---
id: ahocorapy
version: "1.8.0"
license: MIT
license_treatment: permissive
maintenance: active
---

# ahocorapy — ahocorapy - Pure python ahocorasick implementation

License: permissive · Maintenance: active · Downloads: 77.4K/mo

## 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 above — verify before relying.

ahocorapy implements the Aho-Corasick algorithm in pure Python to search for multiple keywords in text or arbitrary sequences in linear time, supporting unicode and case-insensitive matching.

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

pip install ahocorapy
uv add ahocorapy
poetry add ahocorapy

## Installing ahocorapy

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.

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)

Tree construction is not thread-safe; concurrent calls to add() have undefined behavior. Finalize the tree before using it in multi-threaded search contexts.

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_current
- Install friction: low
- Maintenance: active
- Downloads: 77.4K/month (top 15,000 on PyPI)
- Known vulnerabilities: none known

## Tags

aho-corasick algorithm python, multi-keyword search, pattern matching multiple strings, fast substring search, keyword tree lookup, sequence matching algorithm, text search library, string-matching, algorithm-implementation, pure-python

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