On 12/10/2015 18:20, Marko Rauhamaa wrote:
Bartc <b...@freeuk.com>:
(Example, calling fib(40) on the example below took 90 seconds on
Python 3.4, 11 seconds with PyPy, but only 1.8 seconds running the
equivalent with FreeBasic:
I don't know what you need fibonacci numbers for,
It's a benchmark that gives you an idea of how efficient an
implementation is at doing function calls.
but speed is not the
essence of most programming tasks.
They've been wasting their time with PyPy then! Everyone likes a bit
more speed. It can mean being able to have a solution all within the
same language.
Rather, the key issue is managing
complexity.
(Yes, I've seen gal kauffman's post in this thread. That will need some
managing for sure!)
As for managing complexity, many people believe static typing is a
crucial tool. I disagree. Static typing adds vast amounts of noise to
the code. A dynamic programming language like Python allows you to
express powerful abstractions concisely, understandably and likely
correctly.
Static typing gives advantages but it's also nice not to have to bother.
That's why type inference can be useful.
--
Bartc
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