Re: [python-uk] Fwd: It Will Never Work in Theory: live!
hi, I receive a lot of email from the python-list, I want to disable it, when I want to read the email, I want to go to he List. Please How to disable it. Regards Le jeu. 3 mars 2022 à 18:05, Steve Holden a écrit : > A communication from my good friend Greg Wilsin (instigator of the > Software Carpentry workshops) which may be of use to some. It certainly > looks like great value for money. > > Kind regards, > Steve > > > -- Forwarded message - > From: Greg Wilson > Date: Tue, Mar 1, 2022 at 5:11 PM > Subject: It Will Never Work in Theory: live! > To: Steve Holden > > > Hi Steve, > > On April 27, It Will Never Work in Theory is running two sets of online > lightning talks from leading software engineering researchers in which > they’ll summarize actionable findings from their work for practitioners. > Tickets are now on sale at https://neverworkintheory.org/, and all money > raised will to go Books for Africa. I hope to see you there, and if you > could help spread the word or help sponsor it by matching money raised > from ticket sales, we'd be very grateful. > > Cheers, > > Greg > > ___ > python-uk mailing list > python...@python.org > https://mail.python.org/mailman/listinfo/python-uk > -- https://mail.python.org/mailman/listinfo/python-list
Re: C is it always faster than nump?
Thanks every body, I want to close the subject, but just a naive question: Does numpy use a* vectorization *for arrays? I mean when I add 2 arrays ( or in sum function) how it is done, in an other word b=np.arange(100); t=np.sum(b) is equivalent or not to s=0 for i in range(100): s +=b[i] thanks a lot Le sam. 26 févr. 2022 à 06:44, Dan Stromberg a écrit : > > On Fri, Feb 25, 2022 at 8:12 AM BELAHCENE Abdelkader < > abdelkader.belahc...@enst.dz> wrote: > >> Hi, >> a lot of people think that C (or C++) is faster than python, yes I agree, >> but I think that's not the case with numpy, I believe numpy is faster than >> C, at least in some cases. >> > > This is all "last time I heard". > > numpy is written, in significant part, in Fortran. > > Fortran, especially for matrix math with variable dimensions, can be > faster than C. > > Fortran, (still last I heard) did not support pointers, which gives > Fortran compilers the chance to exploit a very nice class of optimizations > you can't use nearly as well in languages with pointers. > > I used to code C to be built with the "noalias" optimization, to get much > of the speed of Fortran in C. But it required using an error prone subset > of C without good error detection. > > > -- https://mail.python.org/mailman/listinfo/python-list
C is it always faster than nump?
Hi,
a lot of people think that C (or C++) is faster than python, yes I agree,
but I think that's not the case with numpy, I believe numpy is faster than
C, at least in some cases.
*Is there another explanation ?Or where can find a doc speaking about the
subject?*Thanks a lot
Regards
Numpy implements vectorization for arrays, or I'm wrong. Anyway here is an
example Let's look at the following case:
Here is the result on my laptop i3:
Labs$ *python3 tempsExe.py 5*
sum with Python: 1250025000 and NumPy 1250025000
time used Python Sum: * 37.28 sec *
time used Numpy Sum: *1.85 sec*
Labs$ *./tt5 *
* CPU time :7.521730*
*The value : 1250025000 *
*This is the Python3 program :import timeit as itimport numpy as npimport
systry : n=eval(sys.argv[1])except: print ("needs integer as argument") ;
exit() a=range(1,n+1)b=np.array(a)def func1(): return sum(a)def
func2(): return np.sum(b)print(f"sum with Python: {func1()} and NumPy
{func2()} ")tm1=it.timeit(stmt=func1, number=n)print(f"time used Python
Sum: {round(tm1,2)} sec")tm2=it.timeit(stmt=func2, number=n)print(f"time
used Numpy Sum: {round(tm2,2)} sec")*
*and Here the C program:#include #include #include
long func1(int n){ long r=0;for (int i=1; i<=
n;i++) r+= i; return r;}int main(int argc, char* argv[]){
clock_t c0, c1; long v,count; int n; if ( argc < 2)
{ printf("Please give an argument"); return
-1; }n=atoi(argv[1]); c0 = clock();*
* for (int j=0;j < n;j++) v=func1(n); c1 = clock(); printf
("\tCPU time :%.2f sec", (float)(c1 - c0)/CLOCKS_PER_SEC);
printf("\n\tThe value : %ld\n", v);}*
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