cozos opened a new issue, #26493:
URL: https://github.com/apache/beam/issues/26493
### What would you like to happen?
I have a multi-output DoFn:
```py
class DoFn1:
def process(self, row) -> Iterable[Union[Dict[str, Any],
pvalue.TaggedOutput]]:
if something:
yield some_dict(...)
else:
yield pvalue.TaggedOutput("bad", ...)
```
And another DoFn that consumes its outputs
```py
class DoFn2:
def process(self, row: Dict[str, Any]) -> Iterable[...]:
if something:
yield some_dict(...)
else:
yield pvalue.TaggedOutput("bad", ...)
```
And then when I use it like this:
```py
pcoll = ...
pcoll = pcoll | "dofn1" >> beam.ParDo(DoFn1()).with_outputs(
"bad",
main="good",
)
pcoll["good"] | "dofn2" >> beam.ParDo(DoFn2())
```
I get an error that looks like this:
```
apache_beam.typehints.decorators.TypeCheckError: Type hint violation for
'dofn2': requires Dict[str, Any] but got Union[Dict[str, Any], TaggedOutput]
for row
```
How can I tell Beam type checking that the `good` tag gives `Dict[str,
Any]`, and `bad` gives `TaggedOutput`? Am I forced to propagate the tagged
output type hints?
Also asked in SO here if not appropriate for Github:
https://stackoverflow.com/questions/76151787/in-apache-beam-dataflow-multi-output-dofns-how-do-you-assign-type-hints-to-spec
I found a related discussion here: https://github.com/apache/beam/pull/9810
### Issue Priority
Priority: 3 (nice-to-have improvement)
### Issue Components
- [X] Component: Python SDK
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- [ ] Component: Beam examples
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