Why is this loop heavy code so slow in Python? Possible Project Euler spoilers

[Alex Martelli]

Re: Why is this loop heavy code so slow in Python? Possible Project Euler spoilers

Mark Dickinson <dickinsm@gmail .comwrote:

On Sep 2, 12:55 pm, al...@mac.com (Alex Martelli) wrote:

Mark Dickinson <dicki...@gmail .comwrote:

Well, for one thing, you're creating half a million xrange objects in
the course of the search. All the C code has
to do is increment a few integers.

I don't think the creation of xrange objects is a meaningful part of
Python's execution time here. Consider:
[...]

>
Agreed---I just came to the same conclusion after doing some tests.
So maybe it's the billion or so integer objects being created that
dominate the running time? (Not sure how many integer objects
actually are created here: doesn't Python cache *some* small
integers?)

Yep, some, say -5 to 100 or thereabouts; it also caches on a free-list
all the "empty" integer-objects it ever has (rather than returning the
memory for the system), so I don't think there's much optimization to be
had on that score either.


Alex

[Wildemar Wildenburger]

Re: Why is this loop heavy code so slow in Python? Possible ProjectEuler spoilers

Martin v. Löwis wrote:

>>(2) it is a interpretation language

>Not quite. It's compiled to byte-code - just like Java (would you call
>Java an 'interpreted language' ?)

>
Python is not implemented like Java. In Java (at least in HotSpot),
the byte code is further compiled to machine code before execution;
in Python, the byte code is interpreted.
>

OK, good. Naive question now comming to mind: Why doesn't Python do the
latter as well?

/W

[Steven D'Aprano]

Re: Why is this loop heavy code so slow in Python? Possible ProjectEuler spoilers

On Sun, 02 Sep 2007 21:00:45 +0200, Wildemar Wildenburger wrote:

Martin v. Löwis wrote:

>>>(2) it is a interpretation language
>>Not quite. It's compiled to byte-code - just like Java (would you call
>>Java an 'interpreted language' ?)

>>
>Python is not implemented like Java. In Java (at least in HotSpot), the
>byte code is further compiled to machine code before execution; in
>Python, the byte code is interpreted.
>>

OK, good. Naive question now comming to mind: Why doesn't Python do the
latter as well?
>
/W

There is no single version of Java, and the reference interpretation runs
on a virtual machine just like Python. Today there are virtual machine
implementations of Java, native compilers, and Just In Time compilers for
Java, including HotSpot mentioned by Martin, but Java the language was
originally defined to run on a VM.

See, for example, here: http://schmidt.devlib.org/java/compilers.html

There are costs to native compilation, the biggest one of course being
the initial investment in time and effort in creating the native
compiler. Sun and other commercial companies have invested a lot of money
in Java, and I don't think the money invested in Python has come even
close. Consequently, any work into JIT compilation for Java has been done
by volunteers.

Nevertheless, we have Psyco, which is a JIT compiler of sorts; work also
continues on PyPy (Python implemented in Python) which, it is hoped, will
lead to faster Python implementations .

Part of the reason that native compilation for Python is hard is that
Python's dynamic object model makes it very difficult to apply the same
sorts of compiler optimizations that C and Java allow. Comparatively
little of the work done by Python can be safely pushed from run time to
compile time, so it is unlikely that the average Python application will
ever run as fast as the equivalent C code -- although that ignores the
question of what "the equivalent C code" could possibly mean. (If the C
code includes all the dynamic high-level features of Python, it too would
surely run as slowly as Python, and if it didn't, it can hardly be said
to be equivalent.) Nevertheless, by using something like Psyco parts of
your Python code can run at virtually the same speed as C.

A big question mark in my mind is Lisp, which according to aficionados is
just as dynamic as Python, but has native compilers that generate code
running as fast as highly optimized C. I'm not qualified to judge whether
the lessons learnt from Lisp can be applied to Python, but in any case
Lisp is an old, old language -- only Fortran is older. The amount of
development effort and money put into Lisp dwarfs that put into Python by
possibly a hundred or more.

