WANG Cong wrote:
However, I think setattr() is a builtin function, using it exposes the *magic* of metaprogramming (or class-programming, if more correct) at a first glance.
But, in Python, creating instance variables is *not* class-programming. It doesn't touch the class at all. In many OO languages, such as Simula, C++ and Java, one of the responsibilities of a class is to define what attributes its instances have. However, that really comes about because those languages are statically typed -- it's not an essential principle of OO at all. In Python, restricting what attributes an object can have is *not* considered to be a responsibility of the class. The class is just a convenient place to put stuff (mostly methods) that some bunch of objects all need to have. Anything beyond that is up to the objects themselves. It so happens that, in most Python programs, all the instances of a given class will usually have a well- defined set of attributes. But Python doesn't go out of its way to enforce that. This is just a part of Python's general philosophy of not requiring declarations. There are very few declarative constructs in Python -- even class and function definitions are executable statements that construct data structures at run time. The only true declarations are the 'global' and 'nonlocal' statements, and they only exist because without them there would be no way to achieve certain things. They are not there to enforce any kind of static check. Why does Python not require declarations? Because it makes code easier and faster to develop. Instead of having to spend time and effort writing declarations, you just get straight on and write the code that does the actual work. And if you change your mind and need to move things around, you don't have to perform extra work to keep the declarations up to date. This can be a big help in the early stages of development, when you're feeling your way and the design is fluid. It also makes the program easier to extend and modify later. The downside is that certain kinds of error, that would be caught at compile time in a more static language, don't show up until you run the program. But if you're testing properly -- which you need to do anyway, whatever language you're using -- they usually show up pretty soon, and aren't much harder to fix when they do. Experience has shown that the overall process -- design, programming, testing and debugging -- tends to be faster using a dynamic, fluid language such as Python, than a static one such as C++ or Java. And, many people would say, more fun as well -- which is a good enough reason on its own for using Python! -- Greg -- http://mail.python.org/mailman/listinfo/python-list
