This my code
def timeout(seconds_before_timeout):
def deco(func):
#functools.wraps(func)
def wrapper(*args, **kwargs):
res = [
Exception("function [%s] timeout [%s seconds] exceeded!"
% (func.__name__, seconds_before_timeout))
]
def new_func():
try:
res[0] = func(*args, **kwargs)
except Exception as ex:
res[0] = ex
thread = Thread(target=new_func)
thread.daemon = True
try:
thread.start()
thread.join(seconds_before_timeout)
except Exception as ex:
print("error starting thread")
raise ex
ret = res[0]
if isinstance(ret, BaseException):
raise ret
return ret
return wrapper
return deco
And timeout function i used for:
#timeout(2)
def listen_for_a_new_campaign(self):
"""
Start listening for new campaign in list_campaign queue
"""
while True:
try:
for method_frame, properties, body \
in self.obj_requester_channel.consume(LIST_CAMPAIGN_QUEUE):
body_dict = literal_eval(body.decode("utf-8"))
message_number = body_dict["Msg_Count"]
n_message = min(message_number, BATCH_SIZE)
identify(n_message)
a_request = {
"campaign_request": body_dict,
"campaign_ack" : method_frame.delivery_tag,
"n_message" : n_message
}
identify(a_request)
return a_request
# Acknowledge the message
n_requeued_messages = self.obj_requester_channel.cancel()
print("Requeued %i messages" % n_requeued_messages)
break
except pika.exceptions.ConnectionWrongStateError:
print("Create connection ...")
self.create_connection()
continue
except pika.exceptions.ChannelWrongStateError:
print("Create connection ...")
self.create_connection()
self.obj_requester_channel = self.obj_connection.channel()
self.obj_requester_channel.queue_declare(queue=LIST_CAMPAIGN_QUEUE)
self.obj_campaign_channel = self.obj_connection.channel()
continue
When I run my program, I checked all process by htop and below is result, all thread is alive:
I don't know what's wrong with that.
I run this code on my laptop everything was OK, but when I deploy them to EC2 instance I found that problems.
Help me!!
Related
For some reason, my program is hanging using multiprocessing and queues, even though I set timeouts and check if the queue is empty. This happens on both Windows and Linux.
There are multiple processes that recieve inputs (here a, b and c) and should send results (here they just send back the inputs a, b and c).
From what I see, after all "arguments are given" they send back results for a and b over and over again, although a and b are provided only once.
import multiprocessing as mp
import queue
class Multithreading:
def __init__(self, n_processes):
self._processes = [
_Thread(name='Process-{}'.format(i))
for i in range(n_processes)]
def __enter__(self):
for process in self._processes:
process.start()
print(f'Started {process.name}')
return self
def __exit__(self, exc_type, exc_val, exc_tb):
for process in self._processes:
process.event_stopped.set()
process.join()
def run(self):
args = ['a', 'b', 'c']
n_calls = len(args)
for i, arg in enumerate(args):
m = i % len(self._processes)
print(f'Setting arguments to {self._processes[m].name}')
is_started = False
while not is_started:
try:
self._processes[m].queue_inputs.put(arg, timeout=0.05)
is_started = True
print(f'Argument given to {self._processes[m].name}')
except queue.Full:
pass
print(f'All arguments given')
for i in range(n_calls):
m = i % len(self._processes)
print(f'Checking result from {self._processes[m].name}')
arg = None
while True:
try:
arg = self._processes[m].queue_results.get(timeout=0.05)
print('Received {}'.format(arg))
break
except queue.Empty:
print(f'Empty in {self._processes[m].name}, arg = {arg}')
pass
class _Thread(mp.Process):
def __init__(self, name):
super().__init__(name=name, target=self._run)
self.queue_inputs = mp.Queue()
self.queue_results = mp.Queue()
self.event_stopped = mp.Event()
def _run(self):
print(f'Running {self.name}')
while not self.event_stopped.is_set():
try:
arg = self.queue_inputs.get(timeout=0.05)
print(f'{self.name} received {arg}')
while not self.event_stopped.is_set():
try:
self.queue_results.put(arg, timeout=0.05)
print(f'{self.name} sent {arg}')
except queue.Full:
pass
except queue.Empty:
pass
if __name__ == '__main__':
for _ in range(100000000):
with Multithreading(n_processes=2) as m:
m.run()
I would expect timeouts of put and get methods to raise the according exceptions, but apparently they do not.
The problem is in _Thread._run:
def _run(self):
print(f'Running {self.name}')
while not self.event_stopped.is_set(): # Ok, loop until event_stopped
try:
arg = self.queue_inputs.get(timeout=0.05) # Ok, try to get an item
print(f'{self.name} received {arg}')
while not self.event_stopped.is_set(): # Oops, what is this loop for???
try:
self.queue_results.put(arg, timeout=0.05)
print(f'{self.name} sent {arg}')
except queue.Full:
pass
except queue.Empty:
pass
Your current code loops infinitely (or until its queue_results queue become full of event_stopped is set) on the same item repeatedly adding it to its output queue. Replacing the offending while with a if is enough to fix the problem:
...
while not self.event_stopped.is_set(): # Ok, loop until event_stopped
try:
arg = self.queue_inputs.get(timeout=0.05) # Ok, try to get an item
print(f'{self.name} received {arg}')
if not self.event_stopped.is_set():# ignore the item if stopped in the meanwhile
try:
...
