diff --git a/sdks/python/apache_beam/examples/wordcount.py b/sdks/python/apache_beam/examples/wordcount.py
index 92929afa2e1dc..c1d86aad75064 100644
--- a/sdks/python/apache_beam/examples/wordcount.py
+++ b/sdks/python/apache_beam/examples/wordcount.py
@@ -19,7 +19,6 @@
 
 from __future__ import absolute_import
 
-import argparse
 import logging
 import re
 
@@ -59,26 +58,29 @@ def process(self, context):
     return words
 
 
+class WordCountOptions(PipelineOptions):
+
+  @classmethod
+  def _add_argparse_args(cls, parser):
+    parser.add_argument(
+      '--input', help='Input for the dataflow pipeline',
+      default='gs://dataflow-samples/shakespeare/kinglear.txt')
+    parser.add_argument(
+      '--output', help='Output for the dataflow pipeline', required=True)
+
+
 def run(argv=None):
   """Main entry point; defines and runs the wordcount pipeline."""
-  parser = argparse.ArgumentParser()
-  parser.add_argument('--input',
-                      dest='input',
-                      default='gs://dataflow-samples/shakespeare/kinglear.txt',
-                      help='Input file to process.')
-  parser.add_argument('--output',
-                      dest='output',
-                      required=True,
-                      help='Output file to write results to.')
-  known_args, pipeline_args = parser.parse_known_args(argv)
+  pipeline_options = PipelineOptions(argv)
   # We use the save_main_session option because one or more DoFn's in this
   # workflow rely on global context (e.g., a module imported at module level).
-  pipeline_options = PipelineOptions(pipeline_args)
   pipeline_options.view_as(SetupOptions).save_main_session = True
+  word_count_options = pipeline_options.view_as(WordCountOptions)
+
   p = beam.Pipeline(options=pipeline_options)
 
   # Read the text file[pattern] into a PCollection.
-  lines = p | 'read' >> ReadFromText(known_args.input)
+  lines = p | 'read' >> ReadFromText(word_count_options.input)
 
   # Count the occurrences of each word.
   counts = (lines
@@ -93,7 +95,7 @@ def run(argv=None):
 
   # Write the output using a "Write" transform that has side effects.
   # pylint: disable=expression-not-assigned
-  output | 'write' >> WriteToText(known_args.output)
+  output | 'write' >> WriteToText(word_count_options.output)
 
   # Actually run the pipeline (all operations above are deferred).
   result = p.run()
diff --git a/sdks/python/apache_beam/utils/pipeline_options.py b/sdks/python/apache_beam/utils/pipeline_options.py
index 16b1640066bdc..1af3a0dfa6bf0 100644
--- a/sdks/python/apache_beam/utils/pipeline_options.py
+++ b/sdks/python/apache_beam/utils/pipeline_options.py
@@ -116,9 +116,16 @@ def get_all_options(self, drop_default=False):
     Returns:
       Dictionary of all args and values.
     """
+
+    # TODO(BEAM-1319): PipelineOption sub-classes in the main session might be
+    # repeated. Pick last unique instance of each subclass to avoid conflicts.
     parser = argparse.ArgumentParser()
+    subset = {}
     for cls in PipelineOptions.__subclasses__():
+      subset[str(cls)] = cls
+    for cls in subset.values():
       cls._add_argparse_args(parser)  # pylint: disable=protected-access
+
     known_args, _ = parser.parse_known_args(self._flags)
     result = vars(known_args)