Overview
- Beta release of JupyterLab for the general public
- Has all the familiar Jupyter notebook features plus third party extensions
- You can use extensions to work with various data formats such as CSV, JSON and GeoJSON.
Introduction
It took three years in the making, but finally JupyterLab has been launched for everyone! The JupyterLab team has announced the beta release series of JupyterLab, a web-based user interface for Project Jupyter.
It includes all the usual components of the classic Jupyter Notebook (notebook, terminal, text editor, file browser, rich outputs, etc.) in a flexible and ultra powerful UI that can be extended through third party extensions.
JupyterLab is an extensible environment for interactive computing, specially designed based on the Jupyter notebook architecture, an open-source web application.
Source: Jupyter blog
In addition to the core JupyterLab developers, more than hundred contributers spent three years to build JupyterLab. With over 11,000 commits and 2,000 releases of npm and Python packages, JupyterLab is made available for regular users.
With the exponential growth of data science and machine learning, Jupyter notebook is extensively being used for operations such as data cleaning, data transformation, numerical simulation, statistical modeling, data visualization, etc. JupyterLab provides full support for Jupyter notebooks along with access to custom components, such as text editors or data file viewers.
Apart from that, JupyterLab provides a high level of integration between the notebooks and documents. The Jupyter blog also mentions a list of activities that a user can perform, such as, using diverse file formats (like Markdown, Vega, VegaLite etc.) or linking your code console to the notebook, and whole other plethora of options!
Apart from this, JupyterLab offers multiple extensions to customise and enhance your notebook. As an independent company or user, you also have the option to develop your own extensions! To know more about this, refer to the JupyterLab Extension Developer Guide.
To install JupyterLab on your machine, follow these steps.
Our take on this
JupyterLab will make working on remote servers much easier. It also let’s a user have terminals, notebooks and file editors all in one browser, thus making it more convenient and suitable.
First Impressions
We took JupyerLab for a proverbial spin and below is a summary of what we liked:
- One of the biggest differences between between Jupyter notebooks and JupyterLab is that the latter is more command centric and far more interactive
- We really liked the collapsing cells and drag-and-drop cells feature
- Other features likes the console editor, single document mode, image file viewing and side by side editing are promising
- JupyterLab is basically a mix of text editor, IDE and notebook
There are quite a few IDEs floating around for python but with this release, JupyterLab is showing a lot of promise. It will definitely be our go-to IDE for the foreseeable future.
After this beta release, the JupyterLab team plans to release version 1.0 later on this year. It will focus on stabilizing the extension development API, user interface improvements, and additional core features. We can’t wait to get our hands on that!
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An avid reader and blogger who loves exploring the endless world of data science and artificial intelligence. Fascinated by the limitless applications of ML and AI; eager to learn and discover the depths of data science.
