Warning
This documentation is for an old version of IPython. You can find docs for newer versions here.
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. Theserve
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 indented 4 spaces.
--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.