snowballstemmer
This package provides 36 stemmers for 34 languages generated from Snowball algorithms.
Decision gist · record as of 2026-08-14
Yes. Snowballstemmer is stable, actively maintained, has zero dependencies, and covers a broad set of languages. Install it if you need stemming for search or text indexing. If raw performance on large word volumes matters, also install PyStemmer to get automatic C-based acceleration, but the pure-Python version alone is sufficient for most applications.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Low friction installation with no runtime dependencies.
- Actively maintained with a recent release; supports current Python versions from 3.3 onward.
License · maintenance · safety
BSD-3-Clause (permissive) — BSD-3-Clause permissive license allows use in commercial and open-source projects with minimal restrictions beyond attribution.
last release 2026-06-03 (72 days) · last repo commit 2026-08-11 · 871 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 36,101,076 downloads/mo, #738 on PyPI
Alternatives
Verify before relying
import snowballstemmer
stemmer = snowballstemmer.stemmer('english')
print(stemmer.stemWords("connected connecting".split()))- Whether the pure-Python implementation meets performance needs for large-scale stemming workloads without installing PyStemmer.
What it is and what it does
Snowballstemmer is a pure-Python implementation of the Snowball stemming algorithms, covering 36 stemmers across 34 languages. It maps word variants—like "connection", "connected", and "connecting"—to a common stem ("connect") for use in search systems and text indexing. The library is designed for practical text search rather than linguistic root reduction, and aims to avoid over-stemming.
The package has no runtime dependencies and works across Python 3.3 and later. Stemmer objects are reusable but not thread-safe if shared across threads; the documentation recommends creating separate stemmer instances per thread. If performance is critical, the package can automatically fall back to PyStemmer (a C-accelerated wrapper) if installed, providing transparent speedup without code changes.
Use it for
- Build search engines that find documents with word variants (e.g., searching 'connected' returns results with 'connection').
- Preprocess text for information retrieval and indexing pipelines in multiple languages.
- Normalize user queries in multilingual applications before matching against indexed content.
- Reduce vocabulary size in NLP pipelines for languages beyond English.
- Implement text deduplication by stemming before comparison.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
Snowballstemmer is stable, actively maintained, has zero dependencies, and covers a broad set of languages. Install it if you need stemming for search or text indexing. If raw performance on large word volumes matters, also install PyStemmer to get automatic C-based acceleration, but the pure-Python version alone is sufficient for most applications.
Install
snowballstemmer on PyPI
Before you install
Low friction installation with no runtime dependencies. Actively maintained with a recent release; supports current Python versions from 3.3 onward.
License in practice
BSD-3-Clause permissive license allows use in commercial and open-source projects with minimal restrictions beyond attribution.
Quickstart
import snowballstemmer
stemmer = snowballstemmer.stemmer('english')
print(stemmer.stemWords("connected connecting".split()))Verify before relying
- Whether the pure-Python implementation meets performance needs for large-scale stemming workloads without installing PyStemmer.
Package facts
| License | BSD-3-Clause permissive |
| Python support | Supports the current Python release >=3.3 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | None |
| Maintenance | Actively maintained 72 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 36,101,076 / month, #738 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 :: DevelopersNatural Language :: ArabicNatural Language :: ArmenianNatural Language :: BasqueNatural Language :: CatalanNatural Language :: CzechNatural Language :: DanishNatural Language :: DutchNatural Language :: EnglishNatural Language :: EsperantoNatural Language :: EstonianNatural Language :: FinnishNatural Language :: FrenchNatural Language :: GermanNatural Language :: GreekNatural Language :: HindiNatural Language :: HungarianNatural Language :: IndonesianNatural Language :: IrishNatural Language :: ItalianNatural Language :: LithuanianNatural Language :: NepaliNatural Language :: NorwegianNatural Language :: PersianNatural Language :: PolishNatural Language :: PortugueseNatural Language :: RomanianNatural Language :: RussianNatural Language :: SerbianNatural Language :: SpanishNatural Language :: SwedishNatural Language :: TamilNatural Language :: TurkishNatural Language :: YiddishOperating System :: OS IndependentProgramming Language :: PythonProgramming 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 :: 3.9Programming Language :: Python :: Implementation :: CPythonProgramming Language :: Python :: Implementation :: PyPyTopic :: DatabaseTopic :: Internet :: WWW/HTTP :: Indexing/SearchTopic :: Text Processing :: IndexingTopic :: Text Processing :: Linguistic |
Evidence: snowballstemmer-3.1.1-py3-none-any.whl
Tags
Let your AI agent find packages like this
Example. Real query, live index.
You found this page by searching. An agent finds it by wishing: SkillFed indexes 14,416 PyPI packages by what they can do, searchable in plain language.
wish › “multilingual text stemming”
- snowballstemmerProvides stemming algorithms for 34 languages, reducing word variants…
- PyStemmerPyStemmer provides word stemming algorithms for multiple languages,…
- py-rust-stemmersProvides fast, parallel word stemming using Snowball algorithms via a…
Give your agent the search over MCP, or paste the wish link into any chat.
More Database packages
psycopg2-binary is a PostgreSQL database adapter for Python that implements the DB API 2.0 specification, enabling Python applications to connect to and query PostgreSQL databases with thread-safe concurrent operations.
Python client library for connecting to and executing commands against Redis key-value stores, supporting both synchronous and asynchronous operations.
Install it if your application needs to interact with Redis; the only prerequisite is a running Redis server instance.
YDB Python SDK is the official client library for connecting to and querying YDB databases from Python applications.
Install it if you need to connect Python applications to YDB databases.
Connects Python applications to Snowflake data warehouses using the DB API 2.0 specification, enabling SQL queries, data transfers, and warehouse operations.
sqlparse tokenizes SQL text into a tree of statements, clauses, and expressions, and provides functions to split scripts, format queries, and inspect parsed tokens without validating dialect or syntax.
Install it if you need to manipulate, format, or analyze SQL text programmatically.
Provides base adapter protocols and shared functionality that database adapters use to integrate with dbt-core, handling connections, dialect translation, relation caching, and core interface management.
See also py-rust-stemmers · PyStemmer · Sastrawi · pyspellchecker · blingfire · num2words · bm25s · english-words · stem · wordfreq