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JupyterLab is a web-based interactive development environment for notebooks, code, and data. It supports over 40 programming languages, including Python, and integrates with big data tools and JupyterHub.
- Install
Project Jupyter’s tools are available for installation via...
- Try
Try Jupyter. Use our tools without installing anything....
- Jupyterlite
Jupyterlite - Project Jupyter | Home
- Get Involved
Intro to Python for Kids, Parents & Teachers Series: (Tariq...
- Documentation
An interactive Python kernel and REPL. Reference. APIs....
- News
The Jupyter Blog. JupyterLab 3 end of maintenance. The...
- Governance
By The Jupyter Book community To the extent possible under...
- Security
The Jupyter Notebook is a web-based interactive computing...
- Install
Learn how to use Jupyter tools for interactive computing workflows with different programming languages. Explore JupyterLab, Jupyter Notebook, JupyterLite, Jupyter Widgets, and Voilà online for free.
WASM powered Jupyter running in the browser.
- Jupyter Lab vs Jupyter Notebook
- Advantages of Using Jupyter Lab and Notebook
- How to Install Jupyter Notebook and Lab
- Start and Explore Jupyterlab
- Your First Steps in A Notebook
- Jupyterlab Plugins
- Ipython
- Jupyter Notebook in Vscode
- Keep Learning
- GeneratedCaptionsTabForHeroSec
JupyterLab is a web-based, interactive development environment. It’s most well known for offering a so-called notebook called Jupyter Notebook, but you can also use it to create and edit other files, like code, text files, and markdownfiles. In addition, it allows you to open a Python terminal, as most IDEs do, to experiment and tinker. JupyterLab ...
Python application developers often prefer and work with a regular Python IDE like VSCode, which facilitates debugging, unit testing, deployment, and version management. In contrast, (data) scientists and data analysts have a different focus and often prefer a Notebook-style IDE. Let’s look at some of the advantages these notebooks have to offer.
Like all Python software, installing Jupyter Lab is a breeze. I’ll demonstrate how to install with both Pip and Conda. One thing to note beforehand: I recommend installing this system-wide. I usually stress the importance of using a virtual environment. However, I feel that tools like this you want to install once.
How to open Jupyter Lab from the command line
If you followed the installation instructions, you should be able to start Jupyter Lab with:
How to open Jupyter Notebook from the command line
If you only want to start a Notebook, use this:
Adding to your PATH
If you get an error like “command not found,” don’t panic. Unfortunately, some systems don’t have the .local/bin directory in the $PATHvariable.
If you start Jupyter Lab or Notebook, it will automatically open your browser. If it didn’t, you can go to http://localhost:8888/ manually to open it. Once there, create a new Notebook, e.g., by clicking File -> New -> Notebook. I created a new Notebook named ‘First steps’ in the following screenshot. There are a couple of noteworthy things to see:...
If you click on the puzzle icon at the left of the screen, you’ll get a list of plugins that can be installed directly. There are lots of plugins, and many of them will add extra visualization capabilities or integration with products like Tableau.
Internally, Jupyter Notebooks use a project called IPython. If you tend to use the Python REPL a lot, I recommend you to read our page on IPythonsince it is an excellent alternative to the regular REPL. I use it a lot personally, and I can’t recommend it enough! For example, it’s worth it just for its terrific auto-completion, and if you are used t...
If you’re a VSCode fan, like me, you need to check out the VSCode extension that allows you to create and work with notebooks directly inside a VSCode tab. If you open up the command pallet, e.g., with ctrl + shift + p, start typing “Jupyter” to create, open, and export Notebooks.
This article is part of a free Python Tutorial. You can browse the tutorial with the navigation buttons at the top and bottom of the article or use the navigation menu. Want to learn more? Here are some great follow-up reads: 1. Learn about NumPy, the foundation of data science in Python. 2. It’s always worth visiting the official project websitefo...
Learn about Jupyter Notebook, a web-based interactive environment for data science and machine learning. Find out how to install it with Pip or Conda, and how to use it with Jupyter Lab or VSCode.
Jupyter Notebook is a notebook authoring application, under the Project Jupyter umbrella. Built on the power of the computational notebook format , Jupyter Notebook offers fast, interactive new ways to prototype and explain your code, explore and visualize your data, and share your ideas with others.
Learn how to install, run, and use Jupyter Notebook, an open source web application for creating and sharing documents with live code, equations, visualizations, and text. Jupyter Notebook supports Python, Julia, R, and many other kernels.
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This web page introduces Jupyter, a platform for interactive computing with different kernels, but does not mention Python. To use Python with Jupyter, you need to install Jupyter locally or use a cloud service like Binder.
