{"categories":[{"label":"Linguistic","url":"https://skillfed.io/packages/category/text-processing-linguistic"}],"enrichment":{"capability":"A Cython wrapper for MeCab that tokenizes and performs morphological analysis on Japanese text, returning parsed words with grammatical features.","skillfed_tags":["japanese-nlp","tokenization","morphological-analysis"],"use_cases":["Tokenizing Japanese text in NLP pipelines where word boundaries and morphological features are needed","Extracting lemmas and parts-of-speech from Japanese documents for linguistic analysis or search indexing","Building Japanese language processing applications that require accurate tokenization without spaces","Preparing Japanese text for downstream tasks like machine translation, sentiment analysis, or named-entity recognition"],"what_it_does":"This package wraps MeCab, a mature Japanese tokenizer and morphological analyzer, making it accessible from Python. It parses Japanese text (which has no spaces) into individual words and returns grammatical features like part-of-speech, lemma, and other linguistic attributes as named tuples. The package ships with prebuilt wheels for common platforms, eliminating the need to compile MeCab yourself on Linux, macOS, and Windows x64.\n\nYou typically install a dictionary alongside the package\u2014unidic-lite for quick testing or unidic for production work\u2014then create a Tagger instance and call it on Japanese text. The package supports both simple tokenization (splitting text into words) and detailed morphological analysis (extracting grammatical information). It also allows custom dictionaries and feature wrappers for non-Unidic use cases.","worth_installing":