Github user cloud-fan commented on the issue:
https://github.com/apache/spark/pull/16534
Recently we hit some problems while extending python udf, to support
`asNondeterministic`, `asNonNullable`, etc. It's really confusing if the return
type is just a python function.
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Github user cloud-fan commented on the issue:
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Is this still a problem? Now `UserDefinedFunction` defines `returnType` as
a property.
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Github user holdenk commented on the issue:
https://github.com/apache/spark/pull/16534
I agree, just in case someone does have an isinstance check (or similar) we
should document the change in the release notes.
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Github user zero323 commented on the issue:
https://github.com/apache/spark/pull/16534
Thanks @holdenk. I think it should be mentioned as a change of behavior in
the release notes. We don't change API, and `UserDefinedFunction` is hardly
public (it is not even included in the docs), n
Github user holdenk commented on the issue:
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Merged to master, thanks @zero323
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Github user holdenk commented on the issue:
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Great! Thanks for doing this, will merge to master :)
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Github user zero323 commented on the issue:
https://github.com/apache/spark/pull/16534
Don't worry, I get it :) The point is to make user experience better not
worse, right? In practice:
- These changes are pretty far from data, so overall impact is negligible
and constant.
Github user holdenk commented on the issue:
https://github.com/apache/spark/pull/16534
Yes pydoc.help does depend on looking at the docstring on the type rather
than the object :( Too bad the IPython magic isn't used in pydoc too.
Sorry for all the back and forth, I'm just try
Github user zero323 commented on the issue:
https://github.com/apache/spark/pull/16534
`update_wrapper` works the same way as `wraps` - it will be useful for
IPython, which uses relatively complex inspection rules, but will be useless
anywhere when one depends on `pydoc.help`.
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Github user holdenk commented on the issue:
https://github.com/apache/spark/pull/16534
I'm not sure about `wraps` but with `update_wrapper`, I tested it in a
Jupyter kernel and it seems to give all of the docstring and signature
information without adding another function dispatch ins
Github user zero323 commented on the issue:
https://github.com/apache/spark/pull/16534
To a very limited extent. It can bring some useful information in IPython
/ Jupyter (maybe some other tools as well) but won't work with built-in `help`
/ `pydoc.help`.
You can compare:
Github user holdenk commented on the issue:
https://github.com/apache/spark/pull/16534
So it feels like we are adding an extra layer of indirection unnecessarily,
could you use update_wrapper from functools directly on the udf object?
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Github user holdenk commented on the issue:
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Sure, I'll take another closer look.
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Github user rxin commented on the issue:
https://github.com/apache/spark/pull/16534
Change looks good to me but I didn't look super carefully.
@holdenk can you take a look at this?
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Github user zero323 commented on the issue:
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@rxin I am not aware of any straightforward way of separating these two,
but I focused on the docstrings anyway. The rationale is simple - I want to be
able to:
- Create packages containin
Github user rxin commented on the issue:
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Is the goal to change the doc or the repl string? It might be useful to
change the repl string but I'm not sure if it is worth changing the doc.
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Github user zero323 commented on the issue:
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Thanks @holdenk! Let's wait for another opinion (maybe @rxin) and if it is
not acceptable I'll just close this and ask for closing the ticket.
Theoretically we could define a constructor with dynam
Github user holdenk commented on the issue:
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So I'm not super comfortable changing the return type (what about if user
code has `isinstance` checks with `UserDefinedFunction`?) That being said if
@davies or one of the other committers thinks t
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Github user zero323 commented on the issue:
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@holdenk I used function arguments to make sure that public API, though not
types, is preserved. Please let me know what you think.
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Github user zero323 commented on the issue:
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@holdenk Indeed. Not the most fortunate moment for making a bunch of
connected PRs :)
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Github user zero323 commented on the issue:
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@holdenk I don't think it should go to the point release at all (same as
https://github.com/apache/spark/pull/16533 which, depending on the resolution,
may introduce new functionality or breaking AP
Github user holdenk commented on the issue:
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It's a bit hard to follow up wit those during JIRA maintenance window -
I'll follow up after JIRA comes back online :)
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Github user holdenk commented on the issue:
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Improving UDF Docstrings for Python seems like a good idea, but at the cost
of breaking the public API in a point release I think it might make sense for
us to do the more work approach unless there
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