which bioinformatics tools are written in python?
I ask this question because new bioinformatic programmers or new pythoners like me can read the source code to find out how python can be used to deal with complex bioinformatics problems besides the problems solved in related books such as "Beginning Python for Bioinformatics"
I will chime in to say QIIME (http://www.qiime.org) is another example.
I believe you're right about the speed consideration, the ability of C or C++ to access low level RAM...etc lets one possibilities to tune a program as close to the hardware as possible (one can also try assembler), but I'm sure the way of coding to achieve a specific task is more critical. Look at, for instance, this biostar discussion. http://www.biostars.org/post/show/10353/how-to-efficiently-parse-a-huge-fastq-file/ (Leszek answer). For the thread interest I would say: Python is good, but use dict() and set() types instead of lists whenever you can.
My answer is malformated due to the transition of the website. If you read my answer together with reformated table in a separate answer, you will know a proper C/C++ implementation is 4-fold faster than Leszek's script. The C++ one is slow due to a stdio synchronization issue which I only know recently. Also, each data structure has its own use. It is just in that example dict() is better.
OK, I see. When I read that answer properly the last time, the best implementation race was not over yet :-) However, that still supports the fact the way of coding is very critical, whatever the programming language. That is a very good post, I like biostar especially for that kind of these. BTW, I'll compile right back Pierre's code.
on formatting: a new fix is incoming will be applied over the weekend most likely