old_contents: # Licensed Materials - Property of IBM
  # Copyright IBM Corp. 2017
  
  # Import the SPL decorators
  from streamsx.spl import spl
  
  import random
  
  # Defines the SPL namespace for any functions in this module
  # Multiple modules can map to the same namespace
  def spl_namespace():
      return "com.ibm.streamsx.topology.pysamples.primitives"
  
  @spl.primitive_operator(output_ports=['MATCH', 'NEAR_MATCH'])
  class SelectCustomers:
      """Score customers using a model.
      Customers that are a good match are submitted to port 0 ('MATCH')
      while customers that are a near match are submitted to port 1 ('NEAR_MATCH').
              
      Customers that are not a good or near match are not submitted to any port. 
      """
      def __init__(self, match, near_match):
          self.match = match
          self.near_match = near_match
      
      @spl.input_port()
      def customers(self, **tuple_):
          customer_score = self.score(tuple_)
          if customer_score >= self.match:
              self.submit('MATCH', tuple_)
          elif prospect_score >= self.near_match:
              self.submit('NEAR_MATCH', tuple_)
  
      def score(**prospect):
          # Real scoring omitted
          score = random.random()
          return score
  
new_contents: # Licensed Materials - Property of IBM
  # Copyright IBM Corp. 2017
  
  # Import the SPL decorators
  from streamsx.spl import spl
  
  import random
  
  # Defines the SPL namespace for any functions in this module
  # Multiple modules can map to the same namespace
  def spl_namespace():
      return "com.ibm.streamsx.topology.pysamples.primitives"
  
  @spl.primitive_operator(output_ports=['MATCH', 'NEAR_MATCH'])
  class SelectCustomers:
      """Score customers using a model.
      Customers that are a good match are submitted to port 0 ('MATCH')
      while customers that are a near match are submitted to port 1 ('NEAR_MATCH').
              
      Customers that are not a good or near match are not submitted to any port. 
      """
      def __init__(self, match, near_match):
          self.match = match
          self.near_match = near_match
      
      @spl.input_port()
      def customers(self, **tuple_):
          customer_score = self.score(tuple_)
          if customer_score >= self.match:
              self.submit('MATCH', tuple_)
          elif customer_score >= self.near_match:
              self.submit('NEAR_MATCH', tuple_)
  
      def score(self, **customer):
          # Real scoring omitted
          score = random.random()
          return score
  
subject: Fix sample