Friday, August 6, 2010

Python as a Research Tool

I love the Python programming language. It amazes me how when someone writes pseudo code to describe some algorithms, it tends to be a valid or almost valid Python code, even if the person who wrote it has no idea what Python is. Python is just the most natural way for humans to describe code.
Today I would like to discus the uses of Python as a research tool. I tend to believe that many different researches could benefit from this tool. I use Python for any kind of research I perform. Let’s take a look at my Python usage during the day:
First for any calculation I need to do, I use Python instead of calc.exe. This way I’ve got a log of all the operations I’ve been doing, I can play with the numbers in various ways, and see how everything changes if I just change a value in any of the steps of my calculation. I find the Python Reinteract interpreter, to be the best environment for the task. For those of you who are not familiar with Python Reinteract, it’s an interpreter in which you can go back to any executed line and change it, and see all the results reevaluated in cascade. A little bit like a Soviet encyclopedia, because it’s possible to rewrite the history.
This tool bring us to my college studies, in which I use Python to solve Linear Algebra and Calculus questions. The math modules that comes with Python and the Linear Algebra modules that comes with the Reinteract environment are perfect to solve, test, visualize, check guesses and gain better understanding of the studies.


But my true love is Idle-spoon, a simple variation of the well known idle-fork. The things that where added to the idle-fork in the idle-spoon version are better navigation, a Squeezer (shown in the pictures below) and enabling of more then one instance. When I preform research, the current status of the interrupter holds my current knowledge of the inspected target. I can access any piece of information, because it is all stored in global variables. This allows me to play with the data to try to make some sense of it.

The only thing I feel the lack of is a good assembly debugger to work inside the Python interpreter. As for PDB, I see no use for it due to the GDB syndrome it shows. GDB is a command line debugger that can make a good platform for writing debugging tools. But using the GDB directly is something that tends to be quite slow, ineffective, and limiting of expressiveness.
I’m currently checking the PyScripter, to see if it is any good, for now I can just say that it looks like there are still some functions missing or incomplete.

Other than the variants above (all built upon cPython), I found that there are more variants, such as iPython which doesn’t have any GUI based environment, and therefore I find it to be just a bit less comfort to work with. I love vim, and I sometimes use gvim to write big scripts. I once read in a book that there is a good eclipse plugin for developing Python, but it has no instant interpreter, and therefore should not be considered for research. And for last and least, the Iron Python / Jython, which should both be considered blasphemy. The implementation of the Python VM inside of the Java VM or any other VM, is something that makes no sense to me. It usually suffers from the lack of many modules that I’m used to work with, if it works at all.


Big thanks to the Fox for helping on the making of this blog post.