Hi Lina, On 8 October 2011 18:18, lina <lina.lastn...@gmail.com> wrote:
> I write mainly critical speed code and large memory code that are meant to > run as hug jobs over cluster (transportability is an issue; > my C code is really faster than my Maple code; interpreter language are > good for development of algorithm in view to write a fast C code; > speed does not involved human time but machine time; I do not really care > about candy interfaces; for human interface Python and alike are recommended > but BASH (and even DASH) can do very good job; I am not sure that a > scientist is more concerned with interface than with efficient code except > for > visual stuff; being very familiar with of a given language is certainly > better than knowing superficially a lot of languages; > as a lot of interpreter languages, Python has a huge manual; C manual is > rather small; D is both a interpreter language and a compiler language: > it is why I want to learn D: no more need to write wrapper that can be > boring and that can be bottle neck. > I should think that the Core Python *language* manual is almost certainly smaller than the C one. (The base Python language is actually rather small and concise. What typically makes Python books larger in general is I think actually the (so called "batteries included") extensive set of libraries and modules included and commonly available for the language, not the Python language itself.) As for the compiler/interpreter argument, I'll just point out again that actually Python in its various forms can either be compiled and/or interepreted, it depends on you really. For compiled Python flavours, see for example Cython (http://cython.org/) which provides a way to write C/C++ modules for Python effectively in Python syntax. (Cython arguably also makes the "need to write wrapper" comment a moot point.) Or see Shedskin ( http://shed-skin.blogspot.com/), a Python to C++ static compiler), or Psyco (http://psyco.sourceforge.net/introduction.html ), a JIT (Just In Time) compiler for CPython. Or see Pypy (http://pypy.org/) which is another reimplementation of the Python language with an optimizing JIT compiler. (The following post re realtime image processing in Python is rather impressive: http://morepypy.blogspot.com/2011/07/realtime-image-processing-in-python.html) I'd like to also mention that there's many many Python packages of interest or used by the scientific community, not least NumPy/SciPy ( http://numpy.scipy.org/ and http://www.scipy.org/). For a more complete list see: http://www.scipy.org/Topical_Software You'll see that Python is used extensively in many science and engineering contexts. Lastly regarding (user) interfaces -- as has already been pointed out, Python can obviously do UI's, but it's by no means limited to being some sort of front-end language. Anyway, I think I'll leave it at that for now. Walter
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