How to make Python run as fast (or faster) than Julia
alister
alister.ware at ntlworld.com
Fri Feb 23 04:19:41 EST 2018
On Fri, 23 Feb 2018 03:11:36 -0500, Terry Reedy wrote:
> On 2/22/2018 10:31 PM, Python wrote:
>
>>> Why do you care about the 50 million calls? That's crazy -- the
>>> important thing is *calculating the Fibonacci numbers as efficiently
>>> as possible*.
>
>> If you are writing practical programs, that's true. But the Julia
>> benchmarks are not practical programs; they are designed to compare the
>> performance of various language features across a range of languages.
>
> If that were so, then the comparison should use the fastest *Python*
> implementation. Which is what the article discussed here did. But the
> comparison is a lie when the comparison is compiled machine code versus
> bytecode interpreted by crippled cpython*. And people use this sort of
> benchmark to choose a language for *practical programs*, and don't know
> that they are not seeing *Python* times, but *crippled cpython* times.
Benchmarks are completely pointless anyway.
the question when choosing a language should not be 'How fast it is', it
should always be 'Is it fast enough'.
once you have a choice of languages that are fast enough other criteria
for suitability become important (such as readability & ease of debugging)
--
If you're going to do something tonight that you'll be sorry for tomorrow
morning, sleep late.
-- Henny Youngman
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