Do you believe in magic? You will after you read this week’s tip! ✨
But first: I’m including a “link of the week” in each issue to share something that I think is worth checking out!
🔗 Link of the week
Nine years after first reading it, this remains my top recommended text for learning the foundational principles of Machine Learning. Although the book’s code was originally written in R, the authors released a Python version which uses libraries like scikit-learn, statsmodels, NumPy, Matplotlib, and PyTorch.
👉 Tip #24: Use IPython magic commands for easier coding
I’m going to show you some “magic” tricks that will improve your coding experience in Jupyter. But first, a quick history lesson… 📖
In the early days of the Jupyter Notebook, it used to be called the IPython Notebook. That’s because it was initially built for Python only, whereas now the Notebook supports many other programming languages.
But why was it called the “IPython Notebook”, not the “Python Notebook”?
That’s because the IPython Notebook was built on top of IPython, which is an Interactive Python shell. IPython is basically a better version of the standard Python shell.
One of the neat features of IPython is “magic commands”, which I’ll demonstrate below. And because the IPython Notebook (and thus the Jupyter Notebook) was built on top of IPython, you can use IPython magic commands from within Jupyter! 🪄
Line magics vs Cell magics
There are two types of IPython magic commands:
- Line magics apply to one line of code, and they start with
- Cell magics apply to an entire cell, and they start with
For example, you can use the line magic
%lsmagic to list all of the magic commands:
You can use another line magic,
%quickref, to open a “quick reference card” that briefly describes each of the commands. (Try it out!)
Below are some of my favorite magic commands... 👇
%time runs a line of code once, times how long it took to run, and displays the output of the code:
%timeit runs a line of code many times and averages the timing results (for greater accuracy), but it does not display the output of the code:
%time for long-running processes (like a scikit-learn grid search) in which I want to know how long it took to run but I don’t actually want to watch it run!
%timeit when I need to accurately compare the performance of two different lines of code.
The use cases for
%%timeit are the same as the line magics above, except that these cell magics time the entire cell:
%who shows you all of the variables you’ve defined in the current session:
%whos is similar, but it prints some extra information about each variable:
%whos can be filtered by data type:
%history shows your input history from the current session:
There are many useful options for %history, which you can learn about by adding a question mark after the command:
(The question mark allows you to get help with any object in Jupyter, not just magic commands!)
One useful option is to add
-n for line numbers:
If you really want to blow your mind, use the
-g (global) option to see your entire history, meaning every command you've ever typed into Jupyter 🤯
That may overflow Jupyter, so you can include the
-f option to save it to a text file:
(The last line in my text file is “5230/15”, which means that I’ve started 5230 Jupyter sessions on this computer 😅)
A more practical use of
%history -g is to search for a particular line of code that you’ve written in the past. For example, I can filter my history to only show input that included “df”:
Another line magic that pairs well with
%pastebin, which makes it easy to share your code with someone else. For example, this code uploads lines 1 through 6 of your current session’s input history to a pastebin website:
You can then share the unique URL with anyone you like, and here’s what they would see:
There are many more magic commands, which you can read about in the IPython documentation.
There are also other IPython features worth learning about, such as the ability to run shell commands from within Jupyter!
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See you next Tuesday!
P.S. Officer: pop the trunk
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