def client_proc(computation, njobs, coro=None):
# use RemoteCoroScheduler to start coroutines at servers (should be done
# before scheduling computation)
rcoro_scheduler = RemoteCoroScheduler(computation)
# execute n jobs (coroutines) and get their results. Number of jobs created
# can be more than number of server processes available; the scheduler will
# use as many processes as necessary/available, running one job at a server
# process
# arguments must correspond to arguments for computaiton; multiple arguments
# (as in this case) can be given as tuples
args = [(i, random.uniform(2, 5)) for i in range(njobs)]
results = yield rcoro_scheduler.map_results(compute, args)
# Coroutines may not be executed in the order of given list of args, but
# results would be in the same order of given list of args
for result in results:
print(' result for %d from %s: %s' % result)
def client_proc(computation, coro=None):
# Use RemoteCoroScheduler to run at most one coroutine at a server process
# This should be created before scheduling computation
rcoro_scheduler = RemoteCoroScheduler(computation)
# execute 10 jobs (coroutines) and get their results. Note that number of
# jobs created can be more than number of server processes available; the
# scheduler will use as many processes as necessary/available, running one
# job at a server process
algorithms = ['md5', 'sha1', 'sha224', 'sha256', 'sha384', 'sha512']
args = [(algorithms[i % len(algorithms)], random.uniform(1, 3)) for i in range(20)]
results = yield rcoro_scheduler.map_results(compute, args)
for i, result in enumerate(results):
if isinstance(result, tuple) and len(result) == 2:
print(' %ssum: %s' % (result[0], result[1]))
else:
print(' rcoro failed for %s: %s' % (args[i][0], str(result)))
yield rcoro_scheduler.finish(close=True)
