Interrupting the workers in Jupyter notebook

[wjaskowski]

If I run something like that

def f(x):
    r = 0
    for i in range(100000000000):
        r += i
    return r
parmap.map(f, range(100))

in Jupyter notebook, and press "Interrupt the kernel" for the first time, I get some output but the workers are still working. After hitting "Interrupt the kernel" for the second time, most workers are killed (44 on my machine), but (always) 4 are still working 100% CPU. Only hitting "Interrupt" for the third time, clears everything.

Here is my workaround with which "Interrput" works with the first hit

def pmap(function, iterable, *args, **kwargs):
    try:
        pool = Pool(processes=psutil.cpu_count()//2)
        return parmap.map(function, iterable, *args, **kwargs, pm_pool=pool)
    finally:
        pool.terminate()

[zeehio]

Thanks for the bug report. I am using pool.join() instead of terminate, I don't know why that makes the difference, but it makes sense that terminate does not wait for anything to finish.

I will try to find time to fix this. I would like to use pool.join unless there is an error or an interruption.

Thanks again!

[zeehio]

I guess it should work now. A bit late though... sorry!