Role of D in Python and performance computing [was post on using go 1.5 and GC latency]

[Laeeth Isharc via Digitalmars-d-learn]

On Monday, 24 August 2015 at 21:57:41 UTC, rsw0x wrote:
> On Monday, 24 August 2015 at 21:20:39 UTC, Russel Winder wrote:
>> For Python and native code, D is a great fit, perhaps more so 
>> that Rust, except that Rust is getting more mind share, 
>> probably because it is new.
>
> I'm of the opinion that Rust's popularity will quickly die when 
> people realize it's a pain to use.

Horses for courses ?  Eg for Andy Smith's problem of processing 
trade information of tens of gigs where Python was choking, I 
guess nobody in their right mind would use Rust.  But maybe D 
isn't quite yet what you would choose for a highly complex mass 
consumer product like a browser?

Btw had a nice little test the other day.  I haven't yet done 
much with intraday data - I only just lately took the FX data I 
had sitting around and pulled it into my data server.    Someone 
asked me a question about something in that domain - would have 
taken them a few weeks at least to begin to get an answer.  I 
have never been the fastest programmer, but took a couple hundred 
lines and three hours to write the analysis from scratch, and 
half the time was figuring out how to get it to display nicely in 
Mathgl.  Took less than 10 minutes to run on my home machine 
using debug Dmd and pulling data from my server over the Internet 
with a spinning drive (so probably could get it down to a minute 
or two).  I know it takes a big Wall Street firm an hour to run 
the same task.  That gets in the way of using rapid iteration to 
explore the data.