Pelican internals

This section describe how Pelican works internally. As you’ll see, it’s quite simple, but a bit of documentation doesn’t hurt. :)

You can also find in the Some history about Pelican section an excerpt of a report the original author wrote with some software design information.

Overall structure

What Pelican does is take a list of files and process them into some sort of output. Usually, the input files are reStructuredText and Markdown files, and the output is a blog, but both input and output can be anything you want.

The logic is separated into different classes and concepts:

• Writers are responsible for writing files: .html files, RSS feeds, and so on. Since those operations are commonly used, the object is created once and then passed to the generators.

• Readers are used to read from various formats (HTML, Markdown and reStructuredText for now, but the system is extensible). Given a file, they return metadata (author, tags, category, etc.) and content (HTML-formatted).

• Generators generate the different outputs. For instance, Pelican comes with ArticlesGenerator and PageGenerator. Given a configuration, they can do whatever they want. Most of the time, it’s generating files from inputs.

• Pelican also uses templates, so it’s easy to write your own theme. The syntax is Jinja2 and is very easy to learn, so don’t hesitate to jump in and build your own theme.

How to implement a new reader?

Is there an awesome markup language you want to add to Pelican? Well, the only thing you have to do is to create a class with a read method that returns HTML content and some metadata.

Take a look at the Markdown reader:

from pelican.readers import BaseReader
from pelican.utils import pelican_open
from markdown import Markdown

class MarkdownReader(BaseReader):
    enabled = True

    def read(self, source_path):
        """Parse content and metadata of markdown files"""

        with pelican_open(source_path) as text:
            md_extensions = {'markdown.extensions.meta': {},
                             'markdown.extensions.codehilite': {}}
            md = Markdown(extensions=md_extensions.keys(),
                          extension_configs=md_extensions)
            content = md.convert(text)

        metadata = {}
        for name, value in md.Meta.items():
            name = name.lower()
            meta = self.process_metadata(name, value[0])
            metadata[name] = meta
        return content, metadata

Simple, isn’t it?

If your new reader requires additional Python dependencies, then you should wrap their import statements in a try...except block. Then inside the reader’s class, set the enabled class attribute to mark import success or failure. This makes it possible for users to continue using their favourite markup method without needing to install modules for formats they don’t use.

How to implement a new generator?

Generators have two important methods. You’re not forced to create both; only the existing ones will be called.

• generate_context, that is called first, for all the generators. Do whatever you have to do, and update the global context if needed. This context is shared between all generators, and will be passed to the templates. For instance, the PageGenerator generate_context method finds all the pages, transforms them into objects, and populates the context with them. Be careful not to output anything using this context at this stage, as it is likely to change by the effect of other generators.

• generate_output is then called. And guess what is it made for? Oh, generating the output. :) It’s here that you may want to look at the context and call the methods of the writer object that is passed as the first argument of this function. In the PageGenerator example, this method will look at all the pages recorded in the global context and output a file on the disk (using the writer method write_file) for each page encountered.