#
# Author: Mike McKerns (mmckerns @caltech and @uqfoundation)
# Copyright (c) 1997-2016 California Institute of Technology.
# License: 3-clause BSD. The full license text is available at:
# - http://trac.mystic.cacr.caltech.edu/project/pathos/browser/pathos/LICENSE
from pathos.parallel import stats
from pathos.parallel import ParallelPool as Pool
pool = Pool()
def host(id):
import socket
return "Rank: %d -- %s" % (id, socket.gethostname())
print "Evaluate 10 items on 1 cpu"
pool.ncpus = 1
res3 = pool.map(host, range(10))
print pool
print '\n'.join(res3)
print stats()
print "Evaluate 10 items on 2 cpus"
pool.ncpus = 2
res5 = pool.map(host, range(10))
print pool
print '\n'.join(res5)
print stats()
# end of file
#!/usr/bin/env python
#
# Author: Mike McKerns (mmckerns @caltech and @uqfoundation)
# Copyright (c) 1997-2016 California Institute of Technology.
# Copyright (c) 2016-2018 The Uncertainty Quantification Foundation.
# License: 3-clause BSD. The full license text is available at:
# - https://github.com/uqfoundation/pathos/blob/master/LICENSE
from pathos.parallel import stats
from pathos.parallel import ParallelPool as Pool
pool = Pool()
def host(id):
import socket
import time
time.sleep(1.0)
return "Rank: %d -- %s" % (id, socket.gethostname())
print("Evaluate 10 items on 2 cpus") #FIXME: reset lport below
pool.ncpus = 2
pool.servers = ('localhost:5653', )
res5 = pool.map(host, range(10))
print(pool)
print('\n'.join(res5))
print(stats())
print('')
# end of file
word_count[word] = 1
return word_count
def top_ten(wordcount):
for key, value in sorted(word_count.items(), key=operator.itemgetter(1), reverse=True)[:10]:
print key, value
def wordcount(f):
words = word_list(f)
clean = cleanup(words)
word_dict(clean)
if __name__ == '__main__':
info('Mainline function')
pool.ncpus = 2
pool.servers = ('localhost:17320',)
words = pool.map(m_word_list, f)
pool.join()
pool.servers = ('localhost:17320',)
clean_list = pool.map(m_cleanup, words)
pool.join(clean_list, )
pool.servers = ('localhost:17320',)
word_count = pool.map(word_dict, cleanlist)
pool.join(word_count, )
top_ten(word_count)