So... if you'd like to see Python run as fast as C or Lisp, and you have
a few tens of millions of dollars spare to invest in development, I think
the Python Software Foundation would love to hear from you.



--
Steven.

[Diez B. Roggisch]

Re: Why is this loop heavy code so slow in Python? Possible ProjectEuler spoilers

Wildemar Wildenburger schrieb:

Martin v. Löwis wrote:

>>>(2) it is a interpretation language
>>Not quite. It's compiled to byte-code - just like Java (would you call
>>Java an 'interpreted language' ?)

>>
>Python is not implemented like Java. In Java (at least in HotSpot),
>the byte code is further compiled to machine code before execution;
>in Python, the byte code is interpreted.
>>

OK, good. Naive question now comming to mind: Why doesn't Python do the
latter as well?

because of the dynamic nature of it. Java is statically typed, so the
JIT can heavily optimize.

OTH psyco IS a JIT-compiler to optimize certain calculations which are
mostly of a numerical nature. But this can't be done to the extend it is
possible in java.

Diez

[Chris Mellon]

Re: Why is this loop heavy code so slow in Python? Possible ProjectEuler spoilers

On 9/2/07, Diez B. Roggisch <deets@nospam.w eb.dewrote:

Wildemar Wildenburger schrieb:

Martin v. Löwis wrote:

>>(2) it is a interpretation language
>Not quite. It's compiled to byte-code - just like Java (would you call
>Java an 'interpreted language' ?)
>
Python is not implemented like Java. In Java (at least in HotSpot),
the byte code is further compiled to machine code before execution;
in Python, the byte code is interpreted.
>

OK, good. Naive question now comming to mind: Why doesn't Python do the
latter as well?

>
because of the dynamic nature of it. Java is statically typed, so the
JIT can heavily optimize.
>
OTH psyco IS a JIT-compiler to optimize certain calculations which are
mostly of a numerical nature. But this can't be done to the extend it is
possible in java.
>

Original code: 3 min, 9 seconds
Original code with psyco: 30.28 seconds
Original code, compiled with Pyrex: 1min 39 seconds (moves the for loops into C)
Same, with a,b,c declared with cdef int: 20 seconds (uses c pow()
instead of going through Python).
Same, with the for..xrange loops rewritten to use C integer loops: 13
seconds (saves xrange use, but since the python loop was already gone,
not too much savings).

With a small amount of work, you should be able to implement the C
algorithm in Pyrex (or even just use the C algorithm, in a wrapper
that converts the return value to an int) and get the same speed as
the C version + a constant marshalling factor.

Adding pysco took all of 20 seconds (half that because I needed to
move the module scope code into a function), and re-writing with pyrex
took a minute or two. So, as a demonstration of numeric optmization,
both of them can give you quite good rewards with minimal effort.

[Neil Cerutti]

Re: Why is this loop heavy code so slow in Python? Possible Project Euler spoilers

On 2007-09-02, Martin v. Löwis <martin@v.loewi s.dewrote:

>>(2) it is a interpretation language

>Not quite. It's compiled to byte-code - just like Java (would
>you call Java an 'interpreted language' ?)

>
Python is not implemented like Java. In Java (at least in
HotSpot), the byte code is further compiled to machine code
before execution; in Python, the byte code is interpreted.
>
Whether this makes Python an interpreter or a compiler, I don't
know.

I'd call it an integrated compiler and virtual machine--a classic
combination.

--
Neil Cerutti

[Paul Rubin]

Re: Why is this loop heavy code so slow in Python? Possible Project Euler spoilers

Steven D'Aprano <steve@REMOVE-THIS-cybersource.com .auwrites: A big

question mark in my mind is Lisp, which according to aficionados is
just as dynamic as Python, but has native compilers that generate
code running as fast as highly optimized C. I'm not qualified to
judge whether the lessons learnt from Lisp can be applied to Python,
but in any case Lisp is an old, old language -- only Fortran is
older. The amount of development effort and money put into Lisp
dwarfs that put into Python by possibly a hundred or more.

