notebook/docs/source/interactive/nbconvert.rst

Converting notebooks to other formats

Newly added in the 1.0 release of IPython is the nbconvert tool, which allows you to convert an .ipynb notebook document file into various static formats.

Currently, nbconvert is provided as a command line tool, run as a script using IPython. A direct export capability from within the IPython Notebook web app is planned.

The command-line syntax to run the nbconvert script is:

$ ipython nbconvert --to FORMAT notebook.ipynb

This will convert the IPython document file notebook.ipynb into the output format given by the FORMAT string.

The default output format is html, for which the --to argument may be omitted:

$ ipython nbconvert notebook.ipynb

IPython provides a few templates for some output formats, and these can be specified via an additional --template argument.

The currently supported export formats are:

• --to html

  • --template full (default)

    A full static HTML render of the notebook. This looks very similar to the interactive view.

  • --template basic

    Simplified HTML, useful for embedding in webpages, blogs, etc. This excludes HTML headers.

• --to latex

  Latex export. This generates NOTEBOOK_NAME.tex file, ready for export. You can automatically run latex on it to generate a PDF by adding --post PDF.

  • --template article (default)

    Latex article, derived from Sphinx's howto template.

  • --template book

    Latex book, derived from Sphinx's manual template.

  • --template basic

    Very basic latex output - mainly meant as a starting point for custom templates.

• --to slides

  This generates a Reveal.js HTML slideshow. It must be served by an HTTP server. The easiest way to do this is adding --post serve on the command-line. The serve post-processor proxies Reveal.js requests to a CDN if no local Reveal.js library is present. To make slides that don't require an internet connection, just place the Reveal.js library in the same directory where your_talk.slides.html is located, or point to another directory using the --reveal-prefix alias.

• --to markdown

  Simple markdown output. Markdown cells are unaffected, and code cells are placed in triple-backtick (```) blocks.

• --to rst

  Basic reStructuredText output. Useful as a starting point for embedding notebooks in Sphinx docs.

• --to python

  Convert a notebook to an executable Python script. This is the simplest way to get a Python script out of a notebook. If there were any magics in the notebook, this may only be executable from an IPython session.

Note

nbconvert uses pandoc to convert between various markup languages, so pandoc is a dependency of most nbconvert transforms, excluding Markdown and Python.

The output file created by nbconvert will have the same base name as the notebook and will be placed in the current working directory. Any supporting files (graphics, etc) will be placed in a new directory with the same base name as the notebook, suffixed with _files:

$ ipython nbconvert notebook.ipynb
$ ls
notebook.ipynb   notebook.html    notebook_files/

For simple single-file output, such as html, markdown, etc., the output may be sent to standard output with:

$ ipython nbconvert --to markdown notebook.ipynb --stdout

Multiple notebooks can be specified from the command line:

$ ipython nbconvert notebook*.ipynb
$ ipython nbconvert notebook1.ipynb notebook2.ipynb

or via a list in a configuration file, say mycfg.py, containing the text:

c = get_config()
c.NbConvertApp.notebooks = ["notebook1.ipynb", "notebook2.ipynb"]

and using the command:

$ ipython nbconvert --config mycfg.py

LaTeX citations

nbconvert now has support for LaTeX citations. With this capability you can:

• Manage citations using BibTeX.
• Cite those citations in Markdown cells using HTML data attributes.
• Have nbconvert generate proper LaTeX citations and run BibTeX.

For an example of how this works, please see the citations example in the nbconvert-examples repository.

Notebook JSON file format

Notebook documents are JSON files with an .ipynb extension, formatted as legibly as possible with minimal extra indentation and cell content broken across lines to make them reasonably friendly to use in version-control workflows. You should be very careful if you ever manually edit this JSON data, as it is extremely easy to corrupt its internal structure and make the file impossible to load. In general, you should consider the notebook as a file meant only to be edited by the IPython Notebook app itself, not for hand-editing.

Note

Binary data such as figures are also saved directly in the JSON file. This provides convenient single-file portability, but means that the files can be large; a diff of binary data is also not very meaningful. Since the binary blobs are encoded in a single line, they affect only one line of the diff output, but they are typically very long lines. You can use the Cell | All Output | Clear menu option to remove all output from a notebook prior to committing it to version control, if this is a concern.

The notebook server can also generate a pure Python version of your notebook, using the File | Download as menu option. The resulting .py file will contain all the code cells from your notebook verbatim, and all Markdown cells prepended with a comment marker. The separation between code and Markdown cells is indicated with special comments and there is a header indicating the format version. All output is removed when exporting to Python.

As an example, consider a simple notebook called simple.ipynb which contains one Markdown cell, with the content The simplest notebook., one code input cell with the content print "Hello, IPython!", and the corresponding output.

The contents of the notebook document simple.ipynb is the following JSON container:

{
 "metadata": {
  "name": "simple"
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": "The simplest notebook."
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": "print \"Hello, IPython\"",
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": "Hello, IPython\n"
      }
     ],
     "prompt_number": 1
    }
   ],
   "metadata": {}
  }
 ]
}

The corresponding Python script is:

# -*- coding: utf-8 -*-
# <nbformat>3.0</nbformat>

# <markdowncell>

# The simplest notebook.

# <codecell>

print "Hello, IPython"

Note that indeed the output of the code cell, which is present in the JSON container, has been removed in the .py script.