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https://issues.apache.org/jira/browse/BEAM-3377?focusedWorklogId=103242&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-103242
 ]

ASF GitHub Bot logged work on BEAM-3377:
----------------------------------------

                Author: ASF GitHub Bot
            Created on: 18/May/18 06:49
            Start Date: 18/May/18 06:49
    Worklog Time Spent: 10m 
      Work Description: mariapython commented on a change in pull request 
#5384: [BEAM-3377] Add validation for streaming wordcount with assert_that
URL: https://github.com/apache/beam/pull/5384#discussion_r189176631
 
 

 ##########
 File path: sdks/python/apache_beam/examples/streaming_wordcount_debugging.py
 ##########
 @@ -0,0 +1,179 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License.  You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+"""An example to use assert_that to validate streaming wordcount.
+
+It includes:
+  - PrintFn (DoFn) to inspect element, window, and timestamp.
+  - AddTimestampFn (DoFn) to modify timestamps.
+  - assert_that via check_gbk_format and equal_to_per_window (matchers).
+"""
+
+from __future__ import absolute_import
+
+import argparse
+import logging
+import re
+
+import six
+
+import apache_beam as beam
+import apache_beam.transforms.window as window
+from apache_beam.examples.wordcount import WordExtractingDoFn
+from apache_beam.options.pipeline_options import PipelineOptions
+from apache_beam.options.pipeline_options import SetupOptions
+from apache_beam.options.pipeline_options import StandardOptions
+from apache_beam.testing.util import assert_that
+from apache_beam.testing.util import equal_to_per_window
+from apache_beam.transforms.core import ParDo
+
+
+class PrintFn(beam.DoFn):
+  """A DoFn that prints label, element, its window, and its timstamp. """
+  def __init__(self, label):
+    self.label = label
+
+  def process(self, element, timestamp=beam.DoFn.TimestampParam,
+              window=beam.DoFn.WindowParam):
+    # Log at INFO level each element processed. When executing this pipeline
+    # using the Dataflow service, these log lines will appear in the Cloud
+    # Logging UI.
+    logging.info('[%s]: %s %s %s', self.label, element, window, timestamp)
+    yield element
+
+
+class AddTimestampFn(beam.DoFn):
+  """A DoFn that attaches timestamps to its elements.
+
+  It takes a string of integers and it attaches to each of them
+  a timestamp of its same value."""
 
 Review comment:
   Done.

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Issue Time Tracking
-------------------

    Worklog Id:     (was: 103242)
    Time Spent: 4h 50m  (was: 4h 40m)

> assert_that not working for streaming
> -------------------------------------
>
>                 Key: BEAM-3377
>                 URL: https://issues.apache.org/jira/browse/BEAM-3377
>             Project: Beam
>          Issue Type: Bug
>          Components: sdk-py-core
>    Affects Versions: 2.2.0
>            Reporter: MarĂ­a GH
>            Priority: Major
>              Labels: starter
>          Time Spent: 4h 50m
>  Remaining Estimate: 0h
>
> assert_that does not work for AfterWatermark timers.
> Easy way to reproduce: modify test_gbk_execution [1] in this form:
>  
> {code:java}
>  def test_this(self):
>     test_stream = (TestStream()
>                    .add_elements(['a', 'b', 'c'])
>                    .advance_watermark_to(20))
>     def fnc(x):
>       print 'fired_elem:', x
>       return x
>     options = PipelineOptions()
>     options.view_as(StandardOptions).streaming = True
>     p = TestPipeline(options=options)
>     records = (p
>                | test_stream
>                | beam.WindowInto(
>                    FixedWindows(15),
>                    
> trigger=trigger.AfterWatermark(early=trigger.AfterCount(2)),
>                    accumulation_mode=trigger.AccumulationMode.ACCUMULATING)
>                | beam.Map(lambda x: ('k', x))
>                | beam.GroupByKey())
>     assert_that(records, equal_to([
>         ('k', ['a', 'b', 'c'])]))
>     p.run()
> {code}
> This test will pass, but if the .advance_watermark_to(20) is removed, the 
> test will fail. However, both cases fire the same elements:
>       fired_elem: ('k', ['a', 'b', 'c'])
>       fired_elem: ('k', ['a', 'b', 'c'])
> In the passing case, they correspond to the sorted_actual inside the 
> assert_that. In the failing case:
>       sorted_actual: [('k', ['a', 'b', 'c']), ('k', ['a', 'b', 'c'])]
>       sorted_actual: []
> [1] 
> https://github.com/mariapython/incubator-beam/blob/direct-timers-show/sdks/python/apache_beam/testing/test_stream_test.py#L120



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