Hi, all.
I implemented my new idea. (still wip)
https://github.com/methane/cpython/pull/3/files
Memory usage when building Python doc with sphinx are:
1) master (shared key)
176MB
2) compact (w/ shared key)
158MB
3) compact (w/o shared key)
166MB
4) compact & interned (new)
160MB
Memory usag
I've checked time and maxrss of sphinx-build.
In case of sphinx,
## master
$ rm -rf build/
$ /usr/bin/time ~/local/python-master/bin/sphinx-build -b html -d
build/doctrees -D latex_paper_size= . build/html -QN
71.76user 0.27system 1:12.06elapsed 99%CPU (0avgtext+0avgdata
176248maxresident)k
8
Hi, Mark. Thank you for reply.
On Thu, Jun 23, 2016 at 10:30 AM, Mark Shannon wrote:
> Hi all,
>
> I think we need some more data before going any further reimplementing
> dicts.
>
> What I would like to know is, across a set of Python programs (ideally a
> representative set), what the proporti
> Memory usage
>
>
> on amd64 arch.
>
> key-sharing dict:
>
> * 96 bytes for ~3 items
> * 128 bytes for 4~5 items.
Note: There are another shared key.
* 128 bytes for ~3 items
* 224 bytes for 4~5 items
So, let S = how many instances shares the key,
* 90 + (96 / S) bytes for
Hi all,
I think we need some more data before going any further reimplementing
dicts.
What I would like to know is, across a set of Python programs (ideally a
representative set), what the proportion of dicts in memory at any one
time are:
a) instance dicts
b) other namespace dicts (classe
As my last email, compact ordered dict can't preserve
insertion order of key sharing dict (PEP 412).
I'm thinking about deprecating key shared dict for now.
Instead, my new idea is introducing more compact dict
specialized for namespace.
If BDFL (or BDFL delegate) likes this idea, I'll take anot
