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Jupyter Notebook

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The Jupyter notebook is a web-based notebook environment for interactive computing.

Jupyter notebook example

Maintained versions

We maintain the two most recently released major versions of Jupyter Notebook, Classic Notebook v6 and Notebook v7. Notebook v5 is no longer maintained. All Notebook v5 users are strongly advised to upgrade to Classic Notebook v6 as soon as possible.

Upgrading to Notebook v7 may require more work, if you use custom extensions, as extensions written for Notebook v5 or Classic Notebook v6 are not compatible with Notebook v7.

Notebook v7

The newest major version of Notebook is based on:

  • JupyterLab components for the frontend
  • Jupyter Server for the Python server

This represents a significant change to the jupyter/notebook code base.

To learn more about Notebook v7: https://jupyter.org/enhancement-proposals/79-notebook-v7/notebook-v7.html

Classic Notebook v6

Maintenance and security-related issues only are now being addressed in the 6.5.x branch. It depends on nbclassic for the HTML/JavaScript/CSS assets.

New features and continuous improvement is now focused on Notebook v7 (see section above).

If you have an open pull request with a new feature or if you were planning to open one, we encourage switching over to the Jupyter Server and JupyterLab architecture, and distribute it as a server extension and / or JupyterLab prebuilt extension. That way your new feature will also be compatible with the new Notebook v7.

Jupyter notebook, the language-agnostic evolution of IPython notebook

Jupyter notebook is a language-agnostic HTML notebook application for Project Jupyter. In 2015, Jupyter notebook was released as a part of The Big Split™ of the IPython codebase. IPython 3 was the last major monolithic release containing both language-agnostic code, such as the IPython notebook, and language specific code, such as the IPython kernel for Python. As computing spans across many languages, Project Jupyter will continue to develop the language-agnostic Jupyter notebook in this repo and with the help of the community develop language specific kernels which are found in their own discrete repos.

Installation

You can find the installation documentation for the Jupyter platform, on ReadTheDocs. The documentation for advanced usage of Jupyter notebook can be found here.

For a local installation, make sure you have pip installed and run:

pip install notebook

Usage - Running Jupyter notebook

Running in a local installation

Launch with:

jupyter notebook

Installation

Platform-Specific Installation

Windows

  1. Using pip (recommended)
    • Install Python first from Python Downloads
    • Be sure to check "Add Python to PATH" during installation.
    • Open Command Prompt as Administrator and run: 
      pip install notebook
  2. Using Microsoft Store
    • Search for "Python" in the Microsoft Store
    • Install Python 3.x
    • Open Command Prompt and run: 
      pip install notebook

macOS

  1. Using pip Install Python first if not already installed
    • Option 1: Download from Python Downloads
    • Option 2: Using Homebrew 
      brew install python
    Then install Jupyter Notebook: 
    pip install notebook
  2. Using Homebrew directly 
    brew install jupyter

Linux

  1. Debian/Ubuntu 
    sudo apt update
sudo apt install python3-pip
pip3 install notebook
  2. Fedora/RHEL/CentOS 
    sudo dnf install python3-pip
pip3 install notebook

Using Conda

Conda is recommended if you need to manage multiple Python environments:

  • Install Miniconda or Anaconda first from Miniconda
  • Create a new environment (recommended): 
    conda create -n jupyter-env python=3.9
conda activate jupyter-env
  • Install Jupyter Notebook: 
    conda install -c conda-forge notebook

Common Installation Issues and Solutions

  1. Permission Errors

    • Windows: Run Command Prompt as Administrator
    • macOS/Linux: Use sudo pip install notebook or pip install --user notebook

  2. Outdated pip

    • Update pip before installation: 
      python -m pip install --upgrade pip

  3. "Command not found" after installation

    • Make sure Python's script directory is in your PATH
    • Windows: Try py -m notebook instead of jupyter notebook
    • macOS/Linux: Try python3 -m notebook

  4. Jupyter command not working after installation

    • Try running: 
      python -m notebook

  5. Dependency conflicts

    • Use virtual environments: 
      python -m venv jupyter-venv
# On Windows
jupyter-venv\Scripts\activate
# On macOS/Linux
source jupyter-venv/bin/activate
pip install notebook

For additional help, visit our troubleshooting guide or ask questions on the Jupyter Community Forum.

Running in a remote installation

You need some configuration before starting Jupyter notebook remotely. See Running a notebook server.

Development Installation

See CONTRIBUTING.md for how to set up a local development installation.

Contributing

If you are interested in contributing to the project, see CONTRIBUTING.md.

Community Guidelines and Code of Conduct

This repository is a Jupyter project and follows the Jupyter Community Guides and Code of Conduct.

Resources

About the Jupyter Development Team

The Jupyter Development Team is the set of all contributors to the Jupyter project. This includes all of the Jupyter subprojects.

The core team that coordinates development on GitHub can be found here: https://github.com/jupyter/.

Our Copyright Policy

Jupyter uses a shared copyright model. Each contributor maintains copyright over their contributions to Jupyter. But, it is important to note that these contributions are typically only changes to the repositories. Thus, the Jupyter source code, in its entirety is not the copyright of any single person or institution. Instead, it is the collective copyright of the entire Jupyter Development Team. If individual contributors want to maintain a record of what changes/contributions they have specific copyright on, they should indicate their copyright in the commit message of the change, when they commit the change to one of the Jupyter repositories.

With this in mind, the following banner should be used in any source code file to indicate the copyright and license terms:

# Copyright (c) Jupyter Development Team.
# Distributed under the terms of the Modified BSD License.

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