Using Python for programming algorithms

[Vicent Giner]

Hello.

I am new to Python. It seems a very interesting language to me. Its
simplicity is very attractive.

However, it is usually said that Python is not a compiled but
interpreted programming language —I mean, it is not like C, in that
sense.

I am working on my PhD Thesis, which is about Operations Research,
heuristic algorithms, etc., and I am considering the possibility of
programming all my algorithms in Python.

The usual alternative is C, but I like Python more.

The main drawbacks I see to using Python are these:

* As far as I understand, the fact that Python is not a compiled
language makes it slower than C, when performing huge amounts of
computations within an algorithm or program.

* I don't know how likely it is to find libraries in Python related to
my research field.

* I know Python is a "serious" and mature programming language, of
course. But I do not know if it is seen as "just funny" in a research
context. Is Python considered as a good programming language for
implementing Operations Research algorithms, such as heuristics and
other soft-computing algorithms?

Maybe this is not the right forum, but maybe you can give me some
hints or tips...

Thank you in advance.

[Henrique Dante de Almeida]

On May 19, 5:46*pm, "bruno.desthuil [e-mail] "
<bruno.desthuil [e-mail] wrote:

On 19 mai, 17:53, Henrique Dante de Almeida <hda...@gmail.c omwrote:

(snip)

*Yes, I was actually referring to statically typed JIT-compiled
languages. Sorry about that, blame the beers that entered my digestive
system that night. :-P

for beer in beers:
* if beer.entered_he nrique_digestiv e_system_last_n ight:
* * beer.blame()

!-)

???

beers += [Beer.random()]

[Bruno Desthuilliers]

Henrique Dante de Almeida a écrit :

On May 19, 5:35 pm, "bruno.desthuil [e-mail] "
<bruno.desthuil [e-mail] wrote:

>> The situation would be simpler if there were good well-known toolkits
for optimization in python (like numpy for matrix operations), but
that's not the case.

There's at least Psyco (if you're willing and able to restrict
yourself from using some of the most dynamic parts of Python - which
might not be a problem here). One could also mention stuff like Pyrex
and Cython.

I meant toolkits for "optimizati on problems", not "code
optimization".

oops, sorry.

[Ivan Illarionov]

On Mon, 19 May 2008 08:53:11 -0700, Henrique Dante de Almeida wrote:

On May 19, 6:52Â*am, Bruno Desthuilliers <bruno.
42.desthuilli.. .@websiteburo.i nvalidwrote:

>Henrique Dante de Almeida a écrit :

On May 17, 7:32 pm, Vicent Giner <vgi...@gmail.c omwrote:
Hello.

(snip)

>However, it is usually said that Python is not a compiled but
interpreted programming language —I mean, it is not like C, in that
sense.

(snip)

Â*I guess that python is not a good language for that.

(snip)

Â*My opinion: choose compiled or byte compiled languages.

Slightly OT (ie : not talking about computation-heavy alorgithm being
better implemented in C then wrapped in Python - this seems quite
obvious) but just a couple facts:

1/ being interpreted or compiled (for whatever definition of these
terms) is not a property of a language, but a property of an
implementati on of a language.

2/ actually, all known Python implementations compile to byte-code.

Yes, I was actually referring to statically typed JIT-compiled
languages. Sorry about that, blame the beers that entered my digestive
system that night. :-P

[beer.blame() for beer in beers]

if len(beers) 2:
news_reader.sto p_working()

:-)

[Ivan Illarionov]

On Mon, 19 May 2008 11:07:06 -0700, Vicent Giner wrote:
[...]

>
By the way, is it possible (and easy) to call a C function from a Python
program??

Yes.

http://groups.google.com/group/comp....47913a265c348a

-- Ivan

[brad]

Vicent Giner wrote:

The usual answer is that development time is more important than running time.

This depends. Run time is not important until you are asked to scale to
millions or billions of users or computations or large data sets. I've
seen this first hand. Getting results back the same day or sooner may be
important. In cases such as this, I use C or C++... nothing else will
do. Nothing else is as fast. Although I always keep a py version around
for testing and for smaller tasks. Don't get me wrong, I love Python,
but there are times when nothing, but pure, hard speed will do.

[Duncan Booth]

Roel Schroeven <rs************ ****@fastmail.f mwrote:

C OTOH was designed to be compiled to assembly code (or directly to
machine code) and as a result there are no (or virtually) no
implementations that interpret C or compile it to bytecode.

Have you considered Microsoft's C/C++ compiler targetted at .Net. That
compiles to a bytecode known as MSIL which is then interpreted and/or JIT
compiled to machine code.

I love Python, but IMHO it's a bit silly to maintain that the fact that
Python compiles to byte code instead of assembly code/machine code is
purely a matter of implementation; on the contrary, I believe it's a
result of its design. I also think that there's a large difference
between byte code and machine code (in Python's case; I haven't looked
at other languages), and that it's a bit silly to try to trivialize that
difference.

And then there's IronPython which is targetted at .Net. That compiles to a
bytecode known as MSIL which is then interpreted and/or JIT compiled to
machine code.

--
Duncan Booth http://kupuguy.blogspot.com

[Arnaud Delobelle]

brad <by*******@gmai l.comwrites:

>Vicent Giner wrote:

>The usual answer is that development time is more important than
running time.

This depends. Run time is not important until you are asked to scale
to millions or billions of users or computations or large data
sets. I've seen this first hand. Getting results back the same day or
sooner may be important. In cases such as this, I use C or
C++... nothing else will do. Nothing else is as fast. Although I
always keep a py version around for testing and for smaller
tasks. Don't get me wrong, I love Python, but there are times when
nothing, but pure, hard speed will do.

Sure. Be careful not to overdose on it though.

--
Arnaud

[sturlamolden]

On May 19, 8:07 pm, Vicent Giner <vgi...@gmail.c omwrote:

By the way, is it possible (and easy) to call a C function from a
Python program??

Yes it is. You can e.g. use ctypes for that.

[sturlamolden]

On May 19, 10:42 pm, "bruno.desthuil [e-mail] "
<bruno.desthuil [e-mail] wrote:

Well... They do - they are called 'C compilers' !-) As Roel Schroven
mentioned - and he is at least partially right on this point - C has
been designed to make optimizing C compiler not to hairy to write.

C has proven very difficult to optimize, particularly because pointer
aliasing prevents efficient register allocation.

Fortran was designed with ease of optimization in mind. Not many years
ago, it was not uncommon for Fortran code to run twice as fast as
equivalent C. C compilers have recently closed on on the gap by
becoming extremely good at what they do. But that is not because C is
easy to optimize. On the contrary.

For serious number crunshing, there is nothing that compares to
Fortran, even today. f2py makes it easy to call Fortran subroutines
from Python.

[Grant Edwards]

On 2008-05-20, Ivan Illarionov <iv************ *@gmail.comwrot e:

On Mon, 19 May 2008 11:07:06 -0700, Vicent Giner wrote:
[...]

>>
By the way, is it possible (and easy) to call a C function from a Python
program??

Yes.

http://groups.google.com/group/comp....47913a265c348a

Even easier:

http://docs.python.org/lib/module-ctypes.html

--
Grant Edwards grante Yow! I'd like some JUNK
at FOOD ... and then I want to
visi.com be ALONE --