Exception handling in Pool callback - python

Given this example scenario:
def _callback(result):
if result == 2:
# introduce an exception into one of the callbacks
raise Exception("foo")
print (result)
def _target(v):
return v
worker_pool = Pool()
for i in range(10):
worker_pool.apply_async(_target, args=(i,), callback=_callback)
worker_pool.close()
worker_pool.join()
I was hoping to see each value of i printed except for i=2, which would instead have yielded an exception.
Instead I see something like the following:
0
1
Exception in thread Thread-3:
Traceback (most recent call last):
File "/usr/lib/python3.6/threading.py", line 916, in _bootstrap_inner
self.run()
File "/usr/lib/python3.6/threading.py", line 864, in run
self._target(*self._args, **self._kwargs)
File "/usr/lib/python3.6/multiprocessing/pool.py", line 479, in _handle_results
cache[job]._set(i, obj)
File "/usr/lib/python3.6/multiprocessing/pool.py", line 649, in _set
self._callback(self._value)
File "test3.py", line 6, in _callback
raise Exception("foo")
Exception: foo
... and then execution just hangs.
I'm aware that Pool handles callbacks on a separate thread, but why would execution hang and how can I reliably guard against errors in a task's callback?

This is happening because the exception inside the callback method is basically killing the thread that handles the Pool, as it does not have an except block to handle this kind of situation. After the Thread is dead, it's unable to join the worker_pool, so your application hangs.
I believe that's a decision made by the Python maintainers, so the best way to handle this exception is to envelop your code inside a try/except block and handle it, instead of bubbling and letting the thread be killed.

Related

KeyboardInterrupt with Python multiprocessing.Pool

I want to write a service that launches multiple workers that work infinitely and then quit when main process is Ctrl+C'd. However, I do not understand how to handle Ctrl+C correctly.
I have a following testing code:
import os
import multiprocessing as mp
def g():
print(os.getpid())
while True:
pass
def main():
with mp.Pool(1) as pool:
try:
s = pool.starmap(g, [[]] * 1)
except KeyboardInterrupt:
print('Done')
if __name__ == "__main__":
print(os.getpid())
main()
When I try to Ctrl+C it, I expect process(es) running g to just receive SIGTERM and silently terminate, however, I receive something like that instead:
Process ForkPoolWorker-1:
Done
Traceback (most recent call last):
File "/usr/lib/python3.8/multiprocessing/process.py", line 315, in _bootstrap
self.run()
File "/usr/lib/python3.8/multiprocessing/process.py", line 108, in run
self._target(*self._args, **self._kwargs)
File "/usr/lib/python3.8/multiprocessing/pool.py", line 125, in worker
result = (True, func(*args, **kwds))
File "/usr/lib/python3.8/multiprocessing/pool.py", line 51, in starmapstar
return list(itertools.starmap(args[0], args[1]))
File "test.py", line 8, in g
pass
KeyboardInterrupt
This obviously means that parent and children processes both raise KeyboardInterrupt from Ctrl+C, further suggested by tests with kill -2. Why does this happen and how to deal with it to achieve what I want?
The signal that triggers KeyboardInterrupt is delivered to the whole pool. The child worker processes treat it the same as the parent, raising KeyboardInterrupt.
The easiest solution here is:
Disable the SIGINT handling in each worker on creation
Ensure the parent terminates the workers when it catches KeyboardInterrupt
You can do this easily by passing an initializer function that the Pool runs in each worker before the worker begins doing work:
import signal
import multiprocessing as mp
# Use initializer to ignore SIGINT in child processes
with mp.Pool(1, initializer=signal.signal, initargs=(signal.SIGINT, signal.SIG_IGN)) as pool:
try:
s = pool.starmap(g, [[]] * 1)
except KeyboardInterrupt:
print('Done')
The initializer replaces the default SIGINT handler with one that ignores SIGINT in the children, leaving it up to the parent process to kill them. The with statement in the parent handles this automatically (exiting the with block implicitly calls pool.terminate()), so all you're responsible for is catching the KeyboardInterrupt in the parent and converting from ugly traceback to simple message.

How can a parent thread know that its child thread has raised an exception?

