We have seen how to measure the total time that a function takes to run (#185), but that doesn't help us with knowing which parts of the code are slow!
To look into that, we need to use a different too called a profiler. Python comes with its own profiler, but we will use a more convenient tool.
Setup
This exercise will work with IPython or Jupyter notebooks, and will use two "magic" commands available there. The %prun magic should be available with every installation of the IPython/Jupyter. However, you may need to install the second magic (%lprun).
If you use Anaconda, run conda install line_profiler from a terminal. Otherwise, use pip install line_profiler.
Using profiling tools in IPython/Jupyter notebook
prun's magic gives us information about every function called.
def sum_of_lists(N):
total = 0
for i in range(5):
L = [j ^ (j >> i) for j in range(N)]
# j >> i == j // 2 ** i (shift j bits i places to the right)
# j ^ i -> bitwise exclusive or; j's bit doesn't change if i's = 0, changes to complement if i's = 1
total += sum(L)
return total
run %prun:
%prun sum_of_lists(10_000_000)
Look at the table of results. What information does it give you? Can you find which operation takes the most time? (You may find it useful to look at the last column first)
Using a line profiler in IPython/Jupyter
While prun presents its results by function, the lprun magic gives us line-by-line details.
Load the extension on your IPython shell or Jupyter notebook
%load_ext line_profiler
Run %lprun
%lprun -f sum_of_lists sum_of_lists(10_000_000)
Can you interpret the results? On which line is most of the time spent?
We have seen how to measure the total time that a function takes to run (#185), but that doesn't help us with knowing which parts of the code are slow!
To look into that, we need to use a different too called a profiler. Python comes with its own profiler, but we will use a more convenient tool.
Setup
This exercise will work with IPython or Jupyter notebooks, and will use two "magic" commands available there. The
%prun
magic should be available with every installation of the IPython/Jupyter. However, you may need to install the second magic (%lprun
). If you use Anaconda, runconda install line_profiler
from a terminal. Otherwise, usepip install line_profiler
.Using profiling tools in IPython/Jupyter notebook
prun
's magic gives us information about every function called.%prun
:Using a line profiler in IPython/Jupyter
While
prun
presents its results by function, thelprun
magic gives us line-by-line details.%lprun