I think Python is for you. lennart wrote: > Can you define 'large'? Is that large in code, or large in database? I > don't know which database is supported. If its a external db, like > MySql, the query is performed through the software of MySql, am I > right? If I'm correct, the 'slowness' comes from the amount of code in > python itself, not from the database.
I'm afraid dakman's comment wasn't really very helpful. Size is not a problem in itself. Ok, if the code modules are very large, you will have a larger startup time, but this is probably even worse in lower level languages such as C/C++. The python byte code works at a higher level of abstraction than machine code, so the byte code files are much more compact than corresponding executable binaries from e.g. C/C++/Delphi. The Python programming language, with its classes, modules, packages etc is in my experience much better for writing large applications without causing a mess than e.g. C++. It's much easier to make a mess with C/C++'s "#include" than with Python's "import". The lack of static typing means that some problems that the compiler/linker would find in e.g. C++ development won't turn up until you test your code in Python, but you'll get to testing much faster with Python, and if you don't test well, you'll fail with any larger development project however clever your compiler and linker is. Due to Python's very dynamic nature, there are a lot of operations that will be much slower than in e.g. C or C++. For instance, if you write "a = b + c" in C, the compiler knows at compile time what types a, b and c are, and if they for example are ints, the addition will be translated into a few very simple and quick machine code instructions. In Python, the types typically won't be know until runtime. This means that the objects need to be inspected during execution to figure out what + means for these kinds of objects. Python also handles memory allocation etc. The consequence of this is that some kinds of programs that do millions of trivial things, such as cryptography applications where there are a lot of repeated multiplications and additions, would be much, much slower in pure Python than in pure C. This doesn't mean that Python is bad for a large group of applications. It means that for a large group of applications, there are some parts (for instance computationally intensive or e.g. interfacing with some kind of devices or third party products) that should be handled by extensions written in e.g. C. Whatever you plan to do, it's likely that the extensions you need already exists. There are such extensions for databases, networking, maths, cryptography, XML parsing, etc etc. I'm a programmer working with C, C++, Python, SQL etc, and despite 10 years of Python coding I never actually needed to code any C extension myself yet. It's very likely that you'll get away using 100% pure Python too. Note that large parts of your programs will be C code, but C code you didn't have to write yourself, and as far as your programming is concerned it could as well have been Python, it's just that things will run faster than if it had been pure Python... Have fun! -- http://mail.python.org/mailman/listinfo/python-list