I am using threading.Thread(target, *args, **k) from the Python threading library:
t = Thread(
target=self.connect,
args=(
hostname,
username,
password,
pre_name,
config_data,
action,
post_name),
kwargs=key_value
)
When I call t.start() - it executes the function in the target, but if the values are wrong or the device is not available - the thread will throw an exception, and the system will hang.
I get the following traceback:
Exception in thread Thread-2:
Traceback (most recent call last):
File "C:\Python27\lib\threading.py", line 801, in __bootstrap_inner
self.run()
File "C:\Python27\lib\threading.py", line 754, in run
self.__target(*self.__args, **self.__kwargs)
the connect function called in a particular thread is throwing an exception -which is not being identified by its parent thread.
How can the rest of my program know of this exception (so I can handle it)?

Pika Consumer as a Python Process (multiprocessing)

I am trying to use the example Pika Async consumer (http://pika.readthedocs.io/en/0.10.0/examples/asynchronous_consumer_example.html) as a multiprocessing process (by making the ExampleConsumer class subclass multiprocessing.Process). However, I'm running into some issues with gracefully shutting down everything.
Let's say for example I have defined my procs as below:
for k, v in queues_callbacks.iteritems():
proc = ExampleConsumer(queue, k, v, rabbit_user, rabbit_pw, rabbit_host, rabbit_port)
"queues_callbacks" is basically just a dictionary of exchange : callback_function (ideally I'd like to be able to connect to several exchanges with this architecture).
Then I do the normal python way of dealing with starting processes:
try:
for proc in self.consumers:
proc.start()
for proc in self.consumers:
proc.join()
except KeyboardInterrupt:
for proc in self.consumers:
proc.terminate()
proc.join(1)
The issue is coming when I try to stop everything. Let's say I've overriden the "terminate" method to call the consumer's "stop" method then continue on with the normal terminate of Process. With this structure, I am getting some strange attribute errors
Traceback (most recent call last):
File "/Users/christopheralexander/PycharmProjects/new_bot/abstract_bot.py", line 154, in <module>
main()
File "/Users/christopheralexander/PycharmProjects/new_bot/abstract_bot.py", line 150, in main
mybot.start()
File "/Users/christopheralexander/PycharmProjects/new_bot/abstract_bot.py", line 71, in start
self.stop()
File "/Users/christopheralexander/PycharmProjects/new_bot/abstract_bot.py", line 53, in stop
self.__stop_consumers__()
File "/Users/christopheralexander/PycharmProjects/new_bot/abstract_bot.py", line 130, in __stop_consumers__
self.consumers[0].terminate()
File "/Users/christopheralexander/PycharmProjects/new_bot/rabbit_consumer.py", line 414, in terminate
self.stop()
File "/Users/christopheralexander/PycharmProjects/new_bot/rabbit_consumer.py", line 399, in stop
self._connection.ioloop.start()
AttributeError: 'NoneType' object has no attribute 'ioloop'
It's as if these attributes somehow disappear at some point. In the particular case above, _connection is initialized as None, but then gets set when the Consumer is started. However, when the "stop" method is called, it has already reverted back to None (with nothing set to do so). I'm also observing other strange behavior, such as times when it appears that things are getting called twice (even though "stop" is called once). Any ideas as to what is going on here, or is this not the proper way of architecting this?
Thanks!

How can I catch a memory error in a spawned thread?

