What are you planning for 2016?
Daren Scot Wilson via Digitalmars-d
digitalmars-d at puremagic.com
Fri Jan 8 02:32:04 PST 2016
On Tuesday, 5 January 2016 at 12:27:12 UTC, Ola Fosheim Grøstad
wrote:
> I wonder what kind of programming people plan or _hope_ to use
> D for in 2016?
>
We're doing Computer Vision stuff where I work. No chance of
smuggling D in, but there are more and more open source libraries
for CV, that I'd like to interface to, or as an exercise in
learning D, try to rewrite simple versions of in D.
Audio signal processing, machine learning, image processing,
generating procedural texture images for use in 3D graphics.
Much of this, when at home instead of at work, is to create demos
of math and physics principles, to go with writings and to show
off.
> What other languages do you think you will use or toy with in
> 2016 and for what purpose?
Python, for quick data exploration, initial algorithm
development, scripts to manage files and data at work. Kaggle
competitions.
Julia in place of Python when I can get away with it, especially
personal projects, and Kaggle. For Kaggle, I start in Python or
Julia to figure out how to solve the problem, get a feel for the
data and solutions, then make a fast number-cruncher in D to deal
with full-size data and hammer away on those O(N!) problems.
Javascript for interactive web doodads, data visualization,
science/engineering educational toys as web apps.
C++ 'cause companies that pay enough to cover my rent still use
C++ (if not Java (ick) or C# (eh, i kinda like it actually)).
Ugh! Someone has to convince executives, software project
managers, team leads and everyone else involved that C++ sux and
D r00lz.
C-like shader languages, for vertex and fragment shaders, for
custom 3D data viz at work, and Blender art projects at home.
> What would it take for you to use D instead, or what changes
> would be needed for you to move from language X to D?
Way less than it would take me to use something else instead of D!
The only reason I use Python or Julia instead of D is the quick,
informal, experimental way of exploring data they allow. The
main reason I favor Julia over Python is I hate having to put
"np." in front of many of the mathy things, and "self." when
inside an object to refer to its own parts.
In an ideal world, it'd be only Julia and D for 97% of the stuff
I do.
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