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All Projects → jupyter → Nbconvert

jupyter / Nbconvert

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Jupyter Notebook Conversion

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python
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nbconvert

Jupyter Notebook Conversion

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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.

Python requirement

Nbconvert 6.0 provides limited support for Python 3.6 (3.6.1 or greater), and support will be dropped with nbconvert 6.1. Limited support means we will test and run CI on Python 3.6.12 or higher. Issues that are found only affecting Python 3.6 are not guaranteed to be fixed. We recommend all users of nbconvert use Python 3.7 and higher.

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

  • Issues and Bug Reports: A place to report bugs or regressions found for nbconvert
  • Community Technical Support and Discussion - Discourse: A place for installation, configuration, and troubleshooting assistannce by the Jupyter community. As a non-profit project and maintainers who are primarily volunteers, we encourage you to ask questions and share your knowledge on Discourse.

Jupyter Resources

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