{"categories":[{"label":"Information Analysis","url":"https://skillfed.io/packages/category/scientific-engineering-information-analysis/2"},{"label":"Linguistic","url":"https://skillfed.io/packages/category/text-processing-linguistic/2"},{"label":"Internationalization","url":"https://skillfed.io/packages/category/software-development-internationalization"},{"label":"Localization","url":"https://skillfed.io/packages/category/software-development-localization"}],"enrichment":{"capability":"Simplemma converts inflected word forms to their dictionary base forms (lemmas) across 54 languages using pure Python with no external dependencies or model downloads.","skillfed_tags":["multilingual","offline-first","zero-dependencies"],"use_cases":["Build a search engine or text indexing system where lemmatization reduces vocabulary size without downloading language models.","Preprocess multilingual documents for topic modeling or information retrieval in resource-constrained environments.","Teach NLP fundamentals in a classroom setting where a simple, dependency-free tool is easier to install and explain than neural pipelines.","Establish a baseline lemmatization result to compare against more complex models in morphological analysis research.","Detect the language of short text snippets by scoring them against a set of candidate languages.","Tokenize and split sentences in a rule-based pipeline where speed and determinism matter more than state-of-the-art accuracy."],"what_it_does":"Simplemma is a pure-Python lemmatizer that reduces inflected word forms to their base dictionary forms across 54 languages. It works offline with no model downloads, ships in a 19 MB package, and includes built-in tokenization, sentence splitting, and language detection utilities. The core trade-off is deliberate: it sacrifices the accuracy of neural pipelines (typically a few percentage points behind trained models) in exchange for speed (millions of tokens per second), simplicity, and a small footprint that suits low-resource settings, teaching, and baseline NLP work.\n\nUnlike stemming, lemmatization always returns valid linguistic forms. Simplemma handles this without morphosyntactic information by performing dictionary lookups on raw token sequences. It supports language chaining to improve coverage when a word is unknown in one language but recognized in another, and offers a tunable RAM footprint via a `low_memory` flag or optional marisa-trie backend. The package is actively maintained, has no runtime dependencies, and works on current Python versions (3.10+).","worth_installing":"Yes. Simplemma is worth installing if you need fast, offline lemmatization across many languages without external dependencies or model downloads. Its zero-dependency design, active maintenance, MIT license, and absence of known vulnerabilities make it a low-risk choice. Install it for baseline NLP work, teaching, or low-resource settings; do not install it if you need the highest accuracy and can afford the overhead of neural pipelines."},"id":"simplemma","links":{"html":"https://skillfed.io/packages/simplemma","md":"https://skillfed.io/packages/simplemma.md","pypi":"https://pypi.org/project/simplemma/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-08-12","license_spdx":null,"license_treatment":"permissive","name":"simplemma","python_support":"supports_current","summary":"Fast and zero-dependency lemmatization, tokenization and sentence splitting for 54 languages."},"popularity":{"monthly_downloads":220470,"position":9299,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"2.0.0"}