I'm a PhD student and use Python to write the code I use for my research.  My workflow often consists of making a small change to the code, running the program, seeing whether the results  improved, and repeating the process.  Because of this, I find myself spending more time waiting for my program to run than I do actually working on it (a common experience, I know).  I'm currently using the most recent version of Python 2 on my system, so my question is whether switching to Python 3 is going to give me any speed boost or not.  At this point, I don't really have a compelling reason to move to Python 3, so if the execution speeds are similar, I'll probably just stick with 2.x.  I know I'm going to have to modify my code a bit to get it working in Python 3, so it's not trivial to just test it on both versions to see which runs faster.  I'd need to be reasonably confident I will get a speed improvement before I spend the time updating my code to Python 3.
I have phylogenetics analysis that takes a long time to run, and uses about a half-dozen python scripts as well as other bioinformatics software (muscle, clustal, blast, even R!).  I use temp files to save intermediate results and a master script with the subprocess module to glue all the pieces together.  It's easy to change the master to run only the modified parts that I want to test.  But, if the changes are being made to early steps, and you only know how good it is at the end of the whole process, then this strategy wouldn't help much.
Python 2.x vs 3.x Speed