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Also, why do you want the main thread to keep looping? Also confirm that PThreads supports this use case fully; I worry it may not. Using the Python methods, this is pretty simple: from threading import Thread, Lock mutex = Lock() def processData(data): mutex.acquire() try: print('Do some stuff') finally: mutex.release() while True: t = Thread(target = processData, args = (some_data,)) t.start() Free 30 Day Trial Please note that this class is deprecated (in Python 3.0) and should be avoided. but hey, that's why I am here asking for help.I don't know why you're using the Window's Mutex instead of Python's.

If the print statement throws an Exception, you'll never release the mutex. An asyncio lock can be used to guarantee exclusive access to a shared resource.

Private self-hosted questions and answers for your enterpriseProgramming and related technical career opportunitiesNot all systems have /tmp in tmpfs ramdisk either; my install of OS X does not seem to. To solve your race condition above, you need to find a way to allow only one thread at a time into the read-modify-write section of your code. would this algorithm be the right usage of a Mutex? In your proof of concept each process is constructing a My answer overlaps with the other answers, but just to add something people can copy-paste, I often do something like this.For a system-wide mutex that enables the synchronization of absolutely separate processes (i.e., to INCLUDE Linux processes that do NOT belong to the same processes tree), simply use Thanks for contributing an answer to Stack Overflow! @Marcelo Cantos, sorry you are probably right. Stack Overflow for Teams is a private, secure spot for you and Stack Overflow for Teams is a private, secure spot for you and Good points all the same, though.My Debian Squeeze install doesn't have a tmpfs /tmp either. The preferred way to use a Lock is an async with statement: The Overflow Blog POSIX_IPC was the easiest solution by far.

@Richard: Why do you want to use threads if you plan to serialise all processing anyway? if you're manipulating large matrices in numpy) because the GIL is unlocked during those calls.There's a potential deadlock. I don't know why you're using the Window's Mutex instead of Python's.
My use case is different, as there is no master process spawning subprocesses. The mutex module defines a class that allows mutual-exclusion via acquiring and releasing locks. In my case: 2-3-4 python programs (the same progam, started 2-3-4 times with different parameters) - and they have to use a non-thread safe resource. Is there any easy way to have a system-wide mutex in Python on Linux? The python equivalent is fcntl.lockf.. You win some, you lose some.The POSIX standard specifies inter-process semaphores which can be used for this purpose. There may be no Python API for this; if not you may have to go native. Featured on Meta A mutex has two pieces of state — a “locked” bit and a queue. The "traditional" Unix answer is to use file locks. It's actually got tmpfs on /dev/shm, which feature I've also seen on Fedora.

But they require support from whatever makes the resource available - most commonly, the file system - where cooperative locking doesn't. @Marcelo Cantos, This is not my actual program. If you then also add a TemporaryFileRLock (which is a matter of 10 lines), the need for maintaining a separate library would probably go away. Free 30 Day Trial Stack Overflow works best with JavaScript enabled Perhaps you are looking for something like 1. https://pypi.python.org/pypi/pid/2.1.1 2. https://docs.python.org/3.6/library/msvcrt.html#msvcrt.locking 3. or https://docs.python.org/3/library/fcntl.html#fcntl.flock Instead, neither hangs; it appears they aren't acquiring the same mutex.The "traditional" Unix answer is to use file locks. Stack Overflow works best with JavaScript enabled your coworkers to find and share information. The mutex module defines the following class:. What's wrong with a simple loop? You can use Traditionally you write the PID of the locking process into the lock file, so that deadlocks due to processes dying while holding the lock are identifiable and fixable.This gets you what you want, since your lock is in a global namespace (the filesystem) and accessible to all processes. Edit: re-reading my code I can see that it is grossly wrong. In my case, each process is invoked completely independently, but they must still coordinate.Shared memory with a configured numeric address may be the only option if there is no relationship between peers but they still need a shared mutex. Create a new (unlocked) mutex. It makes sure that one thread can access a particular resource at a time and it also prevents the use of objects and bytecodes at once.

You need to use Also, there's no need to pass the mutex as an argument to the function. It will just burn CPU, possibly starving other threads. I also want to avoid something with greater privileges coming and writing the file before any workers start, potentially denying them access. Also, to me this is a design smell; it seems like you should be either using threads and mutexes, or a separate process like redis or riak to arbitrate.@KT. TemporaryFileLock has race issues. A lock and a mutex are often used interchangeably however in Python the mutex is a module that defines a class to allow mutual exclusion by acquiring and releasing a lock object. No file-system affected things are needed. I've written a number of cooperative locking systems in the past (eg to protect a network resource, when the mounted file system didn't offer the sort of locking I needed), and they're usually the way to go when there's anything complicated going on. Lock¶ class asyncio.Lock (*, loop=None) ¶ Implements a mutex lock for asyncio tasks. By clicking “Post Your Answer”, you agree to our To subscribe to this RSS feed, copy and paste this URL into your RSS reader. In some other languages this same idea is called a mutex. I just want processData to run in a thread (one at time) and the main while loop to keep running, even if there is a thread in queue.

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