Jupyter Interactive Notebook.
https://jupyter-notebook.readthedocs.io/
The Jupyter notebook is a web-based notebook environment for interactive computing.
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 Notebook v5 is no longer maintained.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.
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
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 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.
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 notebookLaunch with:
jupyter notebookYou need some configuration before starting Jupyter notebook remotely. See Running a notebook server.
See CONTRIBUTING.md for how to set up a local development installation.
- Project Jupyter website
- Online Demo at jupyter.org/try
- Documentation for Jupyter notebook
- Korean Version of Installation
- Documentation for Project Jupyter
- Issues
- Technical support - Jupyter Google Group
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/.
from https://github.com/jupyter/notebook
（https://jupyter-notebook.readthedocs.io/en/stable/)
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Installing the classic Jupyter Notebook interface
This section includes instructions on how to get started with Jupyter Notebook. But there are multiple Jupyter user interfaces one can use, based on their needs. Please checkout the list and links below for additional information and instructions about how to get started with each of them.
This information explains how to install the Jupyter Notebook and the IPython kernel.
Prerequisite: Python
While Jupyter runs code in many programming languages, Python is a requirement for installing the Jupyter Notebook. The Python version required differs between Jupyter Notebook releases (e.g. Python 3.6+ for Notebook v6.3, and Python 3.7+ for Notebook v7) .
We recommend using the Anaconda distribution to install Python and Jupyter. We’ll go through its installation in the next section.
Installing Jupyter using Anaconda and conda
For new users, we highly recommend installing Anaconda. Anaconda conveniently installs Python, the Jupyter Notebook, and other commonly used packages for scientific computing and data science.
Use the following installation steps:
Download Anaconda. We recommend downloading Anaconda’s latest Python 3 version (currently Python 3.9).
Install the version of Anaconda which you downloaded, following the instructions on the download page.
Congratulations, you have installed Jupyter Notebook. To run the notebook:
jupyter notebookSee Running the Notebook for more details.
Alternative for experienced Python users: Installing Jupyter with pip
As an existing Python user, you may wish to install Jupyter using Python’s package manager, pip, instead of Anaconda.
First, ensure that you have the latest pip; older versions may have trouble with some dependencies:
pip3 install --upgrade pip
Then install the Jupyter Notebook using:
pip3 install jupyter
(Use pip if using legacy Python 2.)
Congratulations. You have installed Jupyter Notebook. See Running the Notebook for more details.
from
https://docs.jupyter.org/en/latest/install/notebook-classic.html
(https://docs.jupyter.org/en/latest/install.html)
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Installing Jupyter
Get up and running on your computer
Project Jupyter’s tools are available for installation via the Python Package Index, the leading repository of software created for the Python programming language.
This page uses instructions with pip, the recommended installation tool for Python. If you require environment management as opposed to just installation, look into conda, mamba, pipenv, and Homebrew.
JupyterLab
Install JupyterLab with pip:
pip install jupyterlab
Note: If you install JupyterLab with conda or mamba, we recommend using the conda-forge channel.
Once installed, launch JupyterLab with:
jupyter lab
Jupyter Notebook
Install the classic Jupyter Notebook with:
pip install notebook
To run the notebook:
jupyter notebook
Voilà
Install Voilà with:
pip install voila
Once installed, launch Voilà with:
voilafrom https://jupyter.org/install
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https://github.com/jupyter-book/jupyter-book
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Install Jupyter Book
You can install Jupyter Book via pip:
pip install -U jupyter-book
or via conda-forge:
conda install -c conda-forge jupyter-book
This will install everything you need to build a Jupyter Book locally.
The Jupyter Book command-line interface
Jupyter Book uses a command-line interface to perform a variety of actions. For example, building and cleaning books. You can run the following command to see what options are at your control:
jupyter-book --help
Usage: jupyter-book [OPTIONS] COMMAND [ARGS]...
Build and manage books with Jupyter.
Options:
--version Show the version and exit.
-h, --help Show this message and exit.
Commands:
build Convert your book's or page's content to HTML or a PDF.
clean Empty the _build directory except jupyter_cache.
config Inspect your _config.yml file.
create Create a Jupyter Book template that you can customize.
myst Manipulate MyST markdown files.
toc Command-line for sphinx-external-toc.
For more complete information about the CLI, see Command-line interface reference.
The book building process
Building a Jupyter Book broadly consists of these steps:
Create your book’s content. You structure your book with a collection of folders, files, and configuration. See Anatomy of a Jupyter Book.
Build your book. Using Jupyter Book’s command-line interface you can convert your pages into either an HTML or a PDF book. See Build your book.
Publish your book online. Once your book is built, you can share it with others. Most common is to build HTML, and host it as a public website. See Publish your book online.
Now that we’ve got a short overview, let’s get started building your first book.
from https://jupyterbook.org/en/stable/start/overview.html
(https://github.com/orgs/jupyter/repositories)
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https://app.readthedocs.org/projects/executablebookproject/
https://app.readthedocs.org/projects/executablebookproject/builds/25932438/
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https://executablebooks.org/en/latest/
https://executablebooks.org/en/latest/tools/
https://executablebooks.org/en/latest/blog/2024-05-20-jupyter-book-myst/
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