Writing a simple Lisp compiler is not all that difficult. There's a
chapter in SICP about how to do it, so it's sometimes part of
introductory courses. To get C-like performance you end up having to
rely on user-supplied type declarations and/or type inference, but
even without that you can still do ok. I'd say Lisp is a less dynamic
language than Python. Lisp doesn't have duck typing and doesn't
represent class instance variables as dictionary elements that have to
be looked up at runtime all the time. This maybe even applies to
locals, e.g. in Python if you say

x = 3
print "hello"
y = x + 4

you're possibly not guaranteed that y=7, because you might have bound
sys.stdout to something with a .write method that reaches up the call
stack and messes with the caller's local variables, and if the langref
manual says this is supposed to work, then the compiler has to do it
like CPython. Maybe Python 4.0 will fix some of this stuff.

[jwrweatherley@gmail.com]

Re: Why is this loop heavy code so slow in Python? Possible Project Euler spoilers

Thanks for all the answers to my question. I think what I need to take
away from this is that xrange is an object - I thought it was just
some loop construct, and that maths is slow in python - so avoid
pathological looping.I remember the first time I tried Objective-C on
OS X I used the NSNumber class for arithmetic - the results that time
were pretty awful too!

[Paul Boddie]

Re: Why is this loop heavy code so slow in Python? Possible Project Euler spoilers

On 3 Sep, 15:39, jwrweather...@g mail.com wrote:

Thanks for all the answers to my question. I think what I need to take
away from this is that xrange is an object

Indeed, but using xrange can be faster than converting your "for"
loops to "while" loops plus a counter; I converted your code to use
the latter arrangement and it was noticeably slower. Perhaps the
repeated invocation of each xrange object's next method is less
expensive than repeatedly obtaining new incremented int objects and
testing them against other int objects.

- I thought it was just some loop construct, and that maths is slow in
python - so avoid pathological looping.

You'd be wise to avoid doing unnecessary work deep within nested loops
in any programming language. Sadly, it's not possible for the compiler
to work out that some calculations can be lifted out of the innermost
loops in Python, since the various guarantees that make such
operations possible in other languages are not offered by Python.

I remember the first time I tried Objective-C on OS X I used the
NSNumber class for arithmetic - the results that time were pretty
awful too!

Obviously, it'd be a fairer test if you used comparable numeric types
in both implementations , but a more capable numeric type would be
overkill for the C implementation of this program, and a less capable
numeric type doesn't exist for Python unless you're willing to use a
dialect such as Pyrex (as others have shown).

Paul

[Bruno Desthuilliers]

Re: Why is this loop heavy code so slow in Python? Possible ProjectEuler spoilers

Martin v. Löwis a écrit :

>>(2) it is a interpretation language

>Not quite. It's compiled to byte-code - just like Java (would you call
>Java an 'interpreted language' ?)

>
Python is not implemented like Java. In Java (at least in HotSpot),
the byte code is further compiled to machine code before execution;

This is a VM-specific feature.

in Python, the byte code is interpreted.

Idem.

Whether this makes Python an interpreter or a compiler,
I don't know.

This is an old troll^Mdiscussi on !-)

Now IANAL, but AFAIK, the byte-code compilation stage can make a great
difference performances-wide, and for a same language, a byte-compiled
implementation is likely to be faster than a pure-interpreted one, at
least because of the saving on parsing time (please someone correct me
if I'm wrong) ...

[paulhankin]

Re: Why is this loop heavy code so slow in Python? Possible Project Euler spoilers

On Sep 2, 12:51 pm, jwrweather...@g mail.com wrote:

... right-angled triangle puzzle solver
>
max = 0
maxIndex = 0
index = 0
for solution in solutions:
if solution max:
max = solution
maxIndex = index
index += 1
>
print maxIndex

Not that it solves your slowness problem, or has anything to
do with the question you asked :), but you can replace this
last segment of your code with:

print solutions.index (max(solutions) )

--
Paul Hankin