What is the meaning of bind=True in below celery code? When to use it and when not?
#app.task(bind=True)
def send_twitter_status(self, oauth, tweet):
try:
twitter = Twitter(oauth)
twitter.update_status(tweet)
except (Twitter.FailWhaleError, Twitter.LoginError) as exc:
raise self.retry(exc=exc)
Just a small addition to other answers. As already stated, bound tasks have access to the task instance. One use case when this is needed are retries:
#celery.task(bind=True, max_retries=5)
def retrying(self):
try:
return 1/0
except Exception:
self.retry(countdown=5)
Another use case is when you want to define custom states for your tasks and be able to set it during task execution:
#celery.task(bind=True)
def show_progress(self, n):
for i in range(n):
self.update_state(state='PROGRESS', meta={'current': i, 'total': n})
Bound tasks
A task being bound means the first argument to the task will always be the task instance (self), just like Python bound methods:
logger = get_task_logger(__name__)
#task(bind=True)
def add(self, x, y):
logger.info(self.request.id)
The bind argument means that the function will be a “bound method” so that you can access attributes and methods on the task type instance.
See the docs
Related
In a custom class I have the following code:
class CustomClass():
triggerQueue: multiprocessing.Queue
def __init__(self):
self.triggerQueue = multiprocessing.Queue()
def poolFunc(queueString):
print(queueString)
def listenerFunc(self):
pool = multiprocessing.Pool(5)
while True:
try:
queueString = self.triggerQueue.get_nowait()
pool.apply_async(func=self.poolFunc, args=(queueString,))
except queue.Empty:
break
What I intend to do is:
add a trigger to the queue (not implemented in this snippet) -> works as intended
run an endless loop within the listenerFunc that reads all triggers from the queue (if any are found) -> works as intended
pass trigger to poolFunc which is to be executed asynchronosly -> not working
It works as soon as I source my poolFun() outside of the class like
def poolFunc(queueString):
print(queueString)
class CustomClass():
[...]
But why is that so? Do I have to pass the self argument somehow? Is it impossible to perform it this way in general?
Thank you for any hint!
There are several problems going on here.
Your instance method, poolFunc, is missing a self parameter.
You are never properly terminating the Pool. You should take advantage of the fact that a multiprocessing.Pool object is a context manager.
You're calling apply_async, but you're never waiting for the results. Read the documentation: you need to call the get method on the AsyncResult object to receive the result; if you don't do this before your program exits your poolFunc function may never run.
By making the Queue object part of your class, you won't be able to pass instance methods to workers.
We can fix all of the above like this:
import multiprocessing
import queue
triggerQueue = multiprocessing.Queue()
class CustomClass:
def poolFunc(self, queueString):
print(queueString)
def listenerFunc(self):
results = []
with multiprocessing.Pool(5) as pool:
while True:
try:
queueString = triggerQueue.get_nowait()
results.append(pool.apply_async(self.poolFunc, (queueString,)))
except queue.Empty:
break
for res in results:
print(res.get())
c = CustomClass()
for i in range(10):
triggerQueue.put(f"testval{i}")
c.listenerFunc()
You can, as you mention, also replace your instance method with a static method, in which case we can keep triggerQueue as part of the class:
import multiprocessing
import queue
class CustomClass:
def __init__(self):
self.triggerQueue = multiprocessing.Queue()
#staticmethod
def poolFunc(queueString):
print(queueString)
def listenerFunc(self):
results = []
with multiprocessing.Pool(5) as pool:
while True:
try:
queueString = self.triggerQueue.get_nowait()
results.append(pool.apply_async(self.poolFunc, (queueString,)))
except queue.Empty:
break
for r in results:
print(r.get())
c = CustomClass()
for i in range(10):
c.triggerQueue.put(f"testval{i}")
c.listenerFunc()
But we still need to reap the pool_async results.
Okay, I found an answer and a workaround:
the answer is based the anser of noxdafox to this question.
Instance methods cannot be serialized that easily. What the Pickle protocol does when serialising a function is simply turning it into a string.
For a child process would be quite hard to find the right object your instance method is referring to due to separate process address spaces.
A functioning workaround is to declare the poolFunc() as static function like
#staticmethod
def poolFunc(queueString):
print(queueString)
I am trying to build some UI panels for an Eclipse based tool. The API for the tool has a mechanism for event handling based on decorators, so for example, the following ties callbackOpen to the opening of a_panel_object:
#panelOpenHandler(a_panel_object)
def callbackOpen(event):
print "opening HERE!!"
