That’s normal for languages like Python. The code that is actually running in 
Python is slow, but library functions are fast, because they are written in C.

Andy

> On Jul 7, 2017, at 4:51 AM, jeff.templon.nik...@gmail.com wrote:
> 
> Hi
> 
> Exploring Go, 1st project is to port over my favourite playground (prime 
> number factorisation) from Python to Go.
> 
> Aside: I was a big Oberon-2 fan back in the day, so I'm pretty excited about 
> Go making possible what never was in Oberon.  
> 
> Back to business: I was disappointed that Go is only a factor of 3 or so 
> faster than Python.  The numbers I'm dealing with are big enough that they 
> don't fit into a uint64 so I'm using math/big ... turns out that about 70% of 
> the runtime is spent in the Mod function of math/big, and mostly this is 
> inside the underlying function divLarge. See profile info below.   
> 
> The naive explanation would be that Mod in Go math/big is about just as fast 
> as the % primitive in python (Python has big integers automatically where 
> needed) but the rest of the program is a factor of 10 or so faster in Go than 
> Python.  I wonder though, especially if there is a better way to take a Mod.  
> The numbers are not THAT large (less than 100 decimal digits in most cases) 
> ...
> 
> (pprof) top10 -cum
> 13.01s of 41.11s total (31.65%)
> Dropped 86 nodes (cum <= 0.21s)
> Showing top 10 nodes out of 74 (cum >= 6.66s)
>       flat  flat%   sum%        cum   cum%
>          0     0%     0%     40.45s 98.39%  runtime.goexit
>          0     0%     0%     40.20s 97.79%  main.main
>          0     0%     0%     40.20s 97.79%  runtime.main
>      0.28s  0.68%  0.68%     40.19s 97.76%  
> _/Users/templon/gofact/factoring.Mybrent
>          0     0%  0.68%     40.19s 97.76%  
> _/Users/templon/gofact/factoring.Trial_n_X
>      0.44s  1.07%  1.75%     29.42s 71.56%  math/big.(*Int).Mod
>      0.77s  1.87%  3.62%     28.98s 70.49%  math/big.(*Int).QuoRem
>      0.51s  1.24%  4.86%     28.18s 68.55%  math/big.nat.div
>     10.39s 25.27% 30.14%     27.47s 66.82%  math/big.nat.divLarge
>      0.62s  1.51% 31.65%      6.66s 16.20%  runtime.makeslice
> 
> 
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