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https://issues.apache.org/jira/browse/BEAM-1251?focusedWorklogId=81694&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-81694
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ASF GitHub Bot logged work on BEAM-1251:
----------------------------------------
Author: ASF GitHub Bot
Created on: 18/Mar/18 21:30
Start Date: 18/Mar/18 21:30
Worklog Time Spent: 10m
Work Description: cclauss commented on issue #4820: [BEAM-1251] Upgrade
from buffer to memoryview for Python 3
URL: https://github.com/apache/beam/pull/4820#issuecomment-374046915
Thanks for catching this. I did not have an effective way to test. Reading
through:
* https://docs.python.org/2.7/library/stdtypes.html#memoryview
* https://docs.python.org/3/library/stdtypes.html#memoryview
I get the sense that the next thing to try would be to wrap it with
__six.binary_type()__ as in __six.binary_type(memoryview(data)[:-4])__
__memoryview__ exists in all versions of Python that Beam supports so once
we find a __memoryview__-based solution that works, we should be able to drop
__buffer__ altogether.
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Issue Time Tracking
-------------------
Worklog Id: (was: 81694)
Time Spent: 8h (was: 7h 50m)
> Python 3 Support
> ----------------
>
> Key: BEAM-1251
> URL: https://issues.apache.org/jira/browse/BEAM-1251
> Project: Beam
> Issue Type: Improvement
> Components: sdk-py-core
> Reporter: Eyad Sibai
> Priority: Trivial
> Time Spent: 8h
> Remaining Estimate: 0h
>
> I have been trying to use google datalab with python3. As I see there are
> several packages that does not support python3 yet which google datalab
> depends on. This is one of them.
> https://github.com/GoogleCloudPlatform/DataflowPythonSDK/issues/6
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