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Built for speed, efficiency, and ease of use while delivering complete parsing capabilities.\n\n### Why FastFeedParser?\n\nIt's about 10x faster (check included `benchmark.py`) than popular feedparser\nlibrary while keeping a familiar API. This speed comes from:\n\n- lxml for efficient XML parsing\n- Smart memory management  \n- Minimal dependencies\n- Focused, streamlined code\n\nPowers feed processing for [Kagi Small Web](https://github.com/kagisearch/smallweb), handling processing of thousands of feeds at scale.\n\n\n## Features\n\n- Fast parsing of RSS 2.0, Atom 1.0, and RDF/RSS 1.0 feeds\n- Robust error handling and encoding detection\n- Support for media content and enclosures\n- Automatic date parsing and standardization to UTC ISO 8601 format\n- Clean, Pythonic API similar to feedparser\n- Comprehensive handling of feed metadata\n- Support for various feed extensions (Media RSS, Dublin Core, etc.)\n\n\n## Installation\n\n```bash\npip install fastfeedparser\n```\n\n## Quick Start\n\n```python\nimport fastfeedparser\n\n# Parse from URL\nmyfeed = fastfeedparser.parse('https://example.com/feed.xml')\n\n# Parse from string\nxml_content = '''\u003c?xml version=\"1.0\"?\u003e\n\u003crss version=\"2.0\"\u003e\n    \u003cchannel\u003e\n        \u003ctitle\u003eExample Feed\u003c/title\u003e\n        ...\n    \u003c/channel\u003e\n\u003c/rss\u003e'''\nmyfeed = fastfeedparser.parse(xml_content)\n\n# Access feed global information\nprint(myfeed.feed.title)\nprint(myfeed.feed.link)\n\n# Access feed entries\nfor entry in myfeed.entries:\n    print(entry.title)\n    print(entry.link)\n    print(entry.published)\n```\n\n## Run Benchmark\n\n```bash\npython benchmark.py\n```\n\nThis will run benchmark on a number of feeds with output looking like this\n\n```\nTesting https://gessfred.xyz/rss.xml\nFastFeedParser: 17 entries in 0.004s\nFeedparser: 17 entries in 0.098s\nSpeedup: 26.3x\n\nTesting https://fanf.dreamwidth.org/data/rss\nFastFeedParser: 25 entries in 0.005s\nFeedparser: 25 entries in 0.087s\nSpeedup: 17.9x\n\nTesting https://jacobwsmith.xyz/feed.xml\nFastFeedParser: 121 entries in 0.030s\nFeedparser: 121 entries in 0.166s\nSpeedup: 5.5x\n\nTesting https://bernsteinbear.com/feed.xml\nFastFeedParser: 11 entries in 0.007s\nFeedparser: 11 entries in 0.339s\nSpeedup: 50.1x\n```\n\n\n## Key Features\n\n### Feed Types Support\n- RSS 2.0\n- Atom 1.0\n- RDF/RSS 1.0\n\n### Content Handling\n- Automatic encoding detection\n- HTML content parsing\n- Media content extraction\n- Enclosure handling\n\n### Metadata Support\n- Feed title, link, and description\n- Publication dates\n- Author information\n- Categories and tags\n- Media content and thumbnails\n\n## API Reference\n\n### Main Functions\n\n- `parse(source)`: Parse feed from a source that can be URL or a string\n\n\n### Feed Object Structure\n\nThe parser returns a `FastFeedParserDict` object with two main sections:\n\n- `feed`: Contains feed-level metadata\n- `entries`: List of feed entries\n\nEach entry contains:\n- `title`: Entry title\n- `link`: Entry URL\n- `description`: Entry description/summary\n- `published`: Publication date\n- `author`: Author information\n- `content`: Full content\n- `media_content`: Media attachments\n- `enclosures`: Attached files\n\n## Requirements\n\n- Python 3.7+\n- dateparser\n- lxml\n- python-dateutil\n\n## Contributing\n\nContributions are welcome! Please feel free to submit a Pull Request.\n\n## License\n\nThis project is licensed under the MIT License - see the LICENSE file for details.\n\n## Acknowledgments\n\nInspired by the [feedparser](https://github.com/kurtmckee/feedparser) project, FastFeedParser aims to provide a modern, high-performance alternative while maintaining a familiar API.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fkagisearch%2Ffastfeedparser","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fkagisearch%2Ffastfeedparser","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fkagisearch%2Ffastfeedparser/lists"}