I built a web-scraper application with Python. It consists of three main parts:
The GUI (built on tkinter)
A Client (controls interface between front- and back-end)
Back-end code (various threaded processes).
The problem I have is that when the user hits X to exit the program instead of quitting through the interface, it seems like root.destroy() never gets called and the application runs forever, even though the window does disappear. This ends up consuming vast amounts of system resources.
I have tried setting all threads to Daemon without much success. Is there any other reason the program would keep eating up CPU after exit?
You don't want to set all threads to daemon. You want to set the client thread and the back-end thread to daemon. That way, when the GUI thread dies, the threads with daemon set to True end as well.
From the documentation:
A thread can be flagged as a “daemon thread”. The significance of this flag is that the entire Python program exits when only daemon threads are left.
Related
I'm setting up a multithreaded python server, and I want to remove threads that have been inactive for n seconds.
The approach I can think of for this situation is that, you must have a daemon that would handle such threads. As much as possible, those threads should have been spawned by that daemon for easier thread tracking, as well as handling the timer for such threads.
If this is not the case (a separate program spawned the thread), you must have established a naming (or tracking) standard enabling you to determine which threads are under your program's scope, so they can be terminated by the daemon accordingly.
We are using python multithreading(I/O bound) for our application deployments. From main/parent thread we are creating multiple child threads (multiple hosts [application/web] for deployment within each thread) and waiting for them to finish using .join() in main thread. We are also using some Fabric package commands to ask user input whether to proceed with deployment or not in-case of an error for whatsoever reason.
Problem statement:
Since we are using multithreading, all the child threads are writing the messages to terminal (stdout)output and thus the errors from one thread on the screen are overlapping by other thread messages and it is difficult to comb through the console/terminal to see what thread has failures.
What could be the best way to gather all the failure steps in the deployment from all the threads collectively and display all of them at once on the console/terminal output ?
The difficulty I'm facing is how to interact with child threads while in main thread we are just waiting to finish them (if there are any fabric user interactive questions then will type y/n based on our decision about the failure).
I am using QThread to do some calculations in a separate Thread.
The Thread gets started by a button click, witch launches the function StartMeasurement().
The Thread can finish the process by itself (after finished the calculations)
and emits the PyQT Signal finished. Or the thread can be stopped by the User by the stopBtn click.
The terminate() function is working, but I get a lot of troubles when I try to start the thread again.
Is it recommendable to use the movetoThread() approach here?
Or how could I ensure that the thread is stopped correctly to enable a proper restart. (means, starting new!)
# starts the measurment in a Thread: StartMeasurement()
def StartMeasurement(self):
self.thread = measure.CMeasurementThread(self.osziObj, self.genObj, self.measSetup)
self.thread.newSample.connect(self.plotNewSample)
self.thread.finished.connect(self.Done)
self.stopBtn.clicked.connect(self.thread.terminate)
self.stopBtn.clicked.connect(self.Stop)
self.thread.start()
It's not a problem. The general practice when working with QThread is to connect its finished() signal to the deleteLater() slot of the objects that have been moved to the separate thread via moveToThread(). It's done in order to properly manage the memory when you then destroy your thread because it's assumed that you will first quit the thread and then destroy its instance. ;) This should tell you that stopping a thread has nothing to do with the destruction of those objects UNLESS you have established the connection I've described above.
It is perfectly fine to restart a thread IF you have stopped it properly using quit() and wait() to actually wait untill the stopping is completed.
However my advice is to not do that unless that extra thread has a huge impact on your application for some reason (highly unlikely with modern machines).
Instead of restarting the thread consider the following options:
implement a pause flag that just makes the thread run without doing anything if it's set to true (I've used this example of mine many times to demonstrate such behaviour (check the worker.cpp and the doWork() function in particular) - it's in C++ but it can be ported to PyQt in no time)
use QRunnable - its designed to run something and then (unless autoDelete is set to true) return to the thread pool. It's really nice if you have tasks that occur every once in a while and you don't need a constatly running separate thread. If you want to use signals and slots (to get the result of the calculation done inside the QRunnable::run() you will have to first inherit from QObject and then from QRunnable
Use futures (check the Qt Concurrent module)
I suggest that you first read the Example use cases for the various threading technologies Qt provides.
I am creating a program in Python that listens to varios user interactions and logs them. I have these requirements/restrictions:
I need a separate process that sends those logs to a remote database every hour
I can't do it in the current process because it blocks the UI.
If the main process stops, the background process should also stop.
I've been reading about subprocess but I can't seem to find anything on how to stop both simultaneously. I need the equivalent of spawn_link if anybody know some Erlang/Elixir.
Thanks!
To answer the question in the title (for visitors from google): there are robust solutions on Linux, Windows using OS-specific APIs and less robust but more portable psutil-based solutions.
To fix your specific problem (it is XY problem): use a daemon thread instead of a process.
A thread would allow to perform I/O without blocking GUI, code example (even if GUI you've chosen doesn't provide async. I/O API such as tkinter's createfilehandler() or gtk's io_add_watch()).
I'm running Django, and I'm creating threads that run in parallel while Django runs. Those threads sometimes run external processes that block while waiting for external input.
When I restart Django, those threads that are blocking while awaiting external input sometimes persist through the restart, and further they have and keep open Port 8080 so Django can't restart.
If I knew when Django was restarting, I could kill those threads. How can I tell when Django is restarting so that I can kill those threads (and their spawn).
It wasn't obvious from django.utils.autoreload where any hooks may be to tell when a restart is occurring.
Is there an alternative way to kill these threads when Django starts up?
Thanks for reading.
Brian
It's not easy for a Python process to kill its own threads -- even harder (nearly impossible) to kill the threads of another process, and I suspect the latter is the case you have... the "restart" is presumably happening on a different process, so those threads are more or less out of bounds for you!
What I suggest instead is "a stitch in time saves nine": when you create those threads, make sure you set their daemon property to True (see the docs -- it's the setDaemon method in Python <= 2.5). This way, when the main thread finishes, e.g. to restart in another process, so will the entire process (which should take all the daemon threads down, too, automatically!-)
What are you using to restart django? I'd put something in that script to look for process id's in the socket file(s) and kill those before starting django.
Alternatively, you could be very heavy handed and just run something like 'pkill -9 *django*' before your django startup sequence.