assure that all threads get released (drained) before any one of them can loop
back and re-enter the barrier. The barrier fully resets after each cycle.
-If any of the predecessor tasks can hang or be delayed, a barrier can be created
-with an optional *timeout* parameter. Then if the timeout period elapses before
-all the predecessor tasks reach the barrier point, all waiting threads are
-released and a :exc:`~threading.BrokenBarrierError` exception is raised.
-
Example of using barriers::
def get_votes(site):
and continue to do work (summarizing ballots) after the barrier point is
crossed.
+If any of the predecessor tasks can hang or be delayed, a barrier can be created
+with an optional *timeout* parameter. Then if the timeout period elapses before
+all the predecessor tasks reach the barrier point, all waiting threads are
+released and a :exc:`~threading.BrokenBarrierError` exception is raised::
+
+ def get_votes(site):
+ ballots = conduct_election(site)
+ try:
+ all_polls_closed.wait(timeout = midnight - time.now())
+ except BrokenBarrerError:
+ lockbox = seal_ballots(ballots)
+ queue.put(lockbox)
+ else:
+ totals = summarize(ballots)
+ publish(site, totals)
+
+In this example, the barrier enforces a more robust rule. If some election
+sites do not finish before midnight, the barrier times-out and the ballots are
+sealed and deposited in a queue for later handling.
+
See `Barrier Synchronization Patterns
<http://parlab.eecs.berkeley.edu/wiki/_media/patterns/paraplop_g1_3.pdf>`_ for
more examples of how barriers can be used in parallel computing. Also, there is