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https://issues.apache.org/jira/browse/BEAM-7060?focusedWorklogId=304682&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-304682
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ASF GitHub Bot logged work on BEAM-7060:
----------------------------------------
Author: ASF GitHub Bot
Created on: 31/Aug/19 00:21
Start Date: 31/Aug/19 00:21
Worklog Time Spent: 10m
Work Description: udim commented on pull request #9283: [BEAM-7060] Type
hints from Python 3 annotations
URL: https://github.com/apache/beam/pull/9283#discussion_r319695820
##########
File path: sdks/python/apache_beam/typehints/decorators.py
##########
@@ -265,23 +368,34 @@ def _unpack_positional_arg_hints(arg, hint):
return hint
-def getcallargs_forhints(func, *typeargs, **typekwargs):
- """Like inspect.getcallargs, but understands that Tuple[] and an Any unpack.
+def getcallargs_forhints(using_var_hints, func, *typeargs, **typekwargs):
+ """Like inspect.getcallargs, with support for declaring default args as Any.
+
+ In Python 2, understands that Tuple[] and an Any unpack.
+
+ Args:
+ using_var_hints: For variable length arguments, whether to expect the bound
Review comment:
It's only possible to tell which hints apply to a variadic argument by
calling getacallargs or signature.bind, so I don't see how to preprocess the
hint (unless we create special types, which complicates usage and consistency
checks).
Post-processing is similarly inelegant, since we would have to export
parameter types (vararg, varkw, etc.) and logic that doesn't belong outside of
the typehints module.
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Issue Time Tracking
-------------------
Worklog Id: (was: 304682)
Time Spent: 13h (was: 12h 50m)
> Design Py3-compatible typehints annotation support in Beam 3.
> -------------------------------------------------------------
>
> Key: BEAM-7060
> URL: https://issues.apache.org/jira/browse/BEAM-7060
> Project: Beam
> Issue Type: Sub-task
> Components: sdk-py-core
> Reporter: Valentyn Tymofieiev
> Assignee: Udi Meiri
> Priority: Major
> Fix For: 2.16.0
>
> Time Spent: 13h
> Remaining Estimate: 0h
>
> Existing [Typehints implementaiton in
> Beam|[https://github.com/apache/beam/blob/master/sdks/python/apache_beam/typehints/
> ] heavily relies on internal details of CPython implementation, and some of
> the assumptions of this implementation broke as of Python 3.6, see for
> example: https://issues.apache.org/jira/browse/BEAM-6877, which makes
> typehints support unusable on Python 3.6 as of now. [Python 3 Kanban
> Board|https://issues.apache.org/jira/secure/RapidBoard.jspa?rapidView=245&view=detail]
> lists several specific typehints-related breakages, prefixed with "TypeHints
> Py3 Error".
> We need to decide whether to:
> - Deprecate in-house typehints implementation.
> - Continue to support in-house implementation, which at this point is a stale
> code and has other known issues.
> - Attempt to use some off-the-shelf libraries for supporting
> type-annotations, like Pytype, Mypy, PyAnnotate.
> WRT to this decision we also need to plan on immediate next steps to unblock
> adoption of Beam for Python 3.6+ users. One potential option may be to have
> Beam SDK ignore any typehint annotations on Py 3.6+.
> cc: [~udim], [~altay], [~robertwb].
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