2.2 KiB
| title | updated | created |
|---|---|---|
| Jupyter Built-in magic commands | 2022-04-26 11:13:12Z | 2022-04-26 10:31:22Z |
references
%lsmagic # list of all magic methods %quickref # cheatsheet %magic %lsmagic
Timeit
%%timeit -n 3 %time
The %timeit magic runs the given code many times, then returns the speed of the fastest result.
%timeit sum(range(100000))
The %%timeit cell magic can be used to time blocks of code. Start cell
| Options | Description |
|---|---|
| -n<N> | It executes the code statement <N>times in a loop. If the number is not given, it determines the to get good accuracy. |
| -r<R> | Shows the number of repeats. |
| -p<P> | Used to calculate the precision of <P>digits to show the timing result. |
| -c | Use time.clock; default function on Windows to measure the wall time. |
| -t | Use time.time; the default function on Unix measures the wall time. |
| -q | Use for Quiet; do not display any result. |
| -o | Returns the TimeitResult that is further stored in a variable to view more details |
%%timeit -n 3
a = 0
for i in range(100000):
a += i
The %time magic times a single run of a function
%time sum(range(100000))
run scripts
%run somescript.py
%run -d myscript.py # debug
reset kernel
%reset is not a kernel restart
Matplotlib
from matplotlib import pyplot as plt
%matplotlib inline
%matplotlib # set matplotlib to work interactively; does not import anythig %matplotlib inline %matplotlib qt # request a specific GUI backend
debugging
%debug # jump into the Python debugger (pdb) %pdb # start the debugger on any uncaught exception.
%cd # change directory %pwd # print working directory %env # OS environment variables
OS command
!OScommand !ping www.bbc.co.uk %alias # system command alias !!date # output ['Sat Jan 19 02:53:54 UTC 2019'] %system date
Auto reload
%load_ext autoreload %autoreload When you are working with external tools or changing the enviornment variables, this will certainly help you a lot. The external commands help you autoreload the tools and libraries at a specified defined interval. So whenever there is even a minor change, we do not have to run the imports to update the local enviornment of the notebook