BioPython includes tools for reading DNA/RNA/Protein sequence and structure information from common biological file formats, including FASTA, PDB, etc. It also includes functions for many common operations such as sequence alignment, feature detection and analysis.
High performance Python, including inline Fortran and C/C++
This page has information, benchmarks and example code relating to high performance Python. It includes nice introductions to weave.inline, which lets you include C code in Python, and f2py, which lets you call wrapped Fortran functions.
Use Matlab functions in Python with mlabwrap
This works in much the same way as the previously mentioned RPy2.
Use R functions in Python with RPy2
If you have a lot of R code that you don’t want to convert to Python, this is a life saver!
Tablib: A convenient library for working with tabular data sets in a variety of formats
If you work with textual, tabular data sets frequently, this library will make your life easier.
IPython/PyLab cheat sheet
This cheat sheet will save you a ton of time. You should definitely print it out and keep it somewhere handy.
Matplotlib visualization gallery (with example code)
This gallery contains examples of various things you can do with matplotlib. If you would like to create a visualization, I suggest you go to this page, find a visualization you like, and try to modify the code to suite your needs.
SciPy reference guide
This guide contains reference information for the SciPy API. This is not a guide or tutorial, but is useful if you just want to figure out how a particular function or class is used.
NumPy reference guide
This guide contains reference information for the NumPy API. This is not a guide or tutorial, but is useful if you just want to figure out how a particular function or class is used.
Enthought Canopy (hassle free Python distribution)
Installing all the libraries used for scientific computing in Python can be a big hassle. Enthought Canopy has everything you need.