How to Install JupyterLab: Step-by-Step Guide

Whether you’re a data scientist, a student, or a developer diving into data exploration or machine learning projects, JupyterLab is one of the most powerful interactive development environments you can use. It’s a flexible, extensible open-source platform where you can combine code, text, and visualizations seamlessly. But before the magic can begin, the first step is getting JupyterLab installed on your system correctly.

In this article, we’ll walk you through the installation process of JupyterLab in a way that’s both detailed and easy to follow. No matter if you’re using Windows, MacOS, or Linux, this guide has got you covered.

Contents

TL;DR (Too Long; Didn’t Read)

To install JupyterLab, ensure you have Python and pip or conda installed. Then, simply run pip install jupyterlab or conda install -c conda-forge jupyterlab. It’s recommended to use a virtual environment to keep things organized. Once installed, launch with jupyter lab in your terminal. Easy to set up and incredibly powerful once running!

1. What is JupyterLab?

JupyterLab is the next-generation interface for Project Jupyter. It offers all the features of the classic Jupyter Notebook, but with a modern interface that allows you to arrange multiple panels in tabs, run terminal commands, and open CSV files directly. Ideal for those working in data science, scientific computing, or even education.

JupyterLab supports code execution in numerous programming languages (Python being the most popular), creating dynamic notebooks that combine code, markdown, and results—all in one document.

2. Prerequisites: What You Need Before Installation

Before diving in, make sure you’ve got the necessary ingredients installed on your system. These include:

  • Python (Version 3.6 or later recommended)
  • pip — Python’s package installer
  • Virtual Environment Manager like venv or conda (optional but highly recommended)

You can check these by running the following commands in your terminal or command prompt:

python --version
pip --version

If you’re using conda (from Anaconda or Miniconda), you can verify its presence with:

conda --version

3. Setting Up a Virtual Environment (Optional but Recommended)

Creating a virtual environment ensures that your packages are organized and don’t interfere with global Python settings. Here’s how to set one up using venv:

python -m venv jupyter_env
source jupyter_env/bin/activate  # On macOS/Linux
jupyter_env\Scripts\activate     # On Windows

Alternatively, for conda users:

conda create -n jupyter_env python=3.10
conda activate jupyter_env

4. Installing JupyterLab

Using pip:

If you prefer pip, simply run the following command in your activated virtual environment:

pip install jupyterlab

This will fetch and install all dependencies, including the Jupyter engine and interface components.

Using conda:

With conda, installation is equally simple:

conda install -c conda-forge jupyterlab

This command installs JupyterLab from the community-maintained conda-forge channel, which is often more up-to-date than the default.

5. Verifying the Installation

To confirm that everything went smoothly, run this:

jupyter lab

This will open JupyterLab in your default web browser, typically served from http://localhost:8888. You’ll see a dashboard where you can create or upload notebooks, open terminals, and more.

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If the browser doesn’t launch automatically, simply copy and paste the URL displayed in the terminal into your web browser.

6. Using JupyterLab: A Quick Overview

Once you’re inside JupyterLab, you’ll see a modern web-based interface built for productivity. Here’s what you can do:

  • Create Notebooks: Start fresh or continue working on .ipynb files.
  • Use Consoles and Terminals: Open integrated terminals and interactive Python consoles.
  • File Browser: Navigate through project directories with ease.
  • Drag-and-Drop: Organize workspaces using tabbed panels and horizontal or vertical splits.

You can easily install extra extensions to enhance features such as version control integration, table of contents, and more.

7. Troubleshooting Common Installation Issues

  • Permission Denied: Try using pip install –user jupyterlab or run the command with elevated privileges.
  • pip not recognized: Ensure Python is added to your system’s PATH variable. Reinstalling Python and checking the “Add to PATH” box often resolves this.
  • conda command not found: Make sure Anaconda or Miniconda is installed properly, and that its directory is included in your system’s environment variable.

8. Updating JupyterLab

Technology evolves, and so should your tools. To update JupyterLab:

  • Using pip: 
    pip install --upgrade jupyterlab
  • Using conda: 
    conda update -c conda-forge jupyterlab

Keeping up with updates ensures compatibility with new extensions, improved performance, and enhanced features.

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9. Installing Useful Extensions (Optional)

JupyterLab supports a vibrant ecosystem of extensions that can enhance productivity, visualization, collaboration, and more. To use them:

pip install jupyterlab_code_formatter
jupyter labextension install @ryantam626/jupyterlab_code_formatter

You may also want to install extensions like:

  • jupyterlab-git – For version control
  • plotly – For interactive graphs
  • variable inspector – Shows active variables and values

Most extensions can also be managed via the official JupyterLab GitHub repositories.

10. Launching JupyterLab Automatically

If you plan to work with JupyterLab often, save time by creating shortcuts:

Windows:

  • Create a new text file and insert: cd path\to\your\env && jupyter lab
  • Save it as launch_jupyter.bat and double-click to run JupyterLab.

Mac/Linux:

  • Open terminal and type: alias jl=”jupyter lab”
  • Add this line to your .bashrc or .zshrc for persistent use.

Final Thoughts

Installing JupyterLab is a straightforward process that opens up a world of possibilities. Whether you’re crunching data, building models, or writing scientific papers, JupyterLab offers a consolidated platform that fits your needs. With its modular design, broad extension support, and user-friendly interface, it’s no wonder that JupyterLab has become a standard in research and industry environments worldwide.

So go ahead, get it installed, and start exploring data in an interactive and creative space like never before!

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