No because competitive programming often focuses on speed, and python is not a very fast language.

Great question! As someone who has dabbled in programming contests a bit myself, I may have something to say.

[Let's get the standard disclaimer out of the way: contest programming is only loosely related to "programming in the real world", and while it tests algorithmic and problem-solving skills and the ability to come up with fast bug-free working code under time pressure, it does not necessarily correlate with being able to build large software projects, write maintainable code, etc (beyond the fact that well-structured programs are easier to debug).]

Now for some answers:

• C++/Java are more common than other languages in the real world as well, so you'd expect to see a higher proportion anywhere. (But it's even higher in the contest population.)

• Many of these participants are students, or got into contests as students, and C++/Java are more common "first languages" that students learn. (Undergrad students these days may start with Scheme, Haskell, Python, etc., but high-schoolers (often self-taught) less often.) In fact, many of the Eastern European participants still use Pascal, and are more amazing with it than the rest of us will ever be with any language.

• The school- and college-level contests usually use these languages. The International Olympiad in Informatics (IOI) allows only C, C++ and Pascal (or maybe it allows Java now; I haven't kept up), and the ACM Intercollegiate Programming Contest (ACM ICPC) allows only C, C++ and Java. TopCoder allows C++, Java, C# and VB (really :p); and recently, Python. So you could say the "contest ecosystem" has more C++/Java programmers in it. Google Code Jam and IPSC are among the few contests that allow code in any language, actually.

• Now the question is, in GCJ where the contestants are free to choose a language, why wouldn't they choose Python or Scheme? The most relevant factor is that these languages are slow. Sure, for most real-world programming they are easily fast enough, but for the tight loops that are often involved in getting a program to run under the n-second limit for all test cases, these languages don't cut it for any of the algorithmically more involved problems. (A problem designed to accept O(n log n) solutions but not Θ(n²) solutions for C/C++ frequently rules out even optimal O(n log n) solutions in slower languages. Even Java used to be given a handicap at USACO; I'm not sure this is still the case.)

• Another factor is the libraries: C++ and Java have better libraries for frequently useful algorithms and data structures (e.g. red-black trees, C++'s next_permutation), while Python's libraries (good enough for the real world) are less useful here, and Prolog and Scheme... I don't know about their libraries. This is a relatively minor factor, because these programmers can write their own code when necessary. :-)

• General-purpose multi-paradigm languages are more useful for just getting things done within the time constraints of the contest, than languages that force a philosophy or way of doing things on you. This is why Prolog will always remain unpopular, for instance. (General philosophy: some languages are "enabling" languages that let you do anything including shooting yourself in the foot, some are "directing" that force you to do things the right way.) This is also why C++ is three times more popular than Java in the general contest participants, and much more popular among the top contestants. Since code doesn't have to be read by anyone else, it's ok and even useful to have loop macros like FOR(i,n) (less code to type, and more importantly less chance of making a bug when in a hurry). Nothing against Java, there are a few top programmers who use Java too. :-)

• Finally, although many of these top programmers may have C++/Java/Pascal as their "first language", they are not good because of their language, so you don't have to despair about that. Many of these same programmers have won contests like the ICFP contest even with intentionally using crazy languages like shell scripts, m4 (used in autoconf), and assembly (the team named "You Can't Spell Awesome Without ASM").

u definitely would write code in python faster and it definitely would be slower than c++ in most cases

but since code speed doesnt matter to u all that much python is probably the better option for u

In my experience, when people have excess difficulty coding algorithms in C, it's often because they are tightly coupling their data structure management with their algorithm instead of creating appropriate abstractions. For example, manually manipulating linked list pointers everywhere instead of making push() and pop() functions. They are too accustomed to having those abstractions provided to them.

While this problem is much more evident with lower level abstractions, failure to recognize tight coupling and create appropriate abstractions is a problem at any level. Practicing these skills in C until you can make an algorithm that looks clean and readable will carry over to any language you use.

The other problem I occasionally see among python programmers is difficulty adapting for performance at scale. Granted, performance isn't usually the primary concern, but the most pythonic way to implement an algorithm for a relatively small data structure can grind your system to a halt when you're working with gigabytes or more of data. Becoming a good C programmer helps you be more aware of those kinds of issues in any language.

Can you learn those skills in other languages? Sure, but C helps by making it a lot more obvious when you get it wrong.

That being said, I use python for algorithmic programming when I have a choice, even though I'm just as comfortable in C. Python has language features that make it very nice for that kind of programming, and performance differences are usually negligible. I can't speak to why other programmers who know both would choose C. I imagine a lot of them do it simply to set themselves apart from the crowd.