Episode: Function Level Profiling

[Robadob]

Learning Objectives

• execute a Python program via cprofile to collect profiling information about a Python program’s execution
• use snakeviz to visualise profiling information output by cprofile
• interpret snakeviz views, to identify the functions where time is being spent during a program’s execution

Exercises

• Example algorithm, with a synthetic bottleneck which produces a clear hierarchy.
• Example algorithm, with a synthetic bottleneck, which produces a more complex hierarchy.
• Example algorithm, with a (hidden) synthetic bottleneck, which leads to a complex function. (to lead into the next episode)

Keypoints

• A python program can be function level profiled with cprofile via python -m cprofile -o <output file> <script name/arguments>
• The output file from cprofile can be visualised with snakeviz via python -m snakeviz <output file>
• Function level profiling output displays the nested call hierarchy, listing both the cumulative and total minus sub functions time.