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Comment by kccqzy | Hacker News Reader

Forking and multi threading do not coexist. Even if one of your transitive dependencies decides to launch a thread that’s 99% idle, it becomes unsafe to fork.

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Im curious as to the down votes on this. It's absolutely true, and when I was maintaining a job runner daemon that ran hundreds of thousands of who knows what Python tasks/jobs a day on some shared infra with arbitrary code for a certain megacorp from 2016-2020 or so, this was one of insidious and ugly failure modes to go debug and handle. The docs really make it sound like you can mix threading and multiprocessing but you can never really completely ensure that threading and then bare fork will ever be safe, period. It's really irritating that the docs would have you believe that this is OK or safe, but is in keeping with the Python philosophy of trying to hide the edge of the blade you're using until it's too late and you've cut the shit out of yourself.

I'm replying to a person that scales python by running several containers instead of 1 container with several python processes.

Why is it unsafe?

In general only the thread calling fork() gets forked, so unless you call exec() soon after, there are a lot of complications with signals, shared memory.

What are the complications? A single thread with its own process sandbox with everything from the parent is exactly what I'd expect coming from C land. Are the complications you refer to specific to the python VM or more general?

If you have multiple threads, you almost certainly have mutexes. If your fork happens when a non-main thread holds a mutex, your main thread will never again be able to hold that mutex.

An imperfect solution is to require every mutex created to be accompanied by some pthread_atfork, but libraries don’t do that unless forking is specifically requested. In other words, if you don’t control the library you can’t fork.

Even treating the process as read only after forking is potentially fraught. What if a background thread is mutating some data structure? When it forks the data structure might be internally inconsistent because the work to finish the mutation might not be completed. Imagine there are locks held by various threads when it dies, trying to lock those in the child might deadlock or even worse. There's tons of these types of gotchas.

Okay so just all the usual threading gotchas. Nothing specific to Python.

Conceptually fork "just" noncooperatively preempts and kills all other threads. Use accordingly. Yes it's a giant footgun but then so is all low level "unmanaged" concurrency.

Fork-then-thread works, does it not?

But not the reverse, if its a bare fork and not strictly using basically mutex and shared resource free code (which is hard), and there's little or no warning lights to indicate that this is a terrible idea that fails in really unpredictable and hard to debug ways.

If you have enough discipline to make sure you only create threads after all the forking is done, then sure. But having such discipline is harder than just forbidding fork or forbidding threads in your program. It turns a careful analysis of timing and causality into just banning a few functions.

Can't you check what threads are active at the time you fork?

And what do you do with that information? Refuse to fork after you detect more than one thread running? I haven’t seen any code that gracefully handles the unable-to-fork scenario. When people write fork-based code, especially in Python, they always expect forking to succeed.

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