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Python - Non-empty shared list on separate thread appears empty

I've two classes - MessageProducer and MessageConsumer.
MessageConsumer does the following:
receives messages and puts them in its message list "_unprocessed_msgs"
on a separate worker thread, moves the messages to internal list "_in_process_msgs"
on the worker thread, processes messages from "_in_process_msgs"
On my development environment, I'm facing issue with #2 above - after adding a message by performing step#1, when worker thread checks length of "_unprocessed_msgs", it gets it as zero.
When step #1 is repeated, the list properly shows 2 items on the thread on which the item was added. But in step #2, on worker thread, again the len(_unprocessed_msgs) returns zero.
Not sure why this is happening. Would really appreciate help any help on this.
I'm using Ubuntu 16.04 having Python 2.7.12.
Below is the sample source code. Please let me know if more information is required.
import threading
import time
class MessageConsumerThread(threading.Thread):
def __init__(self):
super(MessageConsumerThread, self).__init__()
self._unprocessed_msg_q = []
self._in_process_msg_q = []
self._lock = threading.Lock()
self._stop_processing = False
def start_msg_processing_thread(self):
self._stop_processing = False
self.start()
def stop_msg_processing_thread(self):
self._stop_processing = True
def receive_msg(self, msg):
with self._lock:
LOG.info("Before: MessageConsumerThread::receive_msg: "
"len(self._unprocessed_msg_q)=%s" %
len(self._unprocessed_msg_q))
self._unprocessed_msg_q.append(msg)
LOG.info("After: MessageConsumerThread::receive_msg: "
"len(self._unprocessed_msg_q)=%s" %
len(self._unprocessed_msg_q))
def _queue_unprocessed_msgs(self):
with self._lock:
LOG.info("MessageConsumerThread::_queue_unprocessed_msgs: "
"len(self._unprocessed_msg_q)=%s" %
len(self._unprocessed_msg_q))
if self._unprocessed_msg_q:
LOG.info("Moving messages from unprocessed to in_process queue")
self._in_process_msg_q += self._unprocessed_msg_q
self._unprocessed_msg_q = []
LOG.info("Moved messages from unprocessed to in_process queue")
def run(self):
while not self._stop_processing:
# Allow other threads to add messages to message queue
time.sleep(1)
# Move unprocessed listeners to in-process listener queue
self._queue_unprocessed_msgs()
# If nothing to process continue the loop
if not self._in_process_msg_q:
continue
for msg in self._in_process_msg_q:
self.consume_message(msg)
# Clean up processed messages
del self._in_process_msg_q[:]
def consume_message(self, msg):
print(msg)
class MessageProducerThread(threading.Thread):
def __init__(self, producer_id, msg_receiver):
super(MessageProducerThread, self).__init__()
self._producer_id = producer_id
self._msg_receiver = msg_receiver
def start_producing_msgs(self):
self.start()
def run(self):
for i in range(1,10):
msg = "From: %s; Message:%s" %(self._producer_id, i)
self._msg_receiver.receive_msg(msg)
def main():
msg_receiver_thread = MessageConsumerThread()
msg_receiver_thread.start_msg_processing_thread()
msg_producer_thread = MessageProducerThread(producer_id='Producer-01',
msg_receiver=msg_receiver_thread)
msg_producer_thread.start_producing_msgs()
msg_producer_thread.join()
msg_receiver_thread.stop_msg_processing_thread()
msg_receiver_thread.join()
if __name__ == '__main__':
main()
Following is the log the I get:
INFO: MessageConsumerThread::_queue_unprocessed_msgs: len(self._unprocessed_msg_q)=0
INFO: Before: MessageConsumerThread::receive_msg: len(self._unprocessed_msg_q)=0
INFO: After: MessageConsumerThread::receive_msg: **len(self._unprocessed_msg_q)=1**
INFO: MessageConsumerThread::_queue_unprocessed_msgs: **len(self._unprocessed_msg_q)=0**
INFO: MessageConsumerThread::_queue_unprocessed_msgs: len(self._unprocessed_msg_q)=0
INFO: Before: MessageConsumerThread::receive_msg: len(self._unprocessed_msg_q)=1
INFO: After: MessageConsumerThread::receive_msg: **len(self._unprocessed_msg_q)=2**
INFO: MessageConsumerThread::_queue_unprocessed_msgs: **len(self._unprocessed_msg_q)=0**

