On Aug 7, 2:52 pm, M8R-n7v...@mailinator.com wrote:
> On Aug 7, 6:38 am, bearophileH...@lycos.com wrote:
>>
>> Yes, this was pointed out in the comments. I had updated the code to
> use
> xrange and is and is not instead of range, == and !=, which is how
> the
> benchmark got updated to 192 microseconds. Moving the main loop into
> a main function resulted in no discernible difference.
>
> Testing with psyco resulted in a time of 33 microseconds per
> iteration.
>

I have since updated the post to reflect the python with psyco timings
as well.

On Aug 7, 8:08 pm, M8R-n7v...@mailinator.com wrote:
> Really how silly can it be when you suggest someone is taking a
> position and tweaking the benchmarks to prove a point [...]

I certainly didn't intend to suggest that you had tweaked -anything-
to prove your point.

I do, however, think there is little value in slavishly implementing
the same algorithm in different languages. To constrain a dynamic
language by what can be achieved in a static language seemed like such
an -amazingly- artificial constraint to me. That you're a fan of
Python makes such a decision even more confusing.

It's great that you saw value in Python enough to choose it for actual
project work. It's a shame you didn't endeavour to understand it well
enough before including it in your benchmark.

As for it being "disappointing", the real question is: has it been
disappointing for you in actual real-world code?

Honestly, performance benchmarks seem to be the dick size comparison
of programming languages.

>
> Honestly, performance benchmarks seem to be the dick size comparison
> of programming languages.
>

But in the honour of dick size:

http://shootout.alioth.debian.org/gp...t=all&lang=all
http://shootout.alioth.debian.org/de...t=all&lang=all

On Thu, Aug 7, 2008 at 8:12 AM, alex23 <wuwei23> wrote:
[..]
> It's great that you saw value in Python enough to choose it for actual
> project work. It's a shame you didn't endeavour to understand it well
> enough before including it in your benchmark.
>
> As for it being "disappointing", the real question is: has it been
> disappointing for you in actual real-world code?
>
> Honestly, performance benchmarks seem to be the dick size comparison
> of programming languages.
> -

I actually think that modelling this problem the way he chose to, with
a Person class and by manually popping stuff out of a linked list
instead of more simply representing the alive/dead state of the
soldiers is a poor solution in general. Whenever you talk about
performance, you need to have a context to evaluate it in and you need
an idea of what you're trying to measure and why it's important for
your purposes. A solution which models the soldiers as bits in a
bitfield is going to run much, much, much faster in C/C++/D than the
current OO/linked list one (not to mention in much less space), and
the JIT in Java/C# and probably python with psyco can improve that as
well.

On Thu, 07 Aug 2008 06:12:04 -0700, alex23 wrote:

> On Aug 7, 8:08 pm, M8R-n7v...@mailinator.com wrote:
>> Really how silly can it be when you suggest someone is taking a
>> position and tweaking the benchmarks to prove a point [...]
>
> I certainly didn't intend to suggest that you had tweaked -anything- to
> prove your point.
>
> I do, however, think there is little value in slavishly implementing the
> same algorithm in different languages. To constrain a dynamic language
> by what can be achieved in a static language seemed like such an
> -amazingly- artificial constraint to me.

I don't know about that... it can be very useful to (say) demonstrate
that Lisp-style lists are fast in Lisp, and slow in Python. Or that
try...except is fast in Python, and slow in Java.

And if your aim is to compare languages, then it's only fair to keep the
algorithm constant. Imagine how we would holler and shout if the
benchmark compared Ruby using Quicksort and Python using Bubblesort.

I guess what some of us are complaining about is that the algorithm
chosen doesn't suit Python's execution model very well, and hence Python
is slow. If the algorithm chosen had suited Python, and hence Python came
up looking really fast, we'd be ecstatic. How about that, hey? *wink*

....
> Honestly, performance benchmarks seem to be the dick size comparison of
> programming languages.

I can't disagree with that one bit.

On Thu, Aug 7, 2008 at 9:09 AM, Steven D'Aprano
<steve> wrote:
> On Thu, 07 Aug 2008 06:12:04 -0700, alex23 wrote:
>> I don't know about that... it can be very useful to (say) demonstrate
> that Lisp-style lists are fast in Lisp, and slow in Python. Or that
> try...except is fast in Python, and slow in Java.
>

That's true, but note that the original post doesn't attempt to draw
any conclusions about what's fast or slow from the benchmark, which is
one reason why it's a poor example of benchmarking.

> And if your aim is to compare languages, then it's only fair to keep the
> algorithm constant. Imagine how we would holler and shout if the
> benchmark compared Ruby using Quicksort and Python using Bubblesort.
>

That's definitely true, and (for example) the Alioth benchmarks are
intended to benchmark specific algorithms for comparisons sake.

