On Wednesday, 14 October 2015 at 15:31:49 UTC, John Colvin wrote:
On Wednesday, 14 October 2015 at 15:25:22 UTC, David DeWitt
wrote:
On Wednesday, 14 October 2015 at 14:48:22 UTC, John Colvin
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-slow
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.
That's true until you need to connect to other systems. There
are countless clients built for other systems thats are used
in real world applications. With web development the Python
code really just becomes glue nowadays and api's. I
understand D is faster until you have to build the clients for
systems to connect. We have an application that uses
Postgres, ElasticSearch, Kafka, Redis, etc. This is plenty
fast and the productivity of Python is more than D as the
clients for Elasticsearch, Postgres and various other systems
are unavailable or incomplete. Sure D is faster but when you
have other real world systems to connect to and time
constraints on projects how can D be more productive or
faster? Our python code essentially becomes the API and usage
of clients to other systems which handle a majority of the
hardcore processing. Once D gets established with those
clients and they are battle tested then I will agree. To me
productivity is more than the language itself but also
building real world applications in a reasonable time-frame.
D will get there but is nowhere near where Python is.
Python is inherently quite good for glue and has great library
support, so if that's the majority of your work then Python is
a good choice. On the other hand, there's plenty of programming
out there that isn't like that.
I agree but the quora question ask why it is popular despite
being slow and this is the reason. If you are doing tasks that
are computationally expensive in Python then yes it will be slow
but Python is popular largely because of their web frameworks and
support. Even something like Pandas is good enough for most
peoples data sets. But still I think most people use it as glue
and if they need something done they can pass it off to something
else to do the "real" work. If this wasn't the case then Python
would not be as popular. You pick the right tool for the right
job maybe D and maybe Python and this doesn't mean your results
will be slow.
