FastFeedParser

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

Why FastFeedParser?

It's about 80-100x faster (run python benchmark.py to measure yourself) than popular feedparser library while keeping a familiar API. This speed comes from:

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

That figure is with the native core. Without it, parsing with lxml alone, the same benchmark comes out at about 40x.

FastFeedParser powers feed processing for Kagi Small Web, handling processing of tens of thousands of feeds at scale every day.

Features

• Fast parsing of RSS 2.0, Atom 1.0, RDF/RSS 1.0, and JSON Feed 1.0/1.1 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

Native core

The package includes a Rust extension (fastfeedparser._core, source in rust/) that extracts entries from well-formed UTF-8 RSS and Atom feeds. parse() uses it automatically and falls back to lxml for everything else; the output is the same either way.

You do not need Rust to install. Wheels for CPython 3.9+ on Linux, macOS and Windows carry the compiled extension. Anywhere else pip installs the pure-Python wheel, which parses with lxml. Installing from source builds the extension if a Rust toolchain is present and skips it if not.

Set FASTFEEDPARSER_DISABLE_CORE=1 to ignore the extension. See rust/README.md.

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)

Run Benchmark

python benchmark.py

This will run benchmark on a number of feeds with output looking like this

[https://gessfred.xyz/rss.xml] FastFeedParser: 17 entries in 0.000s (median of 3 runs)
[https://gessfred.xyz/rss.xml] Feedparser: 17 entries in 0.055s (median of 3 runs)
[https://gessfred.xyz/rss.xml] Speedup: 127.3x
[https://bernsteinbear.com/feed.xml] FastFeedParser: 11 entries in 0.001s (median of 3 runs)
[https://bernsteinbear.com/feed.xml] Feedparser: 11 entries in 0.142s (median of 3 runs)
[https://bernsteinbear.com/feed.xml] Speedup: 146.3x
[https://feeds.kottke.org/main] FastFeedParser: 60 entries in 0.001s (median of 3 runs)
[https://feeds.kottke.org/main] Feedparser: 60 entries in 0.031s (median of 3 runs)
[https://feeds.kottke.org/main] Speedup: 32.3x
[https://alexwlchan.net/atom.xml] FastFeedParser: 25 entries in 0.001s (median of 3 runs)
[https://alexwlchan.net/atom.xml] Feedparser: 25 entries in 0.129s (median of 3 runs)
[https://alexwlchan.net/atom.xml] Speedup: 185.1x

And publish a full report looking like this

Summary:
--------------------------------------------------
Total wall-clock time: 36.73s
Successfully tested 200/200 feeds

FastFeedParser:
  Total entries: 6600
  Total parsing time: 0.13s
  Average per feed: 0.001s
  Feeds/sec: 1490.9

Feedparser:
  Total entries: 6555
  Total parsing time: 11.98s
  Average per feed: 0.060s
  Feeds/sec: 16.7

Speedup: FastFeedParser is 89.3x faster

OUTLIERS: Entry Count Mismatches (2 feeds)
--------------------------------------------------
  https://dylanharris.org/feed-me.rss
    FastFeedParser: 35 entries
    Feedparser: 0 entries
    Difference: +35
  https://humanwhocodes.com/feeds/all.json
    FastFeedParser: 10 entries
    Feedparser: 0 entries
    Difference: +10

Key Features

Feed Types Support

• RSS 2.0
• Atom 1.0
• RDF/RSS 1.0
• JSON Feed 1.0/1.1

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, *, include_content=True, include_tags=True, include_media=True, include_enclosures=True): Parse feed from a URL/XML/JSON source, with optional field extraction toggles for faster parsing.

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
• python-dateutil

Optional extras:

• brotli (pip install fastfeedparser[brotli]) for Content-Encoding: br
• dateparser (pip install fastfeedparser[dateparser]) for the slowest date parsing fallback
• orjson (pip install fastfeedparser[orjson]) for faster JSON Feed decoding
• pip install fastfeedparser[full] for all three

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 feedparser project, FastFeedParser aims to provide a modern, high-performance alternative while maintaining a familiar API.