问题
My understanding is that finally clauses must *always* be executed if the try has been entered.
import random
from multiprocessing import Pool
from time import sleep
def Process(x):
try:
print x
sleep(random.random())
raise Exception('Exception: ' + x)
finally:
print 'Finally: ' + x
Pool(3).map(Process, ['1','2','3'])
Expected output is that for each of x which is printed on its own by line 8, there must be an occurrence of 'Finally x'.
Example output:
$ python bug.py
1
2
3
Finally: 2
Traceback (most recent call last):
File "bug.py", line 14, in <module>
Pool(3).map(Process, ['1','2','3'])
File "/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/multiprocessing/pool.py", line 225, in map
return self.map_async(func, iterable, chunksize).get()
File "/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/multiprocessing/pool.py", line 522, in get
raise self._value
Exception: Exception: 2
It seems that an exception terminating one process terminates the parent and sibling processes, even though there is further work required to be done in other processes.
Why am I wrong? Why is this correct? If this is correct, how should one safely clean up resources in multiprocess Python?
回答1:
Short answer: SIGTERM
trumps finally
.
Long answer: Turn on logging with mp.log_to_stderr()
:
import random
import multiprocessing as mp
import time
import logging
logger=mp.log_to_stderr(logging.DEBUG)
def Process(x):
try:
logger.info(x)
time.sleep(random.random())
raise Exception('Exception: ' + x)
finally:
logger.info('Finally: ' + x)
result=mp.Pool(3).map(Process, ['1','2','3'])
The logging output includes:
[DEBUG/MainProcess] terminating workers
Which corresponds to this code in multiprocessing.pool._terminate_pool
:
if pool and hasattr(pool[0], 'terminate'):
debug('terminating workers')
for p in pool:
p.terminate()
Each p
in pool
is a multiprocessing.Process
, and calling terminate
(at least on non-Windows machines) calls SIGTERM:
from multiprocessing/forking.py
:
class Popen(object)
def terminate(self):
...
try:
os.kill(self.pid, signal.SIGTERM)
except OSError, e:
if self.wait(timeout=0.1) is None:
raise
So it comes down to what happens when a Python process in a try
suite is sent a SIGTERM
.
Consider the following example (test.py):
import time
def worker():
try:
time.sleep(100)
finally:
print('enter finally')
time.sleep(2)
print('exit finally')
worker()
If you run it, then send it a SIGTERM
, then the process ends immediately, without entering the finally
suite, as evidenced by no output, and no delay.
In one terminal:
% test.py
In second terminal:
% pkill -TERM -f "test.py"
Result in first terminal:
Terminated
Compare that with what happens when the process is sent a SIGINT
(C-c
):
In second terminal:
% pkill -INT -f "test.py"
Result in first terminal:
enter finally
exit finally
Traceback (most recent call last):
File "/home/unutbu/pybin/test.py", line 14, in <module>
worker()
File "/home/unutbu/pybin/test.py", line 8, in worker
time.sleep(100)
KeyboardInterrupt
Conclusion: SIGTERM
trumps finally
.
回答2:
The answer from unutbu definitely explains why you get the behavior you observe. However, it should emphasized that SIGTERM is sent only because of how multiprocessing.pool._terminate_pool
is implemented. If you can avoid using Pool
, then you can get the behavior you desire. Here is a borrowed example:
from multiprocessing import Process
from time import sleep
import random
def f(x):
try:
sleep(random.random()*10)
raise Exception
except:
print "Caught exception in process:", x
# Make this last longer than the except clause in main.
sleep(3)
finally:
print "Cleaning up process:", x
if __name__ == '__main__':
processes = []
for i in range(4):
p = Process(target=f, args=(i,))
p.start()
processes.append(p)
try:
for process in processes:
process.join()
except:
print "Caught exception in main."
finally:
print "Cleaning up main."
After sending a SIGINT is, example output is:
Caught exception in process: 0
^C
Cleaning up process: 0
Caught exception in main.
Cleaning up main.
Caught exception in process: 1
Caught exception in process: 2
Caught exception in process: 3
Cleaning up process: 1
Cleaning up process: 2
Cleaning up process: 3
Note that the finally
clause is ran for all processes. If you need shared memory, consider using Queue
, Pipe
, Manager
, or some external store like redis
or sqlite3
.
回答3:
finally
re-raises the original exception unless you return from it. The exception is then raised by Pool.map
and kills your entire application. The subprocesses are terminated and you see no other exceptions.
You can add a return
to swallow the exception:
def Process(x):
try:
print x
sleep(random.random())
raise Exception('Exception: ' + x)
finally:
print 'Finally: ' + x
return
Then you should have None
in your map
result when an exception occurred.
来源:https://stackoverflow.com/questions/7700929/python-multiprocessing-map-if-one-process-raises-an-exception-why-arent-othe