This works fine, but I wanted to wrap all of my event handlers and actual data processing for the panel behind a class. Ideally I would like to do something like:
class Test(object):
def __init__(self):
# initialise some data here
#panelOpenHandler(a_panel_object)
def callbackOpen(self, event):
print "opening HERE!!"
But this doesn't work, I think probably because I am giving it a callback that takes both self and event, when the decorator is only supplying event when it calls the function internally (note: I have no access to source code on panelOpenHandler, and it is not very well documented...also, any error messages are getting swallowed by Eclipse / jython somewhere).
Is there any way that I can use a library decorator that provides one argument to the function being decorated on a function that takes more than one argument? Can I use lambdas in some way to bind the self argument and make it implicit?
I've tried to incorporate some variation of the approaches here and here, but I don't think that it's quite the same problem.
Your decorator apparently registers a function to be called later. As such, it's completely inappropriate for use on a class method, since it will have no idea of which instance of the class to invoke the method on.
The only way you'd be able to do this would be to manually register a bound method from a particular class instance - this cannot be done using the decorator syntax. For example, put this somewhere after the definition of your class:
panelOpenHandler(context.controls.PerformanceTuneDemoPanel)(Test().callbackOpen)
I found a work around for this problem. I'm not sure if there is a more elegant solution, but basically the problem boiled down to having to expose a callback function to global() scope, and then decorate it with the API decorator using f()(g) syntax.
Therefore, I wrote a base class (CallbackRegisterer), which offers the bindHandler() method to any derived classes - this method wraps a function and gives it a unique id per instance of CallbackRegisterer (I am opening a number of UI Panels at the same time):
class CallbackRegisterer(object):
__count = 0
#classmethod
def _instanceCounter(cls):
CallbackRegisterer.__count += 1
return CallbackRegisterer.__count
def __init__(self):
"""
Constructor
#param eq_instance 0=playback 1=record 2=sidetone.
"""
self._id = self._instanceCounter()
print "instantiating #%d instance of %s" % (self._id, self._getClassName())
def bindHandler(self, ui_element, callback, callback_args = [], handler_type = None,
initialize = False, forward_event_args = False, handler_id = None):
proxy = lambda *args: self._handlerProxy(callback, args, callback_args, forward_event_args)
handler_name = callback.__name__ + "_" + str(self._id)
if handler_id is not None:
handler_name += "_" + str(handler_id)
globals()[handler_name] = proxy
# print "handler_name: %s" % handler_name
handler_type(ui_element)(proxy)
if initialize:
proxy()
def _handlerProxy(self, callback, event_args, callback_args, forward_event_args):
try:
if forward_event_args:
new_args = [x for x in event_args]
new_args.extend(callback_args)
callback(*new_args)
else:
callback(*callback_args)
except:
print "exception in callback???"
self.log.exception('In event callback')
raise
def _getClassName(self):
return self.__class__.__name__
I can then derive a class from this and pass in my callback, which will be correctly decorated using the API decorator:
class Panel(CallbackRegisterer):
def __init__(self):
super(Panel, self).__init__()
# can bind from sub classes of Panel as well - different class name in handle_name
self.bindHandler(self.controls.test_button, self._testButtonCB, handler_type = valueChangeHandler)
# can bind multiple versions of same function for repeated ui elements, etc.
for idx in range(0, 10):
self.bindHandler(self.controls["check_box_"+str(idx)], self._testCheckBoxCB,
callback_args = [idx], handler_type = valueChangeHandler, handler_id = idx)
def _testCheckBoxCB(self, *args):
check_box_id = args[0]
print "in _testCheckBoxCB #%d" % check_box_id
def _testButtonCB(self):
"""
Handler for test button
"""
print "in _testButtonCB"
panel = Panel()
Note, that I can also derive further sub-classes from Panel, and any callbacks bound there will get their own unique handler_name, based on class name string.
