Huge News!Announcing our $40M Series B led by Abstract Ventures.Learn More
Socket
Sign inDemoInstall
Socket

nbconvert

Package Overview
Dependencies
Maintainers
14
Alerts
File Explorer

Advanced tools

Socket logo

Install Socket

Detect and block malicious and high-risk dependencies

Install

nbconvert

Converting Jupyter Notebooks (.ipynb files) to other formats. Output formats include asciidoc, html, latex, markdown, pdf, py, rst, script. nbconvert can be used both as a Python library (`import nbconvert`) or as a command line tool (invoked as `jupyter nbconvert ...`).

  • 7.16.4
  • PyPI
  • Socket score

Maintainers
14

nbconvert

Jupyter Notebook Conversion

Build Status Documentation Status

The nbconvert tool, jupyter nbconvert, converts notebooks to various other formats via Jinja templates. The nbconvert tool allows you to convert an .ipynb notebook file into various static formats including:

  • HTML
  • LaTeX
  • PDF
  • Reveal JS
  • Markdown (md)
  • ReStructured Text (rst)
  • executable script

Usage

From the command line, use nbconvert to convert a Jupyter notebook (input) to a a different format (output). The basic command structure is:

$ jupyter nbconvert --to <output format> <input notebook>

where <output format> is the desired output format and <input notebook> is the filename of the Jupyter notebook.

Example: Convert a notebook to HTML

Convert Jupyter notebook file, mynotebook.ipynb, to HTML using:

$ jupyter nbconvert --to html mynotebook.ipynb

This command creates an HTML output file named mynotebook.html.

Dev Install

Check if pandoc is installed (pandoc --version); if needed, install:

sudo apt-get install pandoc

Or

brew install pandoc

Install nbconvert for development using:

git clone https://github.com/jupyter/nbconvert.git
cd nbconvert
pip install -e .

Running the tests after a dev install above:

pip install nbconvert[test]
py.test --pyargs nbconvert

Documentation

Technical Support

Jupyter 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/.

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.

Keywords

FAQs


Did you know?

Socket

Socket for GitHub automatically highlights issues in each pull request and monitors the health of all your open source dependencies. Discover the contents of your packages and block harmful activity before you install or update your dependencies.

Install

Related posts

SocketSocket SOC 2 Logo

Product

  • Package Alerts
  • Integrations
  • Docs
  • Pricing
  • FAQ
  • Roadmap
  • Changelog

Packages

npm

Stay in touch

Get open source security insights delivered straight into your inbox.


  • Terms
  • Privacy
  • Security

Made with ⚡️ by Socket Inc