potiuk commented on issue #18316:
URL: https://github.com/apache/airflow/issues/18316#issuecomment-922248914


   My point is not that "it's not possible" or that it's not "useful" or not 
that it's not "used elsewhere". I simply think comparing it with Windows or 
MacOS "Explorer/Finder" which is targeted for different users and use case is 
not very good comparison. The fact that you CAN do something does not mean that 
you SHOULD.
   
   My point is that we are really not in general "filesystem" users camp where 
you have non-professional users who do not understand what leading zeros are 
and how they impact sorting.
   
   The Dag ids we have are generated programmatically and company using them 
builds their own dags can use and enforce their own conventions for naming 
them. Rather than accepting and supporting (rather poor in terms of consistency 
and organisation) naming convention where you have natural numbering I think we 
should promote better organised ones,
   
   Most of the users who create DAGs are data scientists/engineers who 
understand numbers, sorting, leading 0s etc. And most of all naming your dags 
with consecutive numbers: 0/1/2 etc. is actually a bad idea on it's own because 
it tells exactly nothing other than this is the "next" version of the same DAG 
(without giving any hint of the reasoning behind it). Having multiple versions 
of the same dag with only consecutive number difference is a terrible 
anti-pattern IMHO.
   
   I believe it's good choice for Airflow to stick with lexicographic sorting 
and not to promote some "bad" conventions - and since it is rather easy to make 
your dags define and follow "good" conventions I see "natural sorting" as 
simply bad choice for Airflow that would promote bad naming conventions.
   
   So to explain why I marked it as "won't fix":  not because I thought it as 
("not new") idea. The idea is well known, but I think applying it Airflow DAG 
ids is a bad idea.
   
   But if you have arguments why natural sorting might be useful for  
production, setup where data engineers have to manage multiple DAGs, I am happy 
to hear the arguments.


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