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Groups > comp.lang.python > #70543

Re: object().__dict__

Date 2014-04-23 14:59 +0100
From Phil Connell <pconnell@gmail.com>
Subject Re: object().__dict__
References <51d9b7f1-3511-4110-adb2-aa2226bd7a3c@lists.xtsubasa.org> <20140423061123.GA47008@cskk.homeip.net> <CAL7_Mo9Hb44ZPEw2UvKcRDiugw-Voh0y=JoMHqGKYHzY8dyKrA@mail.gmail.com>
Newsgroups comp.lang.python
Message-ID <mailman.9466.1398261579.18130.python-list@python.org> (permalink)

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On Wed, Apr 23, 2014 at 03:48:32PM +0200, Amirouche Boubekki wrote:
> 2014-04-23 8:11 GMT+02:00 Cameron Simpson <cs@zip.com.au>:
> > Look up the "__slots__" dunder var in the Python doco index:
> >
> >   https://docs.python.org/3/glossary.html#term-slots
> >
> > You'll see it as a (rarely used, mostly discouraged) way to force a fixed
> > set of attributes onto a class. As with object, this brings a smaller
> > memory footprint and faster attribute access, but the price is flexibility.
> >
> 
> True, still can be the only way to save few MB or... GB without falling
> back to C or PyPy.
> 
> Have a look at PyPy to how to save memory (and speed things up) without
> slots:
> http://morepypy.blogspot.fr/2010/11/efficiently-implementing-python-objects.html

Is there any analysis of how this balances increased memory usage from the JIT
vs the CPython VM (with a reasonable amount of code)?

I'd thought that one of the main disadvantages of PyPy was drastically
increased memory usage for any decent-sized program. Would be interested to
know if this was not the case :)


Cheers,
Phil

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Re: object().__dict__ Phil Connell <pconnell@gmail.com> - 2014-04-23 14:59 +0100

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