title: How do you test Beam pipeline (Google Dataflow) in Python?
body: <p>I am having understanding how we are supposed to test our pipeline using Google DataFlow(based on Apache Beam) Python SDK. </p>
  
  <p><a href="https://beam.apache.org/documentation/pipelines/test-your-pipeline/" rel="noreferrer">https://beam.apache.org/documentation/pipelines/test-your-pipeline/</a>
  <a href="https://cloud.google.com/dataflow/pipelines/creating-a-pipeline-beam" rel="noreferrer">https://cloud.google.com/dataflow/pipelines/creating-a-pipeline-beam</a></p>
  
  <p>The above link is ONLY for Java. I am pretty confused as to why Google will point to Java Apache testing. </p>
  
  <p>I want to be able to view the results of a CoGroupByKey join on two p collections. I am coming from a Python background, and I have little to no experience using Beam/Dataflow. </p>
  
  <p>Could really use any help. I know this is open ended to an extent.. basically I need to be able to view results within my pipeline and it's preventing me from seeing the results of my CoGroupByKey Join. </p>
  
  <p>Code Below</p>
  
  <pre><code>    #dwsku, product are PCollections coming from BigQuery. Nested Values as 
      #well in Product, but not dwsku
      d1 = {'dwsku': dwsku, 'product': product}
      results = d1 | beam.CoGroupByKey()
      print results
  </code></pre>
  
  <p>What is printed:</p>
  
  <pre><code>    PCollection[CoGroupByKey/Map(_merge_tagged_vals_under_key).None]
  </code></pre>