multithreading

问题 In threading, we have something called "Thread Context", in which we can save some data (state) for accessing in a special thread. In asyncio, I need to save some state in current execution path, so that all consequent coroutines can access it. What is the solution? Note: I know each coroutine function is instantiated for an execution path in asyncio, but for some reason I can not save the state in function properties. (Although this method os not very good anyway) 回答1: As of Python 3.7 you

问题 I'm trying to develop a software with PyQt, but I often get stuck on software crashes without debug information (only the exit code 0xC0000409). I'm using QThread, and I wrote a system like this: class serialThreadC(QThread): updateOutBox = QtCore.pyqtSignal(str) updateStatus = QtCore.pyqtSignal(int) def __init__(self): super(serialThreadC, self).__init__() self.ser = False self.state = 0 self.serialEnabled = False def run(self): while True: if self.state == -3 or self.state == -2: if self

问题 system() function is implemented by using fork() , execve() and wait() functions. I have heard that fork() function is dangerous in multi-threaded programs. So, is the system() function also dangerous in multi-threaded programs? What problems it may cause? 回答1: fork is dangerous in threaded programs unless followed by execve . Since only the current thread is forked there's very little you can do in a forked multi-threaded program other than execve . You should probably make sure you're not

问题 system() function is implemented by using fork() , execve() and wait() functions. I have heard that fork() function is dangerous in multi-threaded programs. So, is the system() function also dangerous in multi-threaded programs? What problems it may cause? 回答1: fork is dangerous in threaded programs unless followed by execve . Since only the current thread is forked there's very little you can do in a forked multi-threaded program other than execve . You should probably make sure you're not

问题 This is an interview question . In general the deadlock between 2 threads is generated when thread1 locks mutex1,and a moment before it tries to lock mutex2 ,thread 2 locks mutex2.After that tread 2 wants to lock mutex1.So they wait for each other forever. The question was "Can you gave a scenario of deadlock with one mutex and any number of threads?" 回答1: It depends on how you define "deadlock" I guess, but I could see one possibility: Thread A grabs the mutex Thread B waits for mutex Thread

问题 This is an interview question . In general the deadlock between 2 threads is generated when thread1 locks mutex1,and a moment before it tries to lock mutex2 ,thread 2 locks mutex2.After that tread 2 wants to lock mutex1.So they wait for each other forever. The question was "Can you gave a scenario of deadlock with one mutex and any number of threads?" 回答1: It depends on how you define "deadlock" I guess, but I could see one possibility: Thread A grabs the mutex Thread B waits for mutex Thread

问题 On a console application, i am currently starting an array of threads. The thread is passed an object and running a method in it. I would like to know how to call a method on the object inside the individual running threads. Dispatcher doesn't work. SynchronizationContext "Send" runs on the calling thread and "Post" uses a new thread. I would like to be able to call the method and pass parameters on a running thread on the target thread it's running on and not the calling thread. Update 2:

问题 On a console application, i am currently starting an array of threads. The thread is passed an object and running a method in it. I would like to know how to call a method on the object inside the individual running threads. Dispatcher doesn't work. SynchronizationContext "Send" runs on the calling thread and "Post" uses a new thread. I would like to be able to call the method and pass parameters on a running thread on the target thread it's running on and not the calling thread. Update 2:

问题 At this moment I have a webpage in which a long list of Axios POST calls are being made. Now, the requests seem to be sent in parallel (JavaScript continues sending the next request before the result is received). However, the results seem to be returned one by one, not simultaneously. Let's say one POST call to the PHP script takes 4 seconds and I need to make 10 calls. It would currently take 4 seconds per call, which would be 40 seconds in total. I hope to find a solution to both and

问题 At this moment I have a webpage in which a long list of Axios POST calls are being made. Now, the requests seem to be sent in parallel (JavaScript continues sending the next request before the result is received). However, the results seem to be returned one by one, not simultaneously. Let's say one POST call to the PHP script takes 4 seconds and I need to make 10 calls. It would currently take 4 seconds per call, which would be 40 seconds in total. I hope to find a solution to both and