%time¶

Measue the execuation time of the code ONCE.

%timeit¶

Measure the execuation time of the code (accurately) by running it MULTIPLE TIMES and taking the average.

%prun | %%prun¶

-D: output the profiling results into a file so that you can other tools (e.g., snakeviz) to visualize it.

Noticd that %prun and %%prun are based on cProfile or profile, which are designed to provide an execution profile for a given program, not for benchmarking purposes (for that, there is time and timeit for reasonably accurate results). This particularly applies to benchmarking Python code against C code: the profilers introduce overhead for Python code, but not for C-level functions, and so the C code would seem faster than any Python one. Overall, %prun and %%prun might slow down your Python code up to 3 times.

%lprun | %%lprun¶

%%snakeviz¶

pyheatmagic¶

Installation¶

pip3 install py-heat-magic

Usage¶

Load the magic.

%load_ext heat

%%heat

%%heat -o file.png

Line Profiler¶

Within your jupyter notebook, call: %load_ext line_profiler

References¶

• Profile Performance of Python Applications

• https://mortada.net/easily-profile-python-code-in-jupyter.html

• https://jiffyclub.github.io/snakeviz/

• How can you profile a Python script?