Is Python a commercial proposition ?

[Roy Smith]

In article <mailman.2717.1343634778.4697.python-list at python.org>,
 Chris Angelico <rosuav at gmail.com> wrote:

> Python's an excellent glue language, but it's also fine for huge
> applications. Yes, it can't multithread across cores if you use
> CPython and are CPU-bound. That's actually a pretty specific
> limitation, and taking out any component of that eliminates the GIL as
> a serious problem.

These days, I'm working on a fairly large web application (songza.com).  
The business/application logic is written entirely in Python (mostly as 
two django apps).  That's what we spend 80% of our developer time 
writing.

As for scale, we're currently running on 80 cores worth of AWS servers 
for the front end.  Another 50 or so cores for the database and other 
backend functions.  Yesterday (Sunday, so a slow day), we served 27 
million HTTP requests; we're not facebook-sized, but it's not some 
little toy application either.

Every time we look at performance, we can't hardly measure the time it 
takes to run the Python code.  Overall, we spend (way) more time waiting 
on network I/O than anything else.  Other than I/O, our biggest 
performance issue is slow database queries, and making more queries than 
we really need to.

The engineering work to improve performance involves restructuring our 
data representation in the database, caching (at multiple levels), or 
eliminating marginal features which cost more than they're worth.  None 
of this would be any different if we used C++, except that we'd spend so 
much time writing and debugging code that we'd have no time left to 
think about the really important stuff.

As far as the GIL is concerned, it's just not an issue for us.  We run 
lots of server processes.  Perhaps not as elegant as running fewer 
multi-threaded processes, but it works just fine, is easy to implement, 
and we never have to worry about all the horrors of getting memory 
management right in a multi-threaded C++ application.