5 Scripting

5.1 Imports

If you import a module using import sys, then you make the functions from sys available in your code using their fully qualified function names, e.g. sys.argv and sys.exit(). This is different to R, where using the library() function makes functions available using their short names, e.g. after calling library(dplyr) you can just call select(). To get this sort of behaviour in Python, some people use from sys import argv, exit which makes specified functions available using their short names. In general though, it makes sense to use fully qualified names unless they’re really long, in the same way that it makes sense to use functions in R using the :: notation.

To save you a bit of typing, you can rename the imported packages using the import <package> as <shortcut> syntax, e.g. import numpy as np. Going further, you can even do things like from numpy import array as np_array to import specific functions and rename them all in one step.

Python has a “standard library” of imports available, just like R. Some examples include sys, re and os.

You can also import constants from packages - e.g. math.pi.

Some important imports include: numpy, matplotlib, pandas.

5.2 Boilerplate

#!/usr/bin/env python

import sys

def main():
  print('Hello there', sys.argv[1])

if __name__ == '__main__':

In this example:

  • the shebang will use the correct Python conda environment (based on whichever conda env is active when the script is executed)
  • the package imports are included at the top of the file
  • the main() function is the part of the code that should run when you execute the script from the command line
  • The strange thing at the end calls the main() function