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https://issues.apache.org/jira/browse/BEAM-4833?focusedWorklogId=130294&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-130294
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ASF GitHub Bot logged work on BEAM-4833:
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Author: ASF GitHub Bot
Created on: 02/Aug/18 15:49
Start Date: 02/Aug/18 15:49
Worklog Time Spent: 10m
Work Description: aaltay commented on a change in pull request #6005:
[BEAM-4833] Add support for user req.txt for portable python
URL: https://github.com/apache/beam/pull/6005#discussion_r207278269
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File path: sdks/python/container/Dockerfile
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@@ -79,14 +80,18 @@ RUN \
pip install "tensorflow == 1.4.0" && \
pip install "protorpc == 0.11.1" && \
pip install "python-gflags == 3.0.6" && \
- # Remove pip cache.
Review comment:
@holdenk please address this comment.
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Issue Time Tracking
-------------------
Worklog Id: (was: 130294)
Time Spent: 1h 40m (was: 1.5h)
> Add support for users specifying a requirements.txt for their Python portable
> container
> ---------------------------------------------------------------------------------------
>
> Key: BEAM-4833
> URL: https://issues.apache.org/jira/browse/BEAM-4833
> Project: Beam
> Issue Type: Improvement
> Components: sdk-py-core
> Reporter: holdenk
> Assignee: holdenk
> Priority: Minor
> Time Spent: 1h 40m
> Remaining Estimate: 0h
>
> It's pretty common that Python scripts require extra dependencies, even the
> tensorflow model analysis TFMA example requires a different version of TF
> than the one we install by default. While users can roll their own container
> or edit the Dockerfile, it would probably be useful to provide an easier path
> to integrating their dependencies.
> While we support automatically installing the dependencies at runtime on the
> workers, this can be very slow, especially for things like tensorflow, arrow,
> or other numeric heavy code.
> Another alternative could be a simple script to augment the existing base
> image.
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