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https://issues.apache.org/jira/browse/BEAM-7926?focusedWorklogId=332797&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-332797
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ASF GitHub Bot logged work on BEAM-7926:
----------------------------------------
Author: ASF GitHub Bot
Created on: 23/Oct/19 18:47
Start Date: 23/Oct/19 18:47
Worklog Time Spent: 10m
Work Description: KevinGG commented on pull request #9741: [BEAM-7926]
Visualize PCollection
URL: https://github.com/apache/beam/pull/9741#discussion_r338218476
##########
File path:
sdks/python/apache_beam/runners/interactive/interactive_environment.py
##########
@@ -61,8 +66,20 @@ def __init__(self, cache_manager=None):
self._watching_set = set()
# Holds variables list of (Dict[str, object]).
self._watching_dict_list = []
+ # Holds results of pipeline runs as Dict[Pipeline, PipelineResult].
+ # Each key is a pipeline instance defined by the end user. The
+ # InteractiveRunner is responsible for populating this dictionary
+ # implicitly.
+ self._pipeline_results = {}
# Always watch __main__ module.
self.watch('__main__')
+ # Do a warning level logging if current python version is below 2 or 3.5.3.
+ if sys.version_info < (3,):
+ logging.warning('Interactive Beam does not support Python 2.')
+ elif sys.version_info < (3, 5, 3):
Review comment:
We can. I'll make it simpler. Let's just consider every different component
a big feature. The feature requires Py 3.5.3. And we NOOP if dependency is not
ready.
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Issue Time Tracking
-------------------
Worklog Id: (was: 332797)
Time Spent: 12h 10m (was: 12h)
> Visualize PCollection with Interactive Beam
> -------------------------------------------
>
> Key: BEAM-7926
> URL: https://issues.apache.org/jira/browse/BEAM-7926
> Project: Beam
> Issue Type: New Feature
> Components: runner-py-interactive
> Reporter: Ning Kang
> Assignee: Ning Kang
> Priority: Major
> Time Spent: 12h 10m
> Remaining Estimate: 0h
>
> Support auto plotting / charting of materialized data of a given PCollection
> with Interactive Beam.
> Say an Interactive Beam pipeline defined as
> p = create_pipeline()
> pcoll = p | 'Transform' >> transform()
> The use can call a single function and get auto-magical charting of the data
> as materialized pcoll.
> e.g., visualize(pcoll)
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