Pablo Galindo Salgado <pablog...@gmail.com> added the comment:

> One potential reason would be that the consequences of bad resource 
> management in this case are different than in the open() case, i.e., here the 
> interpreter hangs -- or Travis runs for your repo (SciPy) get stuck with 
> over-50-minute errors, which is how we started looking for how to track it 
> down.

Agreed, but is the same problem: resources need to be managed. I am although ok 
if you want to add some targeted warning to the multiprocessing pool docs 
indicating what can happen if the resource is not properly managed.

> Indeed, my point is more about potential prevalence: this (now incorrect) 
> problematic usage pattern was the first example in the docs for 
> multiprocessing for a long time, indicating that there might be a lot of code 
> in the wild that might (still) make use of it.

Right, we put great efforts to make the code such that even incorrect usages do 
not hang (and believe me, is *very* challenging) but we cannot sacrifice 
correct usage fixes or big improvements so incorrect usages keep working even 
if they are leaking resources. Hopefully, more and more people start using the 
context manager or are aware that are doing something wrong leaking the pool.

----

In conclusion, I agree that maybe adding some targetted warning to the pool 
docs about this is in place. When I prepare the PR, would you like to review 
the message to confirm that is clear enough and that makes sense?

----------

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Python tracker <rep...@bugs.python.org>
<https://bugs.python.org/issue38501>
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