FastFeedParser

A high-performance feed parser for Python that handles RSS, Atom, and RDF. Built for speed, efficiency, and ease of use while delivering complete parsing capabilities.

Why FastFeedParser?

It's 10x-100x faster than traditional feedparser while keeping a familiar API. This speed comes from:

• lxml for efficient XML parsing
• Smart memory management
• Minimal dependencies
• Focused, streamlined code

Powers feed processing for Kagi Small Web, handling processing of thousands of feeds at scale.

Features

• Fast parsing of RSS 2.0, Atom 1.0, and RDF/RSS 1.0 feeds
• Robust error handling and encoding detection
• Support for media content and enclosures
• Automatic date parsing and standardization to UTC ISO 8601 format
• Clean, Pythonic API similar to feedparser
• Comprehensive handling of feed metadata
• Support for various feed extensions (Media RSS, Dublin Core, etc.)

Installation

pip install fastfeedparser

Quick Start

import fastfeedparser

# Parse from URL
myfeed = fastfeedparser.parse('https://example.com/feed.xml')

# Parse from string
xml_content = '''<?xml version="1.0"?>
<rss version="2.0">
    <channel>
        <title>Example Feed</title>
        ...
    </channel>
</rss>'''
myfeed = fastfeedparser.parse(xml_content)

# Access feed global information
print(myfeed.feed.title)
print(myfeed.feed.link)

# Access feed entries
for entry in myfeed.entries:
    print(entry.title)
    print(entry.link)
    print(entry.published)

Key Features

Feed Types Support

• RSS 2.0
• Atom 1.0
• RDF/RSS 1.0

Content Handling

• Automatic encoding detection
• HTML content parsing
• Media content extraction
• Enclosure handling

Metadata Support

• Feed title, link, and description
• Publication dates
• Author information
• Categories and tags
• Media content and thumbnails

API Reference

Main Functions

• parse(source): Parse feed from a source that can be URL or a string

Feed Object Structure

The parser returns a FastFeedParserDict object with two main sections:

• feed: Contains feed-level metadata
• entries: List of feed entries

Each entry contains:

• title: Entry title
• link: Entry URL
• description: Entry description/summary
• published: Publication date
• author: Author information
• content: Full content
• media_content: Media attachments
• enclosures: Attached files

Requirements

• Python 3.7+
• lxml
• parsedatetime
• python-dateutil

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgments

Inspired by the Universal Feed Parser (feedparser) project, FastFeedParser aims to provide a modern, high-performance alternative while maintaining a familiar API.