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4GB is literally nothing. My laptop has 16, most servers I use have 128+. 4GB is netbook territory.


... I think the implication is that more than 4GB would exceed the pre-[PAE][1] memory limit[2]. A form of cross-compilation might work, though PyPy build isn't exactly a simple, 'classical' build process. :P

Edit: also, looking at your comments[3E] it looks like surely you know this (sorry) so I'm now really not sure what you're getting at... :P

[1]: http://en.wikipedia.org/wiki/Physical_Address_Extension

[2]: and even with PAE you still need to split into multiple processes/address spaces to do anything useful

[3E]: https://qht.co/threads?id=sitkack


My point is requiring a lot of ram for a build is not a problem. Yes it would be nice to support low end devices for PyPy compilation, but the set of people on extremely constrained hardware and those people doing development on PyPy that would need to build from source is well, by definition zero.

32 bit is dead except for ARM, and it will be dead on ARM in 4 years.


> 32 bit is dead except for ARM, and it will be dead on ARM in 4 years.

Uh... sure? ... but the parent post was about how building for 32 bit _today_ simply does not work and will not work.

Whilst it's not necessarily best to build for technology almost gone, there definitely will continue to exist 32 bit devices that people would expect to run Python on for quite a number of years yet - today's 32 bit ARM chips aren't going anywhere awhile and not every form factor (say non-desktop) is well suited to a 64+-bit architecture. :/


Remember we are talking about _building_, actually JITing a JIT using a dynamic language _for_ a dynamic language.

I haven't run a 32 bit desktop or server system since 2004. 32 bit is quite dead. In 4 years, only the cheapest ARM SoCs will be 32 bits. In embedded devices, yes 32 bits will be around for a great long while.


4GB is not literally nothing, it's 25% of the memory available on your laptop. That's a significant chunk.


That's not true. $1000 ultrabooks often have 4GB. Hell, the base model rMBP has 4GB (I paid the extra for 8GB).


The people surfing the web and buying some music on iTunes are not building PyPy from source. It makes no sense to put the engineering work into supporting such memory constrained dev environments.




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