I've never used the multiprocessing library before, so all advice is welcome..
I've got a python program that uses the multiprocessing library to do some memory-intensive tasks in multiple processes, which occasionally runs out of memory (I'm working on optimizations, but that's not what this question is about). Sometimes, an out-of-memory error gets thrown in a way that I can't seem to catch (output below), and then the program hangs on pool.join() (I'm using multiprocessing.Pool. How can I make the program do something other than indefinitely wait when this problem occurs?
Ideally, The memory error is propagated back to the main process which then dies.
Here's the memory error:
Exception in thread Thread-1:
Traceback (most recent call last):
File "/usr/lib64/python2.7/threading.py", line 811, in __bootstrap_inner
self.run()
File "/usr/lib64/python2.7/threading.py", line 764, in run
self.__target(*self.__args, **self.__kwargs)
File "/usr/lib64/python2.7/multiprocessing/pool.py", line 325, in _handle_workers
pool._maintain_pool()
File "/usr/lib64/python2.7/multiprocessing/pool.py", line 229, in _maintain_pool
self._repopulate_pool()
File "/usr/lib64/python2.7/multiprocessing/pool.py", line 222, in _repopulate_pool
w.start()
File "/usr/lib64/python2.7/multiprocessing/process.py", line 130, in start
self._popen = Popen(self)
File "/usr/lib64/python2.7/multiprocessing/forking.py", line 121, in __init__
self.pid = os.fork()
OSError: [Errno 12] Cannot allocate memory
And here's where i manage multiprocessing:
mp_pool = mp.Pool(processes=num_processes)
mp_results = list()
for datum in input_data:
data_args = {
'value': 0 // actually some other simple dict key/values
}
mp_results.append(mp_pool.apply_async(_process_data, args=(common_args, data_args)))
frame_pool.close()
frame_pool.join() // hangs here when that thread dies..
for result_async in mp_results:
result = result_async.get()
// do stuff to collect results
// rest of the code
When I interrupt the hanging program, I get:
Process process_003:
Traceback (most recent call last):
File "/opt/rh/python27/root/usr/lib64/python2.7/multiprocessing/process.py", line 258, in _bootstrap
self.run()
File "/opt/rh/python27/root/usr/lib64/python2.7/multiprocessing/process.py", line 114, in run
self._target(*self._args, **self._kwargs)
File "/opt/rh/python27/root/usr/lib64/python2.7/multiprocessing/pool.py", line 102, in worker
task = get()
File "/opt/rh/python27/root/usr/lib64/python2.7/multiprocessing/queues.py", line 374, in get
return recv()
racquire()
KeyboardInterrupt
This is actually a known bug in python's multiprocessing module, fixed in python 3 (here's a summarizing blog post I found). There's a patch attached to python issue 22393, but that hasn't been officially applied.
Basically, if one of a multiprocess pool's sub-processes die unexpectedly (out of memory, killed externally, etc.), the pool will wait indefinitely.