> I guess what some of us are complaining about is that the algorithm
> chosen doesn't suit Python's execution model very well, and hence Python
> is slow. If the algorithm chosen had suited Python, and hence Python came
> up looking really fast, we'd be ecstatic. How about that, hey? *wink*
>

The "best" way to implement this problem, as bitfield manipulation,
would actually show python in even worse light. I suspect the main
thing that this benchmark is actually testing is loop overhead, and
secondarily object allocation speed. Python is pretty slow in the
former and reasonable in the latter, so I don't find the results very
surprising at all.

> ...
>> Honestly, performance benchmarks seem to be the dick size comparison of
>> programming languages.
>
> I can't disagree with that one bit.
>

As with genitals, the important thing about benchmark comparison is
what you're going to do with the results.
[..]

On Aug 7, 6:12 pm, alex23 <wuwe> wrote:
> On Aug 7, 8:08 pm, M8R-n7v...@mailinator.com wrote:
>
> > Really how silly can it be when you suggest someone is taking a
> > position and tweaking the benchmarks to prove a point [...]
>
> I certainly didn't intend to suggest that you had tweaked -anything-
> to prove your point.

While that was not how I read it first, I assume that was a misjudged
reading.

> I do, however, think there is little value in slavishly implementing
> the same algorithm in different languages. To constrain a dynamic
> language by what can be achieved in a static language seemed like such
> an -amazingly- artificial constraint to me. That you're a fan of
> Python makes such a decision even more confusing.

It is a sufficiently well understood maxim, that any comparison
between two factors should attempt to keep other factors as equal as
possible (Ceteris Paribus - Everything else being equal), slavishly if
you will. It is my perception that had I changed the algorithms, I
would've been a much higher level of criticism a lot more for
comparing apples and oranges.

I simply could not understand your point with regards to dynamic vs.
static languages. If you are by any chance referring to make the code
a little less OO, I believe the entire exercise could be redone using
a procedural algorithm, and all the languages will run much much
faster than they currently do. But that would be essentially moving
from an OO based design to a procedural design. Is that what you are
referring to (I suspect not .. I suspect it is something else) ? If
not, would certainly appreciate you spending 5 mins describing that.

I am a fan of Python on its own merits. There is little relationship
between that and this exercise.


> It's great that you saw value in Python enough to choose it for actual
> project work. It's a shame you didn't endeavour to understand it well
> enough before including it in your benchmark.

I have endeavoured hard, and maybe there's a shortcoming in the
results of that endeavour. But I haven't quite understood what it is I
haven't understood (hope that makes sense :) )

> As for it being "disappointing", the real question is: has it been
> disappointing for you in actual real-world code?

I am extremely happy with it. But there definitely are some projects I
worked on earlier I would simply not choose any dynamic language for
(not ruby / not python / not ruby / not groovy). These languages
simply cannot be upto the performance demands required of some
projects.

> Honestly, performance benchmarks seem to be the dick size comparison
> of programming languages.

Not sure if there is a real life equivalent use case if I was to use
this analogy further. But there are some days (mind you not most days)
one needs a really big dick. Always helpful to know the size.

M8R-n7vorv wrote:

> Is there any reason why the psyco is not a part of the core python
> feature set ?

Psyco was a PhD project. I do not believe the author ever offered it.
Last I knew, it was almost but not completely compatible.

> Is there a particular reason it is better to be kept as
> a separate extension ?

If he did, he would have to commit to updating it to work with new
version of Python (2.6/3.0) which I don't believe he wants to do. Last
I know, he was working with the PyPy project instead and its JIT
technology. On the otherhand, extensions are also restricted by
Python's release schedule, including no new features in bug-fix
(dot-dot) releases. So library extensions need to be rather stable but
maintained.

> Are there any implications of using psyco ?

It compiles statements to machine code for each set of types used in the
statement or code block over the history of the run. So code used
polymorphically with several combinations of types can end up with
several compiled versions (same as with C++ templates). (But a few
extra megabytes in the running image is less of an issue than it was
even 5 or so years ago.) And time spent compiling for a combination
used just once gains little. So it works best with numeric code used
just for ints or floats.

Terry J. Reedy

alex23:
> Honestly, performance benchmarks seem to be the dick size comparison
> of programming languages.

I don't agree:
- benchmarks can show you what language use for your purpose (because
there are many languages, and a scientist has to choose the right tool
for the job);
- it can show where a language implementation needs improvements (for
example the Haskell community has improved one of their compilers
several times thank to the Shootout, the D community has not yet done
the same because the language is in a too much fast evolving phase
still, so performance tunings is premature still);
- making some code faster for a benchmark can teach you how to make
the code faster in general, how CPUs work, or even a some bits of
computer science;
- if the benchmarks are well chosen and well used, they can show you
what are the faster languages (you may say 'the faster
implementations', and that's partially true, but some languages have a
semantic that allows better or much better optimizations). A computer
is a machine useful for many purposes, programming languages allow
some users to make the machine act as they want. So computers and
languages give some power, they allow you to do something that you
can't do without a computer. A language can give you power because it
gives you the ability to write less bug-prone code, or it can give you
more pre-built modules that allow you to do more things in less time,
or it can give you the power to perform computations in less time, to
find a specific solution faster. So Python and C give you different
kinds of power, and they are both useful. Other languages like D/Java
try to become a compromise, they try to give you as much as possible
of both "powers" (and they sometimes succeed, a D/Ocaml program may be
almost as fast as C, while being on the whole much simpler/safer to
write than C code).

