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Parse and manage posts with YAML (or other) frontmatter

Project description

Python Frontmatter

Jekyll-style YAML front matter offers a useful way to add arbitrary, structured metadata to text documents, regardless of type.

This is a small package to load and parse files (or just text) with YAML (or JSON, TOML or other) front matter.

Tests PyPI



pip install python-frontmatter


>>> import frontmatter

Load a post from a filename:

>>> post = frontmatter.load('tests/yaml/hello-world.txt')

Or a file (or file-like object):

>>> with open('tests/yaml/hello-world.txt') as f:
...     post = frontmatter.load(f)

Or load from text:

>>> with open('tests/yaml/hello-world.txt') as f:
...     post = frontmatter.loads(

Access content:

>>> print(post.content)
Well, hello there, world.

# this works, too
>>> print(post)
Well, hello there, world.

Use metadata (metadata gets proxied as post keys):

>>> print(post['title'])
Hello, world!

Metadata is a dictionary, with some handy proxies:

>>> sorted(post.keys())
['layout', 'title']

>>> from pprint import pprint
>>> post['excerpt'] = 'tl;dr'
>>> pprint(post.metadata)
{'excerpt': 'tl;dr', 'layout': 'post', 'title': 'Hello, world!'}

If you don't need the whole post object, just parse:

>>> with open('tests/yaml/hello-world.txt') as f:
...     metadata, content = frontmatter.parse(
>>> print(metadata['title'])
Hello, world!

Write back to plain text, too:

>>> print(frontmatter.dumps(post)) # doctest: +NORMALIZE_WHITESPACE
excerpt: tl;dr
layout: post
title: Hello, world!
Well, hello there, world.

Or write to a file (or file-like object):

>>> from io import BytesIO
>>> f = BytesIO()
>>> frontmatter.dump(post, f)
>>> print(f.getvalue().decode('utf-8')) # doctest: +NORMALIZE_WHITESPACE
excerpt: tl;dr
layout: post
title: Hello, world!
Well, hello there, world.

For more examples, see files in the tests/ directory. Each sample file has a corresponding .result.json file showing the expected parsed output. See also the examples/ directory, which covers more ways to customize input and output.

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