I'm trying to create some celery tasks as classes, but am having some difficulty. The classes are:
class BaseCeleryTask(app.Task):
def is_complete(self):
""" default method for checking if celery task has completed. """
# simply return result (since by default tasks return boolean indicating completion)
try:
return self.result
except AttributeError:
logger.error('Result not defined. Make sure task has run!')
return False
class MacroReportTask(BaseCeleryTask):
def run(self, params):
""" Override the default run method with signal factory run"""
# hold on to the factory
process = MacroCountryReport(params)
self.result = process.run()
return self.result
but when I initialize the app, and check app.tasks (or run worker), app doesn't seem to have these above tasks in its registry. Other function based tasks (using app.task() decorator) seem to be registered fine.
I run the above task as:
process = SignalFactoryTask()
process.delay(params)
Celery worker errors with the following message:
Received unregistered task of type None.
I think the issue I'm having is: how do I add custom classes to the task registry as I do with regular function based tasks?
Ran into the exact same issue, took hours to find the solution cause I'm 90% sure it's a bug. In your class tasks, try the following
class BaseCeleryTask(app.Task):
def __init__(self):
self.name = "[modulename].BaseCeleryTask"
class MacroReportTask(app.Task):
def __init__(self):
self.name = "[modulename].MacroReportTask"
It seems registering it with the app still has a bug where the name isn't automatically configured. Let me know if that works.
I'm trying to switch MongoEngine with MotorEngine in my Tornado app for the sake of asynchronous DB access and so far I got nowhere.
query
#gen.coroutine
def get_all_users(self):
users = yield User.objects.find_all()
handler
class IUser(BaseHandler):
#asynchronous
#gen.engine
def get(self,userId=None, *args, **kwargs):
try:
userMethods = UserMethods()
sessionId = self.request.headers.get('sessionId')
ret = userMethods.get_all_users()
except Exception as ex:
print str(ex)
self.finish()
When I print ret variable it says <tornado.concurrent.Future object at 0x7fb0236fe450>. If I try to print ret.result() it gets me nowhere.
Any help is appreciated since I'm struggling with everything I guess...
get_all_users needs to return its value somehow. In Python 2.6 or 2.7, generators aren't allowed to use the "return" statement, so coroutines have a special "Return" exception:
#gen.coroutine
def get_all_users(self):
users = yield User.objects.find_all()
raise gen.Return(users)
In Python 3.3 and later, you can simply "return users".
Now in "get", calling "get_all_users" only gives you a pending Future, not a value. You must wait for the Future to resolve to a value by yielding it:
ret = yield userMethods.get_all_users()
For more about calling coroutines from coroutines, see my "Refactoring Tornado Coroutines".
By the way, you can decorate "get" with just "gen.coroutine", it's more modern than "asynchronous" and "gen.engine", but either style works.
Just a suggestion. If you want to avoid to create an instance of userMethods every time you use its method:
userMethods = UserMethods()
You can use the #classmethod decorator before declaring it:
class UserMethods():
pass
#classmethod
#tornado.gen.coroutine
def get_all_users(self):
users = yield User.objects.find_all()
raise gen.Return(users)
## class IUser
...
try:
# userMethods = UserMethods() --not necesary now--
sessionId = self.request.headers.get('sessionId')
ret = yield userMethods.get_all_users()
except Exception as ex:
print str(ex)
...
I'm having a task that looks like this
from mybasetask_module import MyBaseTask
#task(base=MyBaseTask)
#my_custom_decorator
def my_task(*args, **kwargs):
pass
and my base task looks like this
from celery import task, Task
class MyBaseTask(Task):
abstract = True
default_retry_delay = 10
max_retries = 3
acks_late = True
The problem I'm running into is that the celery worker is registering the task with the name
'mybasetask_module.__inner'
The task is registerd fine (which is the package+module+function) when I remove #my_custom_decorator from the task or if I provide an explicit name to the task like this
from mybasetask_module import MyBaseTask
#task(base=MyBaseTask, name='an_explicit_task_name')
#my_custom_decorator
def my_task(*args, **kwargs):
pass
Is this behavior expected? Do I need to do something so that my tasks are registered with the default auto registered name in the first case when I have multiple decorators but no explicit task name?
Thanks,
Use the functools.wraps() decorator to ensure that the wrapper returned by my_custom_decorator has the correct name:
from functools import wraps
def my_custom_decorator(func):
#wraps(func)
def __inner():
return func()
return __inner
The task name is taken from the function call that the task decorator wraps, but by inserting a decorator in between, you gave task your __inner wrapping function instead. The functools.wraps() decorator copies all the necessary metadata over from func to the wrapper so that task() can pick up the proper name.