Throughout my luxurious 24 published article career on Medium I realized i’m in a position to begin giving my opinion, and Jupyter notebooks still seems to be an area where people overlook, and without a doubt I believe Jupyter notebooks can be a super awesome addition to your current coding landscape.
Beginning & Testing
One of my favorite things about Jupyter notebooks would be the testing phases of a project, before I open up PyCharm or any other IDE, I tend to test my code within Jupyter to actually start building out the concept of the code. Depending on the project it may not be feasible to use Jupyter to my knowledge (such as game development, etc.), but for most data science tasks Jupyter can be an awesome point to start off. For example, if you’re working on a certain project within Jupyter, you can begin working on certain chunks of code in Jupyter, test & debug the code within Jupyter, then bring the code over to another IDE if needed. Since Jupyter can run code natively within it’s environment, it’s a great place to begin any project.
Readability of Code
A very useful thing within Jupyter is that it allows you to leave blocks of space with actual customizable text. A common problem with a regular script in another language is that it requires you to leave the standard common syntax for a comment, but it can become pretty bland. For someone who built the program the comments may make perfect sense, but if you share the program to someone else they may not fully understand the program. Take a look at an example of what a Jupyter notebook can look like below:
This definitely looks alot better than just leaving comments in the code.
Multiple Language Support
Within Jupyter, there is over 40 languages that are supported, including Python, R, Scala and Julia. These are massively popular languages for programming, and having an environment where you can run any of these languages is very powerful. Since Jupyter Notebook allows these languages, you can utilize the same features listed before within these languages as well! Instead of downloading different IDE’s for each language, you can use Jupyter Notebook for all of your programming needs.
And there you have it! Those are just a few reasons why I would recommend using a Jupyter Notebook! Although it isn’t perfect, it’s still a very powerful utility to have in your programming toolbox.