On May 17, 7:32 pm, Vicent Giner <[EMAIL PROTECTED]> wrote: > 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.
I guess that python is not a good language for that. Algorithms implemented in plain python are many times slower than C ones (hundreds ?). In practice, algorithms are written in C and wrapped in python. I have near zero experience in operations research, but once I looked for linear programming toolkits for python and IIRC, I only could find a trivial wrapper for glpk (called pulp). My opinion: choose compiled or byte compiled languages. Choose the language paradigm that best suit the algorithms. -- http://mail.python.org/mailman/listinfo/python-list