Bye,
bearophile

On Aug 7, 11:58 pm, Terry Reedy <tjre> wrote:
> M8R-n7v...@mailinator.com wrote:
>  > Are there any implications of using psyco ?
>
> It compiles statements to machine code for each set of types used in the
> statement or code block over the history of the run.  So code used
> polymorphically with several combinations of types can end up with
> several compiled versions (same as with C++ templates).  (But a few
> extra megabytes in the running image is less of an issue than it was
> even 5 or so years ago.)  And time spent compiling for a combination
> used just once gains little.  So it works best with numeric code used
> just for ints or floats.
>
> Terry J. Reedy

Sounds to me very much like polymorphic inline caching / site caching,
which
is something I have seen been worked upon and getting introduced in
recent
versions of groovy / jruby and ruby 1.9 (and I read its being looked
at in
Microsoft CLR as well .. but I could be wrong there). I am no expert
in this
so please correct me if I deserve to be.

But if site caching is indeed being adopted by so many dynamic
language
runtime environments, I kind of wonder what makes python hold back
from
bringing it in to its core. Is it that a question of time and effort,
or
is there something that doesn't make it appropriate to python ?

Cheers,
Dhananjay

On Aug 7, 2:05 am, "Jack" <nos> wrote:
> I know one benchmark doesn't mean much but it's still disappointing to see
> Python as one of the slowest languages in the test:
>
> [..]...


And how does this reflect the performance of real world Python
programs?

Google uses Python to run the YouTube web site. NASA uses Python to
process image data from the Hubble space telescope. Would they do that
if Python was unbearably sluggish? Do you get faster downloads from a
bittorrent client written in Java (e.g. Azureus) than the original
BitTorrent client (a Python program)?

Using a high level language efficiently is an art. The key is using
Python's built-in data types and extension libraries (e.g. PIL and
NumPy). That is the opposite of what authors of these 'benchmarks'
tend to do.




It seems the majority of these 'benchmarks' are written by people who
think like C++ programmers.

On Aug 8, 2:49 pm, Dhananjay <dhananjayn> wrote:
> Is it that a question of time and effort,
> or is there something that doesn't make it appropriate to python ?

I don't think I've ever seen anyone who has raised concerns about the
speed of python actually offer to contribute to resolving it, so I'm
guessing it's the former.

On Aug 8, 9:08 am, alex23 <wuwe> wrote:
> On Aug 8, 2:49 pm, Dhananjay <dhananjayn> wrote:
>
> > Is it that a question of time and effort,
> > or is there something that doesn't make it appropriate to python ?
>
> I don't think I've ever seen anyone who has raised concerns about the
> speed of python actually offer to contribute to resolving it, so I'm
> guessing it's the former.

Contribute to resolve it? Part of me just wants to say that to "speed"
up python would be such a huge undertaking, the outcome would alter
the language beyond what people liked. Another part thinks, why speed
it up, it is pretty fast presently, and I've rarely seen real-world
applications that need that 80/20 rule applied heavily.

Benchmarks for showing what languages are good at is fine, but in
general most conform to a standard range of speed. I cannot find the
article but there was a good piece about how it takes most programmers
the same time to program in any language. Reading through the code is
another matter, I think Python is faster than most in that respect.

I'd look to increase the worst-case scenario's of Python before trying
to speed up everything. Hell the tim_sort is pretty damn fast.

Angel Gutierrez wrote:
> Steven D'Aprano wrote:
>
> Well.. there must be somthing because this is what I got in a normal script
> execution:
>
> [angel@jaulat test]$ python iter.py
> Time per iteration = 357.467989922 microseconds
> [angel@jaulat test]$ vim iter.py
> [angel@jaulat test]$ python iter2.py
> Time per iteration = 320.306909084 microseconds
> [angel@jaulat test]$ vim iter2.py
> [angel@jaulat test]$ python iter2.py
> Time per iteration = 312.917997837 microseconds

What is the standard deviation on those numbers? What is the confidence
level that they are distinct? In a thread complaining about poor
benchmarking it's disappointing to see crappy test methodology being
used to try and demonstrate flaws in the test.

Kris

jlist wrote:
> I think what makes more sense is to compare the code one most
> typically writes. In my case, I always use range() and never use psyco.
> But I guess for most of my work with Python performance hasn't been
> a issue. I haven't got to write any large systems with Python yet, where
> performance starts to matter.

Hopefully when you do you will improve your programming practices to not
make poor choices - there are few excuses for not using xrange ;)

Kris