This is a pre-production deployment of Warehouse, however changes made here WILL affect the production instance of PyPI.
Latest Version Dependencies status unknown Test status unknown Test coverage unknown
Project Description

Type journal article DOIs, and have them automagically converted into a beautiful bibliography.

A Markdown extension that looks through your text for things like doi:10.1234/j.banana.5678, looks up the metadata on the crossref API and outputs text according to your requirements

Add 'markdown_doi' to your Markdown call and watch the magic unfold:

>>> from markdown import Markdown

>>> markdown = Markdown(extensions=['markdown_doi']
>>> markdown.convert('doi:10.1016/j.applanim.2010.02.004')


<p><span class="doi"><a href="">Are cows more likely to lie down the longer they stand?</a> <span class="doi-year">(2010)</span></span></p>

You can enable the caching if for example you are using Pelican and constantly regenerating the same files

>>> markdown = Markdown(extensions=['markdown_doi(cache_file=.doi_cache)']

The templating function takes the metadata Dict from the message key of the JSON API response and returns a markdown.util.etree.ElementTree. See the default template_title_link_year function.

from markdown_doi import makeExtension as makeDoiExtension

def templater(metadata, doi_pattern):
    el = markdown.util.etree.Element("span")
    el.text = '%(given)s %(family)s' % metadata['author'][0]
    return el

ext = makeDoiExtension(templater=templater)
md = markdown.Markdown(extensions=[ext])
html = md.convert('hello 10.1016/j.applanim.2010.02.004')
assert html == 'hello <p><span>Bert J. Tolkamp</span></p>'


Option Type Default Description
templater (Dict, LinkPattern) -> etree.ElementTree None Function which renders the metadata as an element tree
cache_file str File name that can store a cache of the DOIs looked up
cache dict None Instead, you can pass a map from DOI to metadata dict as the cache rather than a file name


From Github:

git clone
pip install -e ./markdown_doi

From Pypi:

pip install markdown_doi
Release History

Release History


This version

History Node

TODO: Figure out how to actually get changelog content.

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