parallel processing - Python, Multiprocessing: what does process.join() do? -

import time multiprocessing import process  def loop(limit):     in xrange(limit):         pass     print  limit = 100000000 #100 million  start = time.time()      in xrange(5):     p = process(target=loop, args=(limit,))     p.start() p.join()  end = time.time() print end - start 

i tried running code, output getting

99999999 99999999 2.73401999474 99999999 99999999 99999999 

and sometimes

99999999 99999999 3.72434902191 99999999 99999999 99999999 99999999 99999999 

in case loop function called 7 times instead of 5. why strange behaviour?

i confused role of p.join() statement. ending 1 process or of them @ same time?

the join function wait last process call finish before moving onto next section of code. if walk through have done should see why "strange" output.

for in xrange(5):     p = process(target=loop, args=(limit,))     p.start() 

this starts 5 new processes 1 after other. these running @ same time. just @ least, down scheduler decide process being processed.

this mean have 5 processes running now:

process 1

process 2

process 3

process 4

process 5

p.join() 

this going wait p process finish process 5 last process assigned p.

lets process 2 finishes first followed process 5, feasible scheduler give processes more time on cpu.

process 1

process 2 prints 99999999

process 3

process 4

process 5 prints 99999999

the p.join() line move on next part p process 5 has finished.

end = time.time() print end - start 

this section prints part , there 3 processes still going on after output.

the other processes finish , print there 99999999.

to fix behaviour need .join() processes. alter code this...

processes = []  in xrange(5):     p = process(target=loop, args=(limit,))     p.start()     processes.append(p)  process in processes:     process.join() 

this wait first process, second , on. won't matter if 1 process finished before anther because every process on list must waited on before script continues.