Also, 
I've pointed at two of those limits that worry me some - namely 
number of classes and number of co-routines, and had not 
seen so far any feedback even whether they actually make sense.

A simple data analysis tasks that create a co-routine per row, and submit those
for workers with more than 1 million rows is something that  just works today, and is not even
a burden in a desktop machine would hit such limits. 

Is there an easy way to locate the data-structures that would be changed on cpython
that would need to be changed to limit classes and co-routines? I'd like to have at 
least a little more concrete  idea of what could possibly be optimized if they were capped. 


  js
 -><-

On Mon, 9 Dec 2019 at 11:22, Chris Angelico <rosuav@gmail.com> wrote:
On Tue, Dec 10, 2019 at 1:09 AM Mark Shannon <mark@hotpy.org> wrote:
> Bear in mind that the costs of higher limits are paid by everyone, but
> the benefits are gained by few.

Can we get some stats on what the costs of higher limits (or having no
limit at all) is? Or, putting it the other way: Since CPython
currently does not enforce limits, what are the benefits of placing
those limits? Merely having a limit doesn't in itself give a benefit
(and is a (minor) cost); it would help the discussion if we knew
exactly WHAT the costs of the higher limits were.

ChrisA
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