On 31 October 2011 18:36, Ned Deily <n...@acm.org> wrote: > In article > <CACac1F_V6_6+uG9qfqBJtuokz0HXO53hsXX3Ptap=o8+pxt...@mail.gmail.com>, > Paul Moore <p.f.mo...@gmail.com> wrote: >> On 30 October 2011 18:04, Ned Deily <n...@acm.org> wrote: >> > Has anyone analyzed the current packages on PyPI to see how many provide >> > binary distributions and in what format? >> >> A very quick and dirty check: >> >> dmg: 5 >> rpm: 12 >> msi: 23 >> dumb: 132 >> wininst: 364 >> egg: 2570 >> >> That's number of packages with binary distributions in that format. >> It's hard to be sure about egg distributions, as many of these could >> be pure-python (there's no way I know, from the PyPI metadata, to >> check this). > > Thanks. If you have access to the egg file name, you should be able to > tell. AFAIK, eggs with extension modules include the Distutils platform > name in the file name preceded by a '-', so '-linux', '-win32', > '-macosx' for the main ones. Pure python eggs do not contain a platform > name. http://pypi.python.org/pypi/pyinterval/ is a random example of > the former.
136 architecture-specific 2502 architecture independent About 5%. The numbers don't quite add up, so there's some funnies in there (possibly bad data that I'm not handling well) but it gives an idea. Counts by architecture: win32 70 linux-i686 43 win-amd64 33 linux-x86_64 26 macosx-10.3-fat 12 macosx-10.5-i386 11 macosx-10.6-universal 9 macosx-10.6-fat 8 macosx-10.3-i386 7 macosx-10.6-i386 6 macosx-10.7-intel 4 macosx-10.6-intel 3 macosx-10.6-x86_64 2 macosx-10.3-ppc 2 macosx-10.4-i386 2 macosx-10.4-ppc 2 py2.3-linux-i686 1 py2.4-linux-i686 1 gnu-0.3-i686-AT386 1 linux-ppc 1 cygwin-1.5.25-i686 1 py2.3 1 py2.4 1 py2.5 1 macosx-10.7-x86_64 1 macosx-10.4-universal 1 py2.5-linux-i686 1 Most of the 1-counts are bad data in some form. I'm not sure what this proves, to be honest, but what I take from it is: - Nearly all binary distributions are for Windows - Architecture-neutral eggs are common (but not relevant here as packaging can install from source with these) - Ignoring architecture-neutral eggs, most popular formats are wininst, egg, dumb(!!!) and msi - Even the most popular binary format (wininst) only accounts for 2% of all packages. Having said all of this, there are two major caveats I'd include: - Not everything is on PyPI. - This analysis ignores relative importance. It's hard to claim that numpy is no more significant than, say, "Products.CMFDynamicViewFTI" (whatever that might be - I picked it at random, so apologies to the author :-)) Paul. _______________________________________________ Python-Dev mailing list Python-Dev@python.org http://mail.python.org/mailman/listinfo/python-dev Unsubscribe: http://mail.python.org/mailman/options/python-dev/archive%40mail-archive.com