Error with multiprocessing, atexit and global data

Sorry in advance, this is going to be long ...
Possibly related:
Python Multiprocessing atexit Error "Error in atexit._run_exitfuncs"
Definitely related:
python parallel map (multiprocessing.Pool.map) with global data
Keyboard Interrupts with python's multiprocessing Pool
Here's a "simple" script I hacked together to illustrate my problem...
import time
import multiprocessing as multi
import atexit
cleanup_stuff=multi.Manager().list([])
##################################################
# Some code to allow keyboard interrupts
##################################################
was_interrupted=multi.Manager().list([])
class _interrupt(object):
"""
Toy class to allow retrieval of the interrupt that triggered it's execution
"""
def __init__(self,interrupt):
self.interrupt=interrupt
def interrupt():
was_interrupted.append(1)
def interruptable(func):
"""
decorator to allow functions to be "interruptable" by
a keyboard interrupt when in python's multiprocessing.Pool.map
**Note**, this won't actually cause the Map to be interrupted,
It will merely cause the following functions to be not executed.
"""
def newfunc(*args,**kwargs):
try:
if(not was_interrupted):
return func(*args,**kwargs)
else:
return False
except KeyboardInterrupt as e:
interrupt()
return _interrupt(e) #If we really want to know about the interrupt...
return newfunc
#atexit.register
def cleanup():
for i in cleanup_stuff:
print(i)
return
#interruptable
def func(i):
print(i)
cleanup_stuff.append(i)
time.sleep(float(i)/10.)
return i
#Must wrap func here, otherwise it won't be found in __main__'s dict
#Maybe because it was created dynamically using the decorator?
def wrapper(*args):
return func(*args)
if __name__ == "__main__":
#This is an attempt to use signals -- I also attempted something similar where
#The signals were only caught in the child processes...Or only on the main process...
#
#import signal
#def onSigInt(*args): interrupt()
#signal.signal(signal.SIGINT,onSigInt)
#Try 2 with signals (only catch signal on main process)
#import signal
#def onSigInt(*args): interrupt()
#signal.signal(signal.SIGINT,onSigInt)
#def startup(): signal.signal(signal.SIGINT,signal.SIG_IGN)
#p=multi.Pool(processes=4,initializer=startup)
#Try 3 with signals (only catch signal on child processes)
#import signal
#def onSigInt(*args): interrupt()
#signal.signal(signal.SIGINT,signal.SIG_IGN)
#def startup(): signal.signal(signal.SIGINT,onSigInt)
#p=multi.Pool(processes=4,initializer=startup)
p=multi.Pool(4)
try:
out=p.map(wrapper,range(30))
#out=p.map_async(wrapper,range(30)).get() #This doesn't work either...
#The following lines don't work either
#Effectively trying to roll my own p.map() with p.apply_async
# results=[p.apply_async(wrapper,args=(i,)) for i in range(30)]
# out = [ r.get() for r in results() ]
except KeyboardInterrupt:
print ("Hello!")
out=None
finally:
p.terminate()
p.join()
print (out)
This works just fine if no KeyboardInterrupt is raised. However, if I raise one, the following exception occurs:
10
7
9
12
^CHello!
None
Error in atexit._run_exitfuncs:
Traceback (most recent call last):
File "/usr/lib/python2.6/atexit.py", line 24, in _run_exitfuncs
func(*targs, **kargs)
File "test.py", line 58, in cleanup
for i in cleanup_stuff:
File "<string>", line 2, in __getitem__
File "/usr/lib/python2.6/multiprocessing/managers.py", line 722, in _callmethod
self._connect()
File "/usr/lib/python2.6/multiprocessing/managers.py", line 709, in _connect
conn = self._Client(self._token.address, authkey=self._authkey)
File "/usr/lib/python2.6/multiprocessing/connection.py", line 143, in Client
c = SocketClient(address)
File "/usr/lib/python2.6/multiprocessing/connection.py", line 263, in SocketClient
s.connect(address)
File "<string>", line 1, in connect
error: [Errno 2] No such file or directory
Error in sys.exitfunc:
Traceback (most recent call last):
File "/usr/lib/python2.6/atexit.py", line 24, in _run_exitfuncs
func(*targs, **kargs)
File "test.py", line 58, in cleanup
for i in cleanup_stuff:
File "<string>", line 2, in __getitem__
File "/usr/lib/python2.6/multiprocessing/managers.py", line 722, in _callmethod
self._connect()
File "/usr/lib/python2.6/multiprocessing/managers.py", line 709, in _connect
conn = self._Client(self._token.address, authkey=self._authkey)
File "/usr/lib/python2.6/multiprocessing/connection.py", line 143, in Client
c = SocketClient(address)
File "/usr/lib/python2.6/multiprocessing/connection.py", line 263, in SocketClient
s.connect(address)
File "<string>", line 1, in connect
socket.error: [Errno 2] No such file or directory
Interestingly enough, the code does exit the Pool.map function without calling any of the additional functions ... The problem seems to be that the KeyboardInterrupt isn't handled properly at some point, but it is a little confusing where that is, and why it isn't handled in interruptable. Thanks.
Note, the same problem happens if I use out=p.map_async(wrapper,range(30)).get()
EDIT 1
A little closer ... If I enclose the out=p.map(...) in a try,except,finally clause, it gets rid of the first exception ... the other ones are still raised in atexit however. The code and traceback above have been updated.
EDIT 2
Something else that does not work has been added to the code above as a comment. (Same error). This attempt was inspired by:
http://jessenoller.com/2009/01/08/multiprocessingpool-and-keyboardinterrupt/
EDIT 3
Another failed attempt using signals added to the code above.
EDIT 4
I have figured out how to restructure my code so that the above is no longer necessary. In the (unlikely) event that someone stumbles upon this thread with the same use-case that I had, I will describe my solution ...
Use Case
I have a function which generates temporary files using the tempfile module. I would like those temporary files to be cleaned up when the program exits. My initial attempt was to pack each temporary file name into a list and then delete all the elements of the list with a function registered via atexit.register. The problem is that the updated list was not being updated across multiple processes. This is where I got the idea of using multiprocessing.Manager to manage the list data. Unfortunately, this fails on a KeyboardInterrupt no matter how hard I tried because the communication sockets between processes were broken for some reason. The solution to this problem is simple. Prior to using multiprocessing, set the temporary file directory ... something like tempfile.tempdir=tempfile.mkdtemp() and then register a function to delete the temporary directory. Each of the processes writes to the same temporary directory, so it works. Of course, this solution only works where the shared data is a list of files that needs to be deleted at the end of the program's life.

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