path/lib/python3.6/site-packages/apache_beam/coders/coders.py",
line 411, in encode
return value.encode('utf-8')
AttributeError: 'list' object has no attribute 'encode' [while running
'ParDo(MyDoFn)']
I do realize that the attribute error itself is a legitimate type of error,
and list type does in fact have no "encode" attribute. But if I run my
pipeline with --no_pipeline_type_check, this attr error does not arise and
the pipeline completes without errors. What could be happening here?
Thanks,
Evan
