Python scripts are essentially pieces of code that can be written and run without having to be compiled into the software. This enables anyone familiar with Python to quickly and easily extend SVS 7 in a number of ways including, integrating with other command line programs (MACH, PLINK, etc.), automating a series of workflows, building custom analysis operations, and more. Python itself is a clear and powerful object-oriented programming language, comparable to Perl, Ruby, Scheme, or Java. It's relatively easy to learn and scripts written in Python are intuitive to read.
Included with Python in SVS are the mature statistical and numeric methods packages of NumPy and SciPy, giving SVS a broad base of standardized test statistics and linear algebra. Now both you and our own bioinformaticians supporting you can quickly adapt methods and build custom analyses to solve any unique challenges you encounter. Combined with the powerful interactive features of SVS, Python scripts using these packages are first class features with polished interfaces, interactions and logging support.
A fully integrated Python script editor enables you to quickly read, write, or edit scripts. It comes complete with automatic formatting and integrated command help. Upon finishing a script, just save it in the appropriate folder and the script will appear in the appropriate menu within the actual user interface, or spreadsheet column to which it applies. This enables those well versed in scripting to provide custom point-and-click features to their colleagues.
The Python Shell gives you access to analysis views programmatically while running in GUI mode. This feature is most useful for casual interaction with the program, such as running quick scripts, trying out new commands, or testing scripts.
Here are some resources to help you get started taking advantage of the power of scripting.