On Thursday, 22 October 2015 at 20:10:36 UTC, rsw0x wrote:
On Thursday, 22 October 2015 at 19:16:00 UTC, Laeeth Isharc
On Thursday, 22 October 2015 at 18:23:08 UTC, Andrei
On 10/22/2015 09:08 AM, Walter Bright wrote:
This has been a homerun. Congratulations for this work and
also for publicizing it! (Consider it might have remained
just one forum discussion read by all of 80 persons...) --
We really do need to stop hiding our light under a bushel.
Thinking in marketing terms doesn't always come easy to
technically minded people, and I understand why, but
ultimately the community benefits a great deal from people
becoming aware of the very real benefits D has to offer (alas
people won't just get it, even if you think they should), and
there are personal career benefits too from helping
communicate how you have applied D to do useful work. It's
hard to find great programmers and showing what you can do
will pay off over time.
D has no well defined area to be used in. Everyone knows D,
when written in a very specific C-mimicking way, is performant.
But nobody is using C# or Scala or Python for performance.
You reply to my post, but I don't entirely see how it relates. D
is very flexible, and that's its virtue. Because splitting a
codebase across multiple languages does have a cost, even if it's
often worth paying the cost in order to use the right till for
the job when those tools are by their nature specialised. I
don't think everyone knows D is performant, and I wouldn't say
fast JSON is written in a C mimicking way, taken as a whole.
Choices are based on making trade-offs, and the relevant data are
not static, but constantly shifting. When an SSD in 2015 that
isn't especially pricey gives 2.1 Gig a sec throughput and one
has many terabytes of text data a month to get through, and
that's today and datasets keep growing and what I write today may
be in use for years then the right decision will be a very
different one to that five years ago. That's not just my
perception, but those in other fields where the problems are
similar - bioinformatics and advertising data being some of the
many others. AdRoll is known for their Python work, but their
data scientists use D.
And my point, which you didn't really reply to, is that as a
community we should do a bit more to share our experiences on how
D can be useful in doing real work. As Walter observes, that's
also something that pays off personally too.