I am trying to end a thread execution without directly referencing the thread. because it is not possible to do that in the full program.
for reference the main program is for the Raspberry Pi and I need it to stop executing a function/thread immediately once a button is pressed.
I have tried raising an exception from main but the other do not catch it for some reason.
Here is the scrap program that I have been testing on:
import threading
import time
class Thread_Exception(Exception):
def __init__(self, msg):
return super().__init__(msg)
def thread_function(index):
bool = True
try:
while bool:
print("Print from thread #", index)
time.sleep(4)
except Thread_Exception:
print('Exception thrown, thread #', index)
bool = False
if __name__ == "__main__":
try:
for index in range(3):
x = threading.Thread(target=thread_function, args=(index,))
x.start()
time.sleep(20)
raise Thread_Exception("intr")
while True:
continue
except KeyboardInterrupt:
print('Interrupted main')
an example of how it can be done:
import threading
import ctypes
import time
class thread_with_exception(threading.Thread):
def __init__(self, name):
threading.Thread.__init__(self)
self.name = name
def run(self):
# target function of the thread class
try:
while True:
print('running ' + self.name)
finally:
print('ended')
def get_id(self):
# returns id of the respective thread
if hasattr(self, '_thread_id'):
return self._thread_id
for id, thread in threading._active.items():
if thread is self:
return id
def raise_exception(self):
thread_id = self.get_id()
res = ctypes.pythonapi.PyThreadState_SetAsyncExc(thread_id,
ctypes.py_object(SystemExit))
if res > 1:
ctypes.pythonapi.PyThreadState_SetAsyncExc(thread_id, 0)
print('Exception raise failure')
t1 = thread_with_exception('Thread 1')
t1.start()
time.sleep(2)
t1.raise_exception()
t1.join()
The article this came from can currently be found here:
https://www.geeksforgeeks.org/python-different-ways-to-kill-a-thread/
I like the default python multiprocessing.Pool, but it's still a pain that it isn't easy to show the current progress being made during the pool's execution. In leui of that, I attempted to create my own, custom multiprocess pool mapper, and it looks like this;
from multiprocessing import Process, Pool, cpu_count
from iterable_queue import IterableQueue
def _proc_action(f, in_queue, out_queue):
try:
for val in in_queue:
out_queue.put(f(val))
except (KeyboardInterrupt, EOFError):
pass
def progress_pool_map(f, ls, n_procs=cpu_count()):
in_queue = IterableQueue()
out_queue = IterableQueue()
err = None
try:
procs = [Process(target=_proc_action, args=(f, in_queue, out_queue)) for _ in range(n_procs)]
[p.start() for p in procs]
for elem in ls:
in_queue.put(elem)
in_queue.close()
bar = 0
for _ in ls:
elem = next(out_queue)
bar += 1
if bar % 1000 == 0:
print(bar)
yield elem
out_queue.close()
except (KeyboardInterrupt, EOFError) as e:
in_queue.close()
out_queue.close()
print("Joining processes")
[p.join() for p in procs]
print("Closing processes")
[p.close() for p in procs]
err = e
if err:
raise err
It works fairly well, and prints a value to the console for every 1000 items processed. The progress display itself is something I can worry about in future. Right now, however, my issue is that when cancelled, the operation does anything but fail gracefully. When I try to interrupt the map, it hangs on Joining Processes, and never makes it to Closing Processes. If I try hitting Ctrl+C again, it causes an infinite spew of BrokenPipeErrors to fill the console until I send an EOF and stop my program.
Here's iterable_queue.py, for reference;
from multiprocessing.queues import Queue
from multiprocessing import get_context, Value
import queue
class QueueClosed(Exception):
pass
class IterableQueue(Queue):
def __init__(self, maxsize=0, *, ctx=None):
super().__init__(
maxsize=maxsize,
ctx=ctx if ctx is not None else get_context()
)
self.closed = Value('b', False)
def close(self):
with self.closed.get_lock():
if not self.closed.value:
self.closed.value = True
super().put((None, False))
# throws BrokenPipeError in another thread without this sleep in between
# terrible hack, must fix at some point
import time; time.sleep(0.01)
super().close()
def __iter__(self):
return self
def __next__(self):
try:
return self.get()
except QueueClosed:
raise StopIteration
def get(self, *args, **kwargs):
try:
result, is_open = super().get(*args, **kwargs)
except OSError:
raise QueueClosed
if not is_open:
super().put((None, False))
raise QueueClosed
return result
def __bool__(self):
return bool(self.closed.value)
def put(self, val, *args, **kwargs):
with self.closed.get_lock():
if self.closed.value:
raise QueueClosed
super().put((val, True), *args, **kwargs)
def get_nowait(self):
return self.get(block=False)
def put_nowait(self):
return self.put(block=False)
def empty_remaining(self, block=False):
try:
while True:
yield self.get(block=block)
except (queue.Empty, QueueClosed):
pass
def clear(self):
for _ in self.empty_remaining():
pass
def __enter__(self):
return self
def __exit__(self, *args):
self.close()
I'm having trouble with this error:
Exception in thread StompReceiverThread-1 (most likely raised during
interpreter shutdown):
That is no traceback at all.. just that.
