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7 Must Have Jupyter Notebook Extensions to Increase Productivity

Anshul_Aggarwal
Published: November 8, 2022

The basics of Jupyter Notebook is to offer an extensive approach while working on any project to offer feasibility to developers. There are times when developers are stuck in small bugs, typos errors, or even while integration and to support this function and enhance its capability, they can now work seamlessly either for selecting or viewing any particular line of code or running debuggers.  

Best Jupyter Notebook Extensions

 

These features offer rich outputs and save a lot of time and effort and by using these extensions, developers can easily provide an API for other extensions to connect with their current project. In other words, the Jupyter Notebook is an open-source web app that delivers a powerful output and can be customized as per need. 

Although there are hundreds of extensions available (official and unofficial), here we’re going to discuss some of the best Jupyter Notebook Extensions to Increase Productivity that can ease the coding life of any developer.

7 Must-Have Jupyter Notebook Extensions to Increase Productivity

1. Spellchecker

SPellchecker is one of the most useful extensions to have in an IDE as this extension alert developers whenever there is any spelling mistake/typos error and the same gets highlighted in Red Colour so that doesn’t get missed. Besides this, the extension offers support for the following languages:

  • English (for America, Britain, Australia, and Canada)
  • French
  • German
  • Spanish
  • Portuguese

Spellchecker can be downloaded from the following syntax:

conda install -c conda-forge jupyterlab-spellchecker

2. Debugger

The purpose of this extension was to offer a quick outcome to maintain the workstream and that’s why Debugger became one the best source of finding and fixing bugs. This extension works with Jupyter notebook, (for both console and source files) and elevates the capability so that the model can work properly.

The extension can be downloaded from the following syntax:

jupyter labextension install @jupyterlab/debugger

Besides this, it’s more or less like pixie-dust GUI (which was the first debugging tool in Python) and fits well with Jupyter Notebook.

3. Variable Inspector

It helps in collecting defined variables after collecting and previews within a floating window. The variable inspector enables users to show previews of their type, and size along with the content. The best part is the columns are sortable and that’s why the floated window can easily be dragged, resized, and collapsed as per requirement. 

To install Variable Inspector, enter the following:

pip install lckr-jupyterlab-variableinspector

Besides this, it also holds some major key features that developers need to implement while working with variable inspector:

  • A developer can easily inspect the interactivity and inline
  • This extension is suitable for python and Jupyter (currently supports python and R kernels)
  • While working on a limited matrix – this extension can be used to view matrices in Datagrid-pattern.

4. GIT

There isn’t any developer who might not have used Git in their coding period either as a student or professional life. Jupyter enables developers to make necessary changes and push their codes so that it doesn’t get misplaced, or adulterated and can easily be recalled when required. This extension allows users/developers to integrate with their projects and it’s a purely open and free-to-use VCS (version control system) platform. 

In other words, it allows the user to control the version and this can be simply opened from the Git tab on the panel, and further modifications are allowed as per requirement. 

If you wish to learn how you can upload your project from Jupyter, refer to this article for better clarity: How to Upload Project on GitHub from Jupyter Notebook?

Here’s an awesome course to let you have a clear idea of the basics of Python Python Programming Foundation -Self Paced in which along with learning you’ll learn to implement those and will also get assistance when in doubt.

5. NBdime

This is one of the most elegant tools that helps in diffing and merging while working on any project. It provides an opportunity to decide intelligently how to render image diffs in a web view and can resolve general conflicts (that includes execution counters.

You can download the nbdime following the below syntax:

pip install nbdime

Besides this, it also offers some major key features that developers need to implement while working with this extension:

  • Its auto-conflict function helps in merging notebooks in multiple ways.
  • A developer can easily view a notebook by simply using terminal
  • It helps in comparing notebooks in terminal-friendly
  • This extension uses diff tools for both input and output (only from existing ones)

6. Code Folding

This feature enables developers to perform folding a piece of code along with the main class or function. Developers generally use this feature to cut long lengths for ease and this also includes expand collapse, etc. add-ons. You can easily enable 

This can be performed by simply hitting Alt+F (default function) and you can also check the below-mentioned example for the best reference:

Python3

class MyClass(object):

    

    

    

    def afun(param1):

        

        return param1**2

7. Plotly

This is one of the most elegant, highly-interactive, open-source libraries which helps developers create unique charts based on stats, geographic, scientific, and 3-D dimension projects in a much simpler way.

This tool enables developers to work and visualize within Jupyter notebook and is also referred to as Plotly.py in a standard format. With the help of this extension, a developer can work on different desktop editors, including Spyder, PyCharm, etc., and the same file can be exported back into PDF formats.

This can easily be installed from below mentioned syntax:

pip install plotly

However, if you wish to learn more about this, refer to this article: Plotly Tutorial

Conclusion

Being a developer, it is a must to have clarity and selection of the right tool or extension so that it will help in uplifting your skill and will definitely save time as well. With the help of this article, we tried to summarize a list of 7 Must-Have Jupyter Notebook Extensions to Increase Productivity but the list is far too long. 

You might find some other extensions like Jupyter SQL, Spreadsheet, Spellchecker, etc. but the tools that we discussed will help you with daily basis work from which you can experiment and implement in your project. Besides this, you can also learn some of the best shortcuts along with the extensions for Jupyter  Notebook that will take you to next level with fluency.

Source: www.geeksforgeeks.org