On Tuesday, 31 March 2015 at 11:04:50 UTC, Laeeth Isharc wrote:
As Andrew Brown pointed out, visualization is not behind
Pythons success. Its success lies in the fact that it's a
language you can hack away in easily.
Sounds right. I am not in the camp that says it is a killer
for D. It would just be nice to have both at least a passable
solution for visualization, and some way of making it
interactive. (The REPL might be one route). The problem with
separating the processes completely and just piping the output
from D code that does the heavy lifting to a python or julia
front end is it may make it more painful to play with and
explore the data. My interests are finance more than science,
so that may lead to a different set of needs. Finishing mathgl
and writing D bindings for bokeh (take a look - it is pretty
cool, particularly to be able to use the browser as client,
acknowledging that it is a tradeoff) is not so much work. But
some help on bokeh particularly would be nice, as I fear
picking one way of implementing the object structure and later
finding it is a mistake.
the initial euphoria of being able to automatically rename
files and extract value X from file Y soon gives way to
frustration when it comes to performance.
Yep.
The paper shows well that in a world where data processing is
of utmost importance, and we're talking about huge sets of
data, languages like Python don't cut it anymore.
I could not agree more, and I do think the intersection of two
trends creates tremendous opportunity for D. It's also
commonsensical to look at notable successes - and I hope it is
not just my biases that lead me to think many of these are in
just this kind of application. Data sets keep getting larger
(but not necessarily more information rich in dollar terms),
and Moore's Law/memory speed+latency is not keeping pace. This
is exactly the kind of change that creeps up on you because not
much changes in a few months (which is the kind of horizon many
of us tend to think in).
People say "what is D's edge", but my personal perception is
"where is the competition for D" in this area. It has to be
native code/JIT, and I refuse to learn Java; it also should be
plastic and lend itself to rapid iteration.
It is in the JVM and .NET eco-systems. Both have AOT compilers
available, are able to chew data on GPGPUs and offer SIMD
libraries.
This is why there is such a strong focus with value types and
better C interop planned for Java 10, has its use for data
analysis has been growing.
In HPF, companies prefer to live with JVM workarounds for the
current limitations than go out and hire a few C++ developers,
given the amount of money saved in salaries.
--
Paulo
