{"id":47185592,"url":"https://github.com/shner-elmo/flashtext2","last_synced_at":"2026-03-13T09:08:28.266Z","repository":{"id":86591625,"uuid":"584023541","full_name":"shner-elmo/flashtext2","owner":"shner-elmo","description":"The fastest FlashText library for 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returned=1 errno=0 peeraddr=140.82.121.5:443 state=error: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["extracting-keywords","flashtext","flashtext2","nlp","pyo3","python","rust","string","text-processing"],"created_at":"2026-03-13T09:08:27.112Z","updated_at":"2026-03-13T09:08:28.236Z","avatar_url":"https://github.com/shner-elmo.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"\u003cdiv align=\"center\"\u003e\n    \n  \u003ca href=\"https://pypi.org/project/flashtext2\"\u003e![PyPi Version](https://badge.fury.io/py/flashtext2.svg)\u003c/a\u003e\n  \u003ca href=\"https://pypi.org/project/flashtext2\"\u003e![Supported Python versions](https://img.shields.io/pypi/pyversions/flashtext2.svg?color=%2334D058)\u003c/a\u003e\n  \u003ca href=\"https://pepy.tech/project/flashtext2\"\u003e![Downloads](https://static.pepy.tech/badge/flashtext2)\u003c/a\u003e\n  \u003ca href=\"https://pepy.tech/project/flashtext2\"\u003e![Downloads](https://static.pepy.tech/badge/flashtext2/month)\u003c/a\u003e\n    \n\u003c/div\u003e\n\n```sh\npip install flashtext2\n```\n\n# flashtext2\n\n`flashtext2` is an optimized version of the `flashtext` library for fast keyword extraction and replacement. \nIts orders of magnitude faster compared to regular expressions.\n\n## Key Enhancements in flashtext2\n\n- **Rewritten for Better Performance**: Completely rewritten in Rust, making it approximately 3-10x faster than the original version.\n- **Unicode Standard Annex #29**: Instead of relying on arbitrary regex patterns like **flashtext** \n[does](https://github.com/vi3k6i5/flashtext/blob/b316c7e9e54b6b4d078462b302a83db85f884a94/flashtext/keyword.py#L13): `[A-Za-z0-9_]+`, \n**flashtext2** uses the [Unicode Standard Annex #29](https://www.unicode.org/reports/tr29/) to split strings into tokens. \nThis ensures compatibility with all languages, not just Latin-based ones.\n- **Unicode Case Folding**: Instead of converting strings to lowercase for case-insensitive matches, it uses \n[Unicode case folding](https://www.w3.org/TR/charmod-norm/#definitionCaseFolding), ensuring accurate normalization \nof characters according to the Unicode standard.\n- **Fully Type-Hinted API**: The entire API is fully type-hinted, providing better code clarity and improved development experience.\n\n\n## Usage\n\n\n\u003cdetails\u003e\n  \u003csummary\u003eClick to unfold usage\u003c/summary\u003e\n\n### Keyword Extraction\n\n```python\nfrom flashtext2 import KeywordProcessor\n\nkp = KeywordProcessor(case_sensitive=False)\n\nkp.add_keyword('Python')\nkp.add_keyword('flashtext')\nkp.add_keyword('program')\n\ntext = \"I love programming in Python and using the flashtext library.\"\n\nkeywords_found = kp.extract_keywords(text)\nprint(keywords_found)\n# Output: ['Python', 'flashtext']\n\nkeywords_found = kp.extract_keywords_with_span(text)\nprint(keywords_found)\n# Output: [('Python', 22, 28), ('flashtext', 43, 52)]\n```\n\n### Keyword Replacement\n\n```python\nfrom flashtext2 import KeywordProcessor\n\nkp = KeywordProcessor(case_sensitive=False)\n\nkp.add_keyword('Java', 'Python')\nkp.add_keyword('regex', 'flashtext')\n\ntext = \"I love programming in Java and using the regex library.\"\nnew_text = kp.replace_keywords(text)\n\nprint(new_text)\n# Output: \"I love programming in Python and using the flashtext library.\"\n```\n\n### Case Sensitivity\n\n```python\nfrom flashtext2 import KeywordProcessor\n\ntext = 'abc aBc ABC'\n\nkp = KeywordProcessor(case_sensitive=True)\nkp.add_keyword('aBc')\n\nprint(kp.extract_keywords(text))\n# Output: ['aBc']\n\nkp = KeywordProcessor(case_sensitive=False)\nkp.add_keyword('aBc')\n\nprint(kp.extract_keywords(text))\n# Output: ['aBc', 'aBc', 'aBc']\n```\n\n### Other Examples\n\nOverlapping keywords (returns the longest sequence)\n```python\nfrom flashtext2 import KeywordProcessor\n\nkp = KeywordProcessor(case_sensitive=True)\nkp.add_keyword('machine')\nkp.add_keyword('machine learning')\n\ntext = \"machine learning is a subset of artificial intelligence\"\nprint(kp.extract_keywords(text))\n# Output: ['machine learning']\n```\n\nCase folding\n```python\nfrom flashtext2 import KeywordProcessor\n\nkp = KeywordProcessor(case_sensitive=False)\nkp.add_keywords_from_iter([\"flour\", \"Maße\", \"ᾲ στο διάολο\"])\n\ntext = \"flour, MASSE, ὰι στο διάολο\"\nprint(kp.extract_keywords(text))\n# Output: ['flour', 'Maße', 'ᾲ στο διάολο']\n```\n\u003c/details\u003e\n\n\n### Performance\n\n\u003cdetails\u003e\n  \u003csummary\u003e\n  Click to unfold performance\n  \u003c/summary\u003e\n\nExtracting keywords is usually 2.5-3x faster, and replacing them is about 10x.  \nThere is still room to optimize the code and improve performance.   \nYou can find the benchmarks [here](https://github.com/shner-elmo/FlashText2.0/tree/master/benchmarks).\n\n\n![Image](benchmarks/extract-keywords.png)\n\n![Image](benchmarks/replace-keywords.png)\n\nThe words have on average 6 characters, and a sentence has 10k words, so the length is 60k.\n\u003c/details\u003e\n\n\n### TODO\n\n\u003cdetails\u003e\n  \u003csummary\u003e\n  Click to unfold TODO\n  \u003c/summary\u003e\n\n* Add multiple ways of normalizing strings: simple case folding, full case folding, and locale-aware folding\n* Remove all clones in src code\n\u003c/details\u003e\n\nCredit to [Vikash Singh](https://github.com/vi3k6i5/), the author of the original `flashtext` 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