This lesson introduces the basics of profiling and optimising Python code. The course is designed to be accessible to Python users of all skill levels (beyond total beginner). The optimisations presented should be considered performance best practices, they are demonstrated with small programming patterns that demonstrate multiple approaches in code to achieve the same result with differing performance.

This course was originally authored by and is currently maintained by @Robadob, it is a fork of the University of Sheffield branded course. Both repositories are maintained, so issues will be monitored .

See Contributing

The initial development of this course was funded by the University of Sheffield, to support training initiatives for users of their Stanage HPC cluster.

If you are making complex changes, and wish to build the site locally the below instructions can be followed.

Both of these steps should be followed within rterm.

# Setup mirrors
options(repos = c(
  carpentries = "https://carpentries.r-universe.dev/", 
  CRAN = "https://cran.rstudio.com/"
))
# Setup install from github
install.packages("devtools")
library(devtools)
# Install Uni of Shef Varnish theme
install_github("RSE-Sheffield/uos-varnish")
# Install remaining official carpentries packages
install.packages(c("sandpaper", "tinkr", "pegboard"))

sandpaper::serve()