old_contents: import sys
  from random import Random
  
  from pyspark import SparkContext
  
  numEdges = 200
  numVertices = 100
  rand = Random(42)
  
  
  def generateGraph():
      edges = set()
      while len(edges) < numEdges:
          src = rand.randrange(0, numEdges)
          dst = rand.randrange(0, numEdges)
          if src != dst:
              edges.add((src, dst))
      return edges
  
  
  if __name__ == "__main__":
      if len(sys.argv) == 1:
          print >> sys.stderr, \
              "Usage: PythonTC <master> [<slices>]"
          exit(-1)
      sc = SparkContext(sys.argv[1], "PythonTC")
      slices = sys.argv[2] if len(sys.argv) > 2 else 2
      tc = sc.parallelize(generateGraph(), slices).cache()
  
      # Linear transitive closure: each round grows paths by one edge,
      # by joining the graph's edges with the already-discovered paths.
      # e.g. join the path (y, z) from the TC with the edge (x, y) from
      # the graph to obtain the path (x, z).
  
      # Because join() joins on keys, the edges are stored in reversed order.
      edges = tc.map(lambda (x, y): (y, x))
  
      oldCount = 0L
      nextCount = tc.count()
      while True:
          oldCount = nextCount
          # Perform the join, obtaining an RDD of (y, (z, x)) pairs,
          # then project the result to obtain the new (x, z) paths.
          new_edges = tc.join(edges).map(lambda (_, (a, b)): (b, a))
          tc = tc.union(new_edges).distinct().cache()
          nextCount = tc.count()
          if nextCount == oldCount:
              break
  
      print "TC has %i edges" % tc.count()
  
new_contents: import sys
  from random import Random
  
  from pyspark import SparkContext
  
  numEdges = 200
  numVertices = 100
  rand = Random(42)
  
  
  def generateGraph():
      edges = set()
      while len(edges) < numEdges:
          src = rand.randrange(0, numEdges)
          dst = rand.randrange(0, numEdges)
          if src != dst:
              edges.add((src, dst))
      return edges
  
  
  if __name__ == "__main__":
      if len(sys.argv) == 1:
          print >> sys.stderr, \
              "Usage: PythonTC <master> [<slices>]"
          exit(-1)
      sc = SparkContext(sys.argv[1], "PythonTC")
      slices = int(sys.argv[2]) if len(sys.argv) > 2 else 2
      tc = sc.parallelize(generateGraph(), slices).cache()
  
      # Linear transitive closure: each round grows paths by one edge,
      # by joining the graph's edges with the already-discovered paths.
      # e.g. join the path (y, z) from the TC with the edge (x, y) from
      # the graph to obtain the path (x, z).
  
      # Because join() joins on keys, the edges are stored in reversed order.
      edges = tc.map(lambda (x, y): (y, x))
  
      oldCount = 0L
      nextCount = tc.count()
      while True:
          oldCount = nextCount
          # Perform the join, obtaining an RDD of (y, (z, x)) pairs,
          # then project the result to obtain the new (x, z) paths.
          new_edges = tc.join(edges).map(lambda (_, (a, b)): (b, a))
          tc = tc.union(new_edges).distinct().cache()
          nextCount = tc.count()
          if nextCount == oldCount:
              break
  
      print "TC has %i edges" % tc.count()
  
subject: Fix argv handling in Python transitive closure example