To help you get started, we've collected the most common ways that nbconvert is being used within popular public projects.

spatialaudio / nbsphinx / src / nbsphinx.py View on Github

/* indent single paragraph */
div.admonition {
    text-indent: 20px;
}
/* don't indent multiple paragraphs */
div.admonition > p {
    text-indent: 0;
}
/* remove excessive padding */
div.admonition.inline-title p.admonition-title {
    padding-left: .2em;
}
"""


class Exporter(nbconvert.RSTExporter):
    """Convert Jupyter notebooks to reStructuredText.

    Uses nbconvert to convert Jupyter notebooks to a reStructuredText
    string with custom reST directives for input and output cells.

    Notebooks without output cells are automatically executed before
    conversion.

    """

    def __init__(self, execute='auto', kernel_name='', execute_arguments=[],
                 allow_errors=False, timeout=30, codecell_lexer='none'):
        """Initialize the Exporter."""

        # NB: The following stateful Jinja filters are a hack until
        # template-based processing is dropped

View more ways to use nbconvert

nbconvert

Jupyter Notebook Conversion

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> <input>

where <output> is the desired output format and <input> 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

• Documentation for Jupyter nbconvert
• nbconvert examples on GitHub
• Documentation for Project Jupyter

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

• Jupyter mailing list
• Project Jupyter website

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.