Usualy everything works fine but rarely it happens and then the action does not conclude.
Any tips?
My code:
class Listener(stomp.ConnectionListener):
def __init__(self, conn, request):
self.conn = conn
self.request = request
def on_error(self, headers, message):
global WAITING_RESPONSE
print('received an error: ' + message)
WAITING_RESPONSE = False
def on_message(self, headers, message):
global WAITING_RESPONSE
try:
msg = json.loads(message)
if str(msg.get('transaction_id','')) == str(CURRENT_ID):
printDebugLine('Queue response:'+str(message))
manageQueueResponse(message,self.request)
WAITING_RESPONSE = False
self.conn.ack(headers['message-id'], '11')
except stomp.exception.ConnectFailedException:
print('Stomp error on message')
sys.exit(3)
except Exception as e:
print('ERROR: %s' % str(e))
sys.exit(3)
class Queue(object):
def __init__(self):
self.host = xx
self.port = xx
self.login = xx
self.passwd = xx
self.request = {}
self.start()
def start(self):
try:
self.conn = stomp.Connection(host_and_ports=[(self.host, self.port)])
self.conn.start()
self.conn.connect(self.login, self.passwd, wait=True)
self.conn.set_listener('xx', Listener(self.conn, self.request))
self.conn.subscribe(destination='xx', id='xx', ack='xx')
except stomp.exception.ConnectFailedException:
print('ERROR: unable to connect')
sys.exit(3)
except Exception as e:
print('ERROR: %s' % str(e))
sys.exit(3)
def send(self, data):
global CURRENT_ID
while WAITING_RESPONSE:
time.time(0.1)
try:
CURRENT_ID = str(uuid.uuid4())
data.update({'transaction_id': CURRENT_ID})
b = json.dumps(data)
self.request.update(data)
printDebugLine('Queue request:'+str(data))
self.conn.send(body=b, destination='xx')
timeout(data,self.request,29)
except stomp.exception.ConnectFailedException:
print('ERROR: unable to connect')
except Exception as e:
print('ERROR: %s' % str(e))
It looks like your main program is exiting, the interpreter is cleaning up things, but the stomp receiver thread was not shutdown first. The receiver thread goes to do something but basic modules are no longer available, so it gives an exception message, but cannot print a Traceback because that fuctionality is no longer available due to the program exiting.
Look at why the main program would be exiting.
Im using the following code to multithread urlib2. However what is the best way to limit the number of threads that it consumes ??
class ApiMultiThreadHelper:
def __init__(self,api_calls):
self.q = Queue.Queue()
self.api_datastore = {}
self.api_calls = api_calls
self.userpass = '#####'
def query_api(self,q,api_query):
self.q.put(self.issue_request(api_query))
def issue_request(self,api_query):
self.api_datastore.update({api_query:{}})
for lookup in ["call1","call2"]:
query = api_query+lookup
request = urllib2.Request(query)
request.add_header("Authorization", "Basic %s" % self.userpass)
f = urllib2.urlopen(request)
response = f.read()
f.close()
self.api_datastore[api_query].update({lookup:response})
return True
def go(self):
threads = []
for i in self.api_calls:
t = threading.Thread(target=self.query_api, args = (self.q,i))
t.start()
threads.append(t)
for t in threads:
t.join()
You should use a thread pool. Here's my implementation I've made years ago (Python 3.x friendly):
import traceback
from threading import Thread
try:
import queue as Queue # Python3.x
except ImportError:
import Queue
class ThreadPool(object):
def __init__(self, no=10):
self.alive = True
self.tasks = Queue.Queue()
self.threads = []
for _ in range(no):
t = Thread(target=self.worker)
t.start()
self.threads.append(t)
def worker(self):
while self.alive:
try:
fn, args, kwargs = self.tasks.get(timeout=0.5)
except Queue.Empty:
continue
except ValueError:
self.tasks.task_done()
continue
try:
fn(*args, **kwargs)
except Exception:
# might wanna add some better error handling
traceback.print_exc()
self.tasks.task_done()
def add_job(self, fn, args=[], kwargs={}):
self.tasks.put((fn, args, kwargs))
def join(self):
self.tasks.join()
def deactivate(self):
self.alive = False
for t in self.threads:
t.join()
You can also find a similar class in multiprocessing.pool module (don't ask me why it is there). You can then refactor your code like this:
def go(self):
tp = ThreadPool(20) # <-- 20 thread workers
for i in self.api_calls:
tp.add_job(self.query_api, args=(self.q, i))
tp.join()
tp.deactivate()
Number of threads is now defined a priori.