class_docstr: The next version of our playlist generator that uses the statistics
  generated from 'Episode 02' to improve the title recommendations.
  
  The flow performs the following steps:
  
  1) Load the genre-specific statistics from the MovieStatsFlow.
  2) In parallel branches:
     - A) Build a playlist from the top grossing films in the requested genre.
     - B) Choose a random movie.
  3) Join the two to create a movie playlist and display it.
docstr: Use the Metaflow client to retrieve the latest successful run from our
  MovieStatsFlow and assign them as data artifacts in this flow.
docstr_tok: ["Use","the","Metaflow","client","to","retrieve","the","latest","successful","run","from","our","MovieStatsFlow","and","assign","them","as","data","artifacts","in","this","flow","."]
code: def start(self):
      """
      Use the Metaflow client to retrieve the latest successful run from our
      MovieStatsFlow and assign them as data artifacts in this flow.
  
      """
      from metaflow import Flow, get_metadata
  
      # Print metadata provider
      print("Using metadata provider: %s" % get_metadata())
  
      # Load the analysis from the MovieStatsFlow.
      run = Flow("MovieStatsFlow").latest_successful_run
      print("Using analysis from '%s'" % str(run))
  
      self.genre_stats = run.data.genre_stats
  
      # Compute our two recommendation types in parallel.
      self.next(self.bonus_movie, self.genre_movies)
  
file_path: metaflow/metaflow/tutorials/03-playlist-redux/playlist.py
imports: from metaflow import FlowSpec, step, Parameter
label_desc: Use image node_id 1 for calling the PlayListFlow obj's underlying member method code with example usage: obj.start() without return types