Five years ago the two most practical and used computer languages for me were C and Perl.
While I still use C for the nitty-gritty stuff that needs to be fast, I’m finding that a lot of stuff can get done, and get done very fast in a scripting language. Over a year ago I learned the wonders of Ruby (which, to me, is basically a superior replacement to Perl from a ‘it’s fun to code in’ perspective and is easy to transition to from Perl).
But overwhelmingly, I’ve found myself enjoying and using Python. The biggest selling point from my perspective is the high quality scientific computing and plotting support (which in many cases has replaced my use of R-project for these types of things).
Here are three little tidbits that I’ve recently found handy and take virtually no effort to begin using:
(1) First,to speed up the things that need the speed, calling C functions from Python is super-handy. I really like the ctypes module because in many cases, as long as your C functions take the default types as inputs, you can simply expose your function via a dynamic library with no real extra effort.
(2) List comprehensions are a fun and very useful feature in Python. But many times, you don’t want to create the whole list before iterating through it. Here’s where generator expressions come in. Instead of brackets around your comprehension, just put parens, and suddenly you can iterate over these elements without creating the entire list in advance (especially useful with a module like itertools).
(3) Finally, one thing that had bugged me a little in Python, especially since I’m used to C, is that there really is no real scanf equivalent . What I end up doing is parsing out my variables from a string and on separate lines explicitly setting their type. This just takes too many lines (and I could often do it in fewer lines in C)! After some thought, a lab mate and I converged on:
>>> types = [float, str, int]
>>> fields = [‘3.14159’, ‘Hello’, 10]
>>> pi, hi, ten = [f(x) for f,x in zip(types,fields)]
 Note that while there is a suggestion in the Python docs on how to do this, it just suggests how to extract different types with regular expressions, not concisely convert them.