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https://issues.apache.org/jira/browse/BEAM-8335?focusedWorklogId=377973&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-377973
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ASF GitHub Bot logged work on BEAM-8335:
----------------------------------------

                Author: ASF GitHub Bot
            Created on: 28/Jan/20 01:26
            Start Date: 28/Jan/20 01:26
    Worklog Time Spent: 10m 
      Work Description: rohdesamuel commented on pull request #10368: 
[BEAM-8335] Modify PipelineInstrument to add TestStream for unbounded 
PCollections
URL: https://github.com/apache/beam/pull/10368#discussion_r371571135
 
 

 ##########
 File path: sdks/python/apache_beam/testing/test_stream.py
 ##########
 @@ -172,13 +172,14 @@ class TestStream(PTransform):
   output.
   """
 
-  def __init__(self, coder=coders.FastPrimitivesCoder(), events=None):
+  def __init__(self, coder=coders.FastPrimitivesCoder(), events=None,
+               output_tags=None):
     super(TestStream, self).__init__()
     assert coder is not None
     self.coder = coder
     self.watermarks = {None: timestamp.MIN_TIMESTAMP}
-    self._events = [] if events is None else list(events)
-    self.output_tags = set()
+    self._events = list(events) if events is not None else []
+    self.output_tags = set(output_tags) if output_tags is not None else set()
 
 Review comment:
   Done
 
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Issue Time Tracking
-------------------

    Worklog Id:     (was: 377973)
    Time Spent: 54h  (was: 53h 50m)

> Add streaming support to Interactive Beam
> -----------------------------------------
>
>                 Key: BEAM-8335
>                 URL: https://issues.apache.org/jira/browse/BEAM-8335
>             Project: Beam
>          Issue Type: Improvement
>          Components: runner-py-interactive
>            Reporter: Sam Rohde
>            Assignee: Sam Rohde
>            Priority: Major
>          Time Spent: 54h
>  Remaining Estimate: 0h
>
> This issue tracks the work items to introduce streaming support to the 
> Interactive Beam experience. This will allow users to:
>  * Write and run a streaming job in IPython
>  * Automatically cache records from unbounded sources
>  * Add a replay experience that replays all cached records to simulate the 
> original pipeline execution
>  * Add controls to play/pause/stop/step individual elements from the cached 
> records
>  * Add ability to inspect/visualize unbounded PCollections



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