Writing Better Jupyter Notebook Code

Henk Griffioen shows how to write Python code in your IDE of choice and then synchronize a Jupyter Notebook with the results:

How can you get the interactivity back and get our changes immediately in our Notebook? Add %autoreload at the top of your Notebook:

%loadext autoreload # Load the extension%autoreload 2 # Autoreload all modules

%autoreload is a Jupyter extension that reloads modules before executing your code. Functions and classes loaded in notebooks get their functionality updated every time you execute a cell. This means that when new code is saved in the editor, the changes are immediately loaded in your Notebook if you run a cell.

Using %autoreload bridges the gap between Notebook and IDE. You gain all the benefits of an IDE, but you’re still as flexible as before! See the GIF at the top as an example.

That’s a useful trick.  I’ve tended to use notebooks more for post-hoc work, where I’ve already structured my code and want to formalize it for others to use.

Related Posts

Building Credit Scorecards

Andre Violante uses SAS to build credit scorecards and analyze credit data: For this analysis I’m using the SAS Open Source library called SWAT (Scripting Wrapper for Analytics Transfer) to code in Python and execute SAS CAS Action Sets. SWAT acts as a bridge between the python language to CAS Action Sets. CAS Action Sets are synonymous to libraries […]

Read More

A Functional Approach To PySpark

Tristan Robinson shows us how we can implement a transform function which makes Python code look a little bit more functional: After a small bit of research I discovered the concept of monkey patching (modifying a program to extend its local execution) the DataFrame object to include a transform function. This function is missing from […]

Read More

Categories

August 2018
MTWTFSS
« Jul Sep »
 12345
6789101112
13141516171819
20212223242526
2728293031