On 19 June 2018 at 13:02, Nick Coghlan <ncogh...@gmail.com> wrote: > On 19 June 2018 at 16:12, INADA Naoki <songofaca...@gmail.com> wrote: > > > > On Tue, Jun 19, 2018 at 2:56 PM Jeroen Demeyer <j.deme...@ugent.be> > wrote: > >> > >> On 2018-06-18 16:55, INADA Naoki wrote: > >> > Speeding up most python function and some bultin functions was very > >> > significant. > >> > But I doubt making some 3rd party call 20% faster can make real > >> > applications significant faster. > >> > >> These two sentences are almost contradictory. I find it strange to claim > >> that a given optimization was "very significant" in specific cases while > >> saying that the same optimization won't matter in other cases. > > > > > > It's not contradictory because there is basis: > > > > In most real world Python application, number of calling Python > methods or > > bulitin functions are much more than other calls. > > > > For example, optimization for bulitin `tp_init` or `tp_new` by FASTCALL > was > > rejected because it's implementation is complex and it's performance > gain is > > not significant enough on macro benchmarks. > > > > And I doubt number of 3rd party calls are much more than calling builtin > > tp_init or tp_new. > > I don't think this assumption is correct, as scientific Python > software spends a lot of time calling other components in the > scientific Python stack, and bypassing the core language runtime > entirely. > > A recent Python survey by PSF/JetBrains shows that almost half of current Python users are using it for data science/ML/etc. For all these people most of the time is spent on calling C functions in extensions.
-- Ivan
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