On Wednesday, 14 October 2015 at 18:17:29 UTC, Russel Winder
wrote:
On Wed, 2015-10-14 at 14:48 +0000, John Colvin via
Digitalmars-d-learn wrote:
On Wednesday, 14 October 2015 at 14:32:00 UTC, jmh530 wrote:
> On Tuesday, 13 October 2015 at 23:26:14 UTC, Laeeth Isharc
> wrote:
> > https://www.quora.com/Why-is-Python-so-popular-despite-being-so-s
> > low
> > Andrei suggested posting more widely.
>
> I was just writing some R code yesterday after playing
> around with D for a couple weeks. I accomplished more in an
> afternoon of R coding than I think I had in like a month's
> worth of playing around with D. The same is true for python.
As someone who uses both D and Python every day, I find that -
once you are proficient in both - initial productivity is
higher in Python and then D starts to overtake as a project
gets larger and/or has stricter requirements. I hope never to
have to write anything longer than a thousand lines in Python
ever again.
The thing about Python is NumPy, SciPy, Pandas, Matplotlib,
IPython, Jupyter, GNU Radio. The data science, bioinformatics,
quant, signal provessing, etc. people do not give a sh!t which
language they used, what they want is to get their results as
fast as possible. Most of them do not write programs that are
to last, they are effectively throw away programs. This leads
them to Python (or R) and they are not really interested in
learning anything else.
The fact that NumPy sort of sucks in terms of performance, isn't
noticed by them
as they get their results "fast enough" and a lot faster than
sequential Python. The fact that if they used Chapel or even D
for
their compute intensive code they would rapidly discover that
NumPy
sort of sucks never really occurs to these people as they are
focussed
on the results not the means of achieving them.
Polyglot Python/D or Python/Chapel with Matplotlib is the way
to go. But that really requires a D replacement for Pandas.
Russell, thanks for your thoughts - I appreciate it.
What would a Pandas replacement look like in D?
