old_contents: #
  # 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.
  #
  
  """A streaming word-counting workflow.
  
  Important: streaming pipeline support in Python Dataflow is in development
  and is not yet available for use.
  """
  
  from __future__ import absolute_import
  
  import argparse
  import logging
  
  
  import apache_beam as beam
  import apache_beam.transforms.window as window
  
  
  def split_fn(lines):
    import re
    return re.findall(r'[A-Za-z\']+', x)
  
  
  def run(argv=None):
    """Build and run the pipeline."""
    parser = argparse.ArgumentParser()
    parser.add_argument(
        '--input_topic', required=True,
        help='Input PubSub topic of the form "/topics/<PROJECT>/<TOPIC>".')
    parser.add_argument(
        '--output_topic', required=True,
        help='Output PubSub topic of the form "/topics/<PROJECT>/<TOPIC>".')
    known_args, pipeline_args = parser.parse_known_args(argv)
  
    with beam.Pipeline(argv=pipeline_args) as p:
  
      # Read from PubSub into a PCollection.
      lines = p | beam.io.ReadStringsFromPubSub(known_args.input_topic)
  
      # Capitalize the characters in each line.
      transformed = (lines
                     # Use a pre-defined function that imports the re package.
                     | 'Split' >> (
                         beam.FlatMap(split_fn).with_output_types(unicode))
                     | 'PairWithOne' >> beam.Map(lambda x: (x, 1))
                     | beam.WindowInto(window.FixedWindows(15, 0))
                     | 'Group' >> beam.GroupByKey()
                     | 'Count' >> beam.Map(lambda (word, ones): (word, sum(ones)))
                     | 'Format' >> beam.Map(lambda tup: '%s: %d' % tup))
  
      # Write to PubSub.
      # pylint: disable=expression-not-assigned
      transformed | beam.io.WriteStringsToPubSub(known_args.output_topic)
  
  
  if __name__ == '__main__':
    logging.getLogger().setLevel(logging.INFO)
    run()
  
new_contents: #
  # 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.
  #
  
  """A streaming word-counting workflow.
  
  Important: streaming pipeline support in Python Dataflow is in development
  and is not yet available for use.
  """
  
  from __future__ import absolute_import
  
  import argparse
  import logging
  
  
  import apache_beam as beam
  import apache_beam.transforms.window as window
  
  
  def split_fn(lines):
    import re
    return re.findall(r'[A-Za-z\']+', lines)
  
  
  def run(argv=None):
    """Build and run the pipeline."""
    parser = argparse.ArgumentParser()
    parser.add_argument(
        '--input_topic', required=True,
        help='Input PubSub topic of the form "/topics/<PROJECT>/<TOPIC>".')
    parser.add_argument(
        '--output_topic', required=True,
        help='Output PubSub topic of the form "/topics/<PROJECT>/<TOPIC>".')
    known_args, pipeline_args = parser.parse_known_args(argv)
  
    with beam.Pipeline(argv=pipeline_args) as p:
  
      # Read from PubSub into a PCollection.
      lines = p | beam.io.ReadStringsFromPubSub(known_args.input_topic)
  
      # Capitalize the characters in each line.
      transformed = (lines
                     # Use a pre-defined function that imports the re package.
                     | 'Split' >> (
                         beam.FlatMap(split_fn).with_output_types(unicode))
                     | 'PairWithOne' >> beam.Map(lambda x: (x, 1))
                     | beam.WindowInto(window.FixedWindows(15, 0))
                     | 'Group' >> beam.GroupByKey()
                     | 'Count' >> beam.Map(lambda (word, ones): (word, sum(ones)))
                     | 'Format' >> beam.Map(lambda tup: '%s: %d' % tup))
  
      # Write to PubSub.
      # pylint: disable=expression-not-assigned
      transformed | beam.io.WriteStringsToPubSub(known_args.output_topic)
  
  
  if __name__ == '__main__':
    logging.getLogger().setLevel(logging.INFO)
    run()
  
subject: Fix a typo in function args