ahocorapy
ahocorapy - Pure python ahocorasick implementation
Decision gist · record as of 2026-08-14
Yes. ahocorapy is worth installing for multi-keyword search when you need a pure-Python, platform-independent solution with unicode support and no compiled dependencies. It is actively maintained, has no security vulnerabilities, carries a permissive MIT license, and performs competitively on typical (sparse) text. Install it if C extensions are unavailable or undesirable; if you are searching very dense text with many overlapping matches and latency is critical, a C-based alternative may be faster.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Tree construction is not thread-safe; concurrent calls to add() have undefined behavior.
- Finalize the tree before using it in multi-threaded search contexts.
- Installation is straightforward with no runtime dependencies and low friction.
License · maintenance · safety
MIT (permissive) — MIT license permits unrestricted use, modification, and distribution in both open-source and commercial projects with minimal restrictions.
last release 2026-07-21 (24 days) · last repo commit 2026-07-21 · 217 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 77,375 downloads/mo, #14,530 on PyPI
Alternatives
Verify before relying
pip install ahocorapy
from ahocorapy.keywordtree import KeywordTree
kwtree = KeywordTree(case_insensitive=True)
kwtree.add('malaga')
kwtree.add('lacrosse')
kwtree.finalize()
result = kwtree.search('My favorite islands are malaga and sylt.')
print(result)- Whether the library's performance on dense text (0.42s for 100 searches) meets your latency requirements compared to C-extension alternatives.
- Memory overhead of the suffix-shortcutting optimization relative to other pure-Python implementations in your use case.
- Whether pickling support for huge keyword trees is tested at the scale your application requires.
What it is and what it does
ahocorapy is a pure-Python implementation of the Aho-Corasick algorithm designed to search for multiple keywords in text or arbitrary sequences with linear-time complexity. It was created to address gaps in existing libraries: it supports unicode in Python 2.7 without C extensions (making it platform-independent), and it uses suffix-shortcutting during setup to accelerate lookup times. The library works with any hashable symbols—strings, tuples of integers, lists of tokens, or bytes—making it flexible for character-level, word-level, or token-level matching.
The package trades setup time for faster search performance by precomputing state transitions and match positions. On sparse text it matches C-extension performance on CPython; on dense text (many overlapping matches) it remains slower than C extensions but faster than other pure-Python alternatives. It is fully pickleable using a non-recursive serialization strategy to handle large keyword trees, and it supports case-insensitive matching for string-based searches.
Use it for
- Scan large documents for a fixed set of names, terms, or patterns without installing compiled dependencies.
- Perform word-level keyword matching by building a tree from token lists instead of character sequences.
- Search binary data or custom symbol sequences (tuples, lists) using the same algorithm without string conversion.
- Serialize and reuse large pre-built keyword trees across application restarts via pickling.
- Find all overlapping keyword matches in a single pass through text, returning both matches and their positions.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
ahocorapy is worth installing for multi-keyword search when you need a pure-Python, platform-independent solution with unicode support and no compiled dependencies. It is actively maintained, has no security vulnerabilities, carries a permissive MIT license, and performs competitively on typical (sparse) text. Install it if C extensions are unavailable or undesirable; if you are searching very dense text with many overlapping matches and latency is critical, a C-based alternative may be faster.
Install
ahocorapy on PyPI
Before you install
Installation is straightforward with no runtime dependencies and low friction. The package is actively maintained with a release 24 days old and has been stable since its first release in 2018.
Tree construction is not thread-safe; concurrent calls to add() have undefined behavior. Finalize the tree before using it in multi-threaded search contexts.
License in practice
MIT license permits unrestricted use, modification, and distribution in both open-source and commercial projects with minimal restrictions.
Quickstart
pip install ahocorapy
from ahocorapy.keywordtree import KeywordTree
kwtree = KeywordTree(case_insensitive=True)
kwtree.add('malaga')
kwtree.add('lacrosse')
kwtree.finalize()
result = kwtree.search('My favorite islands are malaga and sylt.')
print(result)Verify before relying
- Whether the library's performance on dense text (0.42s for 100 searches) meets your latency requirements compared to C-extension alternatives.
- Memory overhead of the suffix-shortcutting optimization relative to other pure-Python implementations in your use case.
- Whether pickling support for huge keyword trees is tested at the scale your application requires.
Package facts
| License | MIT permissive |
| Python support | Supports the current Python release >=2.7 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | None |
| Maintenance | Actively maintained 24 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 77,375 / month, #14,530 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 5 - Production/StableIntended Audience :: DevelopersProgramming Language :: Python :: 2Programming Language :: Python :: 2.7Programming Language :: Python :: 3Programming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14Programming Language :: Python :: 3.3Programming Language :: Python :: 3.4Programming Language :: Python :: 3.5Programming Language :: Python :: 3.6Programming Language :: Python :: 3.7Programming Language :: Python :: 3.8Programming Language :: Python :: 3.9Topic :: Software Development :: Libraries :: Python Modules |
Evidence: ahocorapy-1.8.0-py2.py3-none-any.whl
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See also ahocorasick-rs · pyahocorasick · textsearch · flashtext · suffix-trees · strsimpy · pylcs · regex · HLL · confusables