This is not a good desing for you application.
I spent some time trying to debug this - but threading code is naturally complicated, so we should try to descomplicate it, instead of getting it even more confure.
When I see threading code in Python, I usually see it written a in a procedural form: a normal function that is passed to threading.Thread as the target argument that drives each thread. That way, you don't need to write code for a new class that will have a single instance.
Another thing is that, although Python's global interpreter lock itself guarantees lists won't get corrupted if modified in two separate threads, lists are not a recomended "thread data passing" data structure. You probably should look at threading.Queue to do that
The thing is wrong in this code at first sight is probably not the cause of your problem due to your use of locks, but it might be. Instead of
self._unprocessed_msg_q = []
which will create a new list object, the other thread have momentarily no reference too (so it might write data to the old list), you should do:
self._unprocessed_msg_q[:] = []
Or just the del slice thing you do on the other method.
But to be on the safer side, and having mode maintanable and less surprising code, you really should change to a procedural approach there, assuming Python threading. Assume "Thread" is the "final" object that can do its thing, and then use Queues around:
# coding: utf-8
from __future__ import print_function
from __future__ import unicode_literals
from threading import Thread
try:
from queue import Queue, Empty
except ImportError:
from Queue import Queue, Empty
import time
import random
TERMINATE_SENTINEL = object()
NO_DATA_SENTINEL = object()
class Receiver(object):
def __init__(self, queue):
self.queue = queue
self.in_process = []
def receive_data(self, data):
self.in_process.append(data)
def consume_data(self):
print("received data:", self.in_process)
del self.in_process[:]
def receiver_loop(self):
queue = self.queue
while True:
try:
data = queue.get(block=False)
except Empty:
print("got no data from queue")
data = NO_DATA_SENTINEL
if data is TERMINATE_SENTINEL:
print("Got sentinel: exiting receiver loop")
break
self.receive_data(data)
time.sleep(random.uniform(0, 0.3))
if queue.empty():
# Only process data if we have nothing to receive right now:
self.consume_data()
print("sleeping receiver")
time.sleep(1)
if self.in_process:
self.consume_data()
def producer_loop(queue):
for i in range(10):
time.sleep(random.uniform(0.05, 0.4))
print("putting {0} in queue".format(i))
queue.put(i)
def main():
msg_queue = Queue()
msg_receiver_thread = Thread(target=Receiver(msg_queue).receiver_loop)
time.sleep(0.1)
msg_producer_thread = Thread(target=producer_loop, args=(msg_queue,))
msg_receiver_thread.start()
msg_producer_thread.start()
msg_producer_thread.join()
msg_queue.put(TERMINATE_SENTINEL)
msg_receiver_thread.join()
if __name__ == '__main__':
main()
note that since you want multiple methods in the recever thread to do things with data, I used a class - but it does not inherit from Thread, and does not have to worry about its workings. All its methods are called within the same thread: no need of locks, no worries about race conditions within the receiver class itself. For communicating outside the class, the Queue class is structured to handle any race conditions for us.
The producer loop, as it is just a dummy producer, has no need at all to be written in class form. But it would look just the same, if it had more methods.
(The random sleeps help visualize what would happen in "real world" message receiving)
Also, you might want to take a look at something like:
https://www.thoughtworks.com/insights/blog/composition-vs-inheritance-how-choose

Finally I was able to solve the issue. In the actual code, I've a Manager class that is responsible for instantiating MessageConsumerThread as its last thing in the initializer:
class Manager(object):
def __init__(self):
...
...
self._consumer = MessageConsumerThread(self)
self._consumer.start_msg_processing_thread()
The problem seems to be with passing 'self' in MessageConsumerThread initializer when Manager is still executing its initializer (eventhough those are last two steps). The moment I moved the creation of consumer out of initializer, consumer thread was able to see the elements in "_unprocessed_msg_q".
Please note that the issue is still not reproducible with the above sample code. It is manifesting itself in the production environment only. Without the above fix, I tried queue and dictionary as well but observed the same issue. After the fix, tried with queue and list and was able to successfully execute the code.
I really appreciate and thank #jsbueno and #ivan_pozdeev for their time and help! Community #stackoverflow is very helpful!

Passing data between separately running Python scripts

If I have a python script running (with full Tkinter GUI and everything) and I want to pass the live data it is gathering (stored internally in arrays and such) to another python script, what would be the best way of doing that?
I cannot simply import script A into script B as it will create a new instance of script A, rather than accessing any variables in the already running script A.
The only way I can think of doing it is by having script A write to a file, and then script B get the data from the file. This is less than ideal however as something bad might happen if script B tries to read a file that script A is already writing in. Also I am looking for a much faster speed to communication between the two programs.
EDIT:
Here are the examples as requested. I am aware why this doesn't work, but it is the basic premise of what needs to be achieved. My source code is very long and unfortunately confidential, so it is not going to help here. In summary, script A is running Tkinter and gathering data, while script B is views.py as a part of Django, but I'm hoping this can be achieved as a part of Python.
Script A
import time
i = 0
def return_data():
return i
if __name__ == "__main__":
while True:
i = i + 1
print i
time.sleep(.01)
Script B
import time
from scriptA import return_data
if __name__ == '__main__':
while True:
print return_data() # from script A
time.sleep(1)

you can use multiprocessing module to implement a Pipe between the two modules. Then you can start one of the modules as a Process and use the Pipe to communicate with it. The best part about using pipes is you can also pass python objects like dict,list through it.
Ex:
mp2.py:
from multiprocessing import Process,Queue,Pipe
from mp1 import f
if __name__ == '__main__':
parent_conn,child_conn = Pipe()
p = Process(target=f, args=(child_conn,))
p.start()
print(parent_conn.recv()) # prints "Hello"
mp1.py:
from multiprocessing import Process,Pipe
def f(child_conn):
msg = "Hello"
child_conn.send(msg)
child_conn.close()

If you wanna read and modify shared data, between 2 scripts, which run separately, a good solution is, take advantage of the python multiprocessing module, and use a Pipe() or a Queue() (see differences here). This way, you get to sync scripts, and avoid problems regarding concurrency and global variables (like what happens if both scripts wanna modify a variable at the same time).
As Akshay Apte said in his answer, the best part about using pipes/queues, is that you can pass python objects through them.
Also, there are methods to avoid waiting for data, if there hasn't been any passed yet (queue.empty() and pipeConn.poll()).
See an example using Queue() below:
# main.py
from multiprocessing import Process, Queue
from stage1 import Stage1
from stage2 import Stage2
s1= Stage1()
s2= Stage2()
# S1 to S2 communication
queueS1 = Queue() # s1.stage1() writes to queueS1
# S2 to S1 communication
queueS2 = Queue() # s2.stage2() writes to queueS2
# start s2 as another process
s2 = Process(target=s2.stage2, args=(queueS1, queueS2))
s2.daemon = True
s2.start() # Launch the stage2 process
s1.stage1(queueS1, queueS2) # start sending stuff from s1 to s2
s2.join() # wait till s2 daemon finishes
# stage1.py
import time
import random
class Stage1:
def stage1(self, queueS1, queueS2):
print("stage1")
lala = []
lis = [1, 2, 3, 4, 5]
for i in range(len(lis)):
# to avoid unnecessary waiting
if not queueS2.empty():
msg = queueS2.get() # get msg from s2
print("! ! ! stage1 RECEIVED from s2:", msg)
lala = [6, 7, 8] # now that a msg was received, further msgs will be different
time.sleep(1) # work
random.shuffle(lis)
queueS1.put(lis + lala)
queueS1.put('s1 is DONE')
# stage2.py
import time
class Stage2:
def stage2(self, queueS1, queueS2):
print("stage2")
while True:
msg = queueS1.get() # wait till there is a msg from s1
print("- - - stage2 RECEIVED from s1:", msg)
if msg == 's1 is DONE ':
break # ends loop
time.sleep(1) # work
queueS2.put("update lists")
EDIT: just found that you can use queue.get(False) to avoid blockage when receiving data. This way there's no need to check first if the queue is empty. This is no possible if you use pipes.

You could use the pickling module to pass data between two python programs.
import pickle
def storeData():
# initializing data to be stored in db
employee1 = {'key' : 'Engineer', 'name' : 'Harrison',
'age' : 21, 'pay' : 40000}
employee2 = {'key' : 'LeadDeveloper', 'name' : 'Jack',
'age' : 50, 'pay' : 50000}
# database
db = {}
db['employee1'] = employee1
db['employee2'] = employee2
# Its important to use binary mode
dbfile = open('examplePickle', 'ab')
# source, destination
pickle.dump(db, dbfile)
dbfile.close()
def loadData():
# for reading also binary mode is important
dbfile = open('examplePickle', 'rb')
db = pickle.load(dbfile)
for keys in db:
print(keys, '=>', db[keys])
dbfile.close()

This will pass data to and from two running scripts using TCP host socket. https://zeromq.org/languages/python/. required module zmq: use( pip install zmq ).
This this is called a client server communication. The server will wait for the client to send a request. The client will also not run if the server is not running. In addition, this client server communication allows for you to send a request from one device(client) to another device(server), as long as the client and server are on the same network and you change localhost (localhost for the server is marked with: * )to the actual IP of your device(server)( IP help( go into your device network settings, click on your network icon, find advanced or properties, look for IP address. note this may be different from going to google and asking for your ip. I am using IPV6 so. DDOS protection.)) Change the localhost IP of the client to the server IP. QUESTION to OP. Do you have to have script b always running or can script b be imported as a module to script a? If so look up how to make python modules.

I solved the same problem using the lib Shared Memory Dict, it's a very simple dict implementation of multiprocessing.shared_memory.
Source1.py
from shared_memory_dict import SharedMemoryDict
from time import sleep
smd_config = SharedMemoryDict(name='config', size=1024)
if __name__ == "__main__":
smd_config["status"] = True
while True:
smd_config["status"] = not smd_config["status"]
sleep(1)
Source2.py
from shared_memory_dict import SharedMemoryDict
from time import sleep
smd_config = SharedMemoryDict(name='config', size=1024)
if __name__ == "__main__":
while True:
print(smd_config["status"])
sleep(1)

Win32com events not raising inside thread?

I am new to both COM and Python, so im not very familiar with exact terminologies. So apologies for using inexact terms.
I am trying to connect to a desktop application via a proprietary COM interface using pywin32.
I created a PoC and it runs fine. The COM function call is processed and I get the expected event.
class MyEvents:
def __init__(self):
print("Callback class initialized")
def OnMyEvent(self, data):
print('MyEvent raised')
class ComUser:
comObj = None
def __init__(self):
comObj = win32com.client.DispatchWithEvents("ProproetaryInterface.InterfaceClass",
MyEvents)
comObj.Register()
comObj.DoSomething(data)
time.sleep(120)
userObj = ComUser()
So far so good. I get the event on the screen
Callback class initialized
MyEvent raised
Next I tried to put it into my application where I have multiple threads. To explain it in simple terms:
Main creates an object of Class X which initializes an XMLRPC Server thread.
The XMLRPC handler simply takes incoming info and puts it into a queue
The queue is from multiprocessing lib.
Another thread waits on this queue for an incoming message
def __startPollingThread(self):
pythoncom.CoInitialize()
pollingThread = Thread(target=self.__checkQueue )
pollingThread.start()
pythoncom.CoUninitialize()
This is the polling thread method:
def __checkQueue(self):
try:
pythoncom.CoInitialize()
while True:
currMessage = self.__messageQueue.get()
self.__processMessage(currMessage);
except :
#Log message
finally:
pythoncom.CoUninitialize()
The __processMessage passes through multliple classes (something like a strategy pattern + state pattern) before it hits the class that handles COM interface.
In the ComUser class, i have a method which registers with the client application's com interface:
def initSystem(self):
import pythoncom
try:
pythoncom.CoInitialize()
self.ComConnector = win32com.client.DispatchWithEvents("ProprietaryInterface.InterfaceClass",
MyEvents)
self.ComConnector.Register()
except:
finally:
pythoncom.CoUninitialize()
Another method handles the specific requests as they arrive and makes the corresponding COM calls.
def handleMessage(self, message):
#if message = this then
comObj.DoSomething(data)
Both methods are called from the __processMessage method. All my classes reside in separate Py files. Except ComUser and MyEvents which are in same py module
I can call the Com Interface and see the Application reacting to the COM method calls but I cant see any events being raised. I have tried a whole lot of combinations of CoInitialize and Uninitialze and "import pythoncom" statements to ensure that it is not a problem with the threading. Also tried setting the sys.coinit_flags = 0 and checked. Seems to make no difference. I just dont see any events.
Is it a problem that I call DispatchWithEvents in a child thread instead of the main thread(The calls seem to work fine) ? Or is it that the main thread (ie main method of the program) dies out. I tried putting a long sleep there too. I even tried a separate thread with PumpWaitingMessages loop but it made no difference. I cant think of any solutions.

Stopping task.LoopingCall if exception occurs

I'm new to Twisted and after finally figuring out how the deferreds work I'm struggling with the tasks. What I want to achieve is to have a script that sends a REST request in a loop, however if at some point it fails I want to stop the loop. Since I'm using callbacks I can't easily catch exceptions and because I don't know how to stop the looping from an errback I'm stuck.
This is the simplified version of my code:
def send_request():
agent = Agent(reactor)
req_result = agent.request('GET', some_rest_link)
req_result.addCallbacks(cp_process_request, cb_process_error)
if __name__ == "__main__":
list_call = task.LoopingCall(send_request)
list_call.start(2)
reactor.run()

To end a task.LoopingCall all you need to do is call the stop on the return object (list_call in your case).
Somehow you need to make that var available to your errback (cb_process_error) either by pushing it into a class that cb_process_error is in, via some other class used as a pseudo-global or by literally using a global, then you simply call list_call.stop() inside the errback.
BTW you said:
Since I'm using callbacks I can't easily catch exceptions
Thats not really true. The point of an errback to to deal with exceptions, thats one of the things that literally causes it to be called! Check out my previous deferred answer and see if it makes errbacks any clearer.
The following is a runnable example (... I'm not saying this is the best way to do it, just that it is a way...)
#!/usr/bin/python
from twisted.internet import task
from twisted.internet import reactor
from twisted.internet.defer import Deferred
from twisted.web.client import Agent
from pprint import pprint
class LoopingStuff (object):
def cp_process_request(self, return_obj):
print "In callback"
pprint (return_obj)
def cb_process_error(self, return_obj):
print "In Errorback"
pprint(return_obj)
self.loopstopper()
def send_request(self):
agent = Agent(reactor)
req_result = agent.request('GET', 'http://google.com')
req_result.addCallbacks(self.cp_process_request, self.cb_process_error)
def main():
looping_stuff_holder = LoopingStuff()
list_call = task.LoopingCall(looping_stuff_holder.send_request)
looping_stuff_holder.loopstopper = list_call.stop
list_call.start(2)
reactor.callLater(10, reactor.stop)
reactor.run()
if __name__ == '__main__':
main()
Assuming you can get to google.com this will fetch pages for 10 seconds, if you change the second arg of the agent.request to something like http://127.0.0.1:12999 (assuming that port 12999 will give a connection refused) then you'll see 1 errback printout (which will have also shutdown the loopingcall) and have a 10 second wait until the reactor shuts down.

Least painful way to run a Python delay loop

I've got an event-driven chatbot and I'm trying to implement spam protection. I want to silence a user who is behaving badly for a period of time, without blocking the rest of the application.
Here's what doesn't work:
if user_behaving_badly():
ban( user )
time.sleep( penalty_duration ) # Bad! Blocks the entire application!
unban( user )
Ideally, if user_behaving_badly() is true, I want to start a new thread which does nothing but ban the user, then sleep for a while, unban the user, and then the thread disappears.
According to this I can accomplish my goal using the following:
if user_behaving_badly():
thread.start_new_thread( banSleepUnban, ( user, penalty ) )
"Simple" is usually an indicator of "good", and this is pretty simple, but everything I've heard about threads has said that they can bite you in unexpected ways. My question is: Is there a better way than this to run a simple delay loop without blocking the rest of the application?

instead of starting a thread for each ban, put the bans in a priority queue and have a single thread do the sleeping and unbanning
this code keeps two structures a heapq that allows it to quickly find the soonest ban to expire and a dict to make it possible to quickly check if a user is banned by name
import time
import threading
import heapq
class Bans():
def __init__(self):
self.lock = threading.Lock()
self.event = threading.Event()
self.heap = []
self.dict = {}
self.thread = threading.thread(target=self.expiration_thread)
self.thread.setDaemon(True)
self.thread.start()
def ban_user(self, name, duration):
with self.lock:
now = time.time()
expiration = (now+duration)
heapq.heappush(self.heap, (expiration, user))
self.dict[user] = expiration
self.event.set()
def is_user_banned(self, user):
with self.lock:
now = time.time()
return self.dict.get(user, None) > now
def expiration_thread(self):
while True:
self.event.wait()
with self.lock:
next, user = self.heap[0]
now = time.time()
duration = next-now
if duration > 0:
time.sleep(duration)
with self.lock:
if self.heap[0][0] = next:
heapq.heappop(self.heap)
del self.dict(user)
if not self.heap:
self.event.clear()
and is used like this:
B = Bans()
B.ban_user("phil", 30.0)
B.is_user_banned("phil")

Use a threading timer object, like this:
t = threading.Timer(30.0, unban)
t.start() # after 30 seconds, unban will be run
Then only unban is run in the thread.

Why thread at all?
do_something(user):
if(good_user(user)):
# do it
else
# don't
good_user():
if(is_user_baned(user)):
if(past_time_since_ban(user)):
user_good_user(user)
elif(is_user_bad()):
ban_user()
ban_user(user):
# add a user/start time to a hash
is_user_banned()
# check hash
# could check if expired now too, or do it seperately if you care about it
is_user_bad()
# check params or set more values in a hash

This is language agnostic, but consider a thread to keep track of stuff. The thread keeps a data structure that has something like "username" and "banned_until" in a table. The thread is always running in the background checking the table, if banned_until is expired, it unblocks the user. Other threads go on normally.

If you're using a GUI,
most GUI modules have a timer function which can abstract all the yuck multithreading stuff,
and execute code after a given time,
though still allowing the rest of the code to be executed.
For instance, Tkinter has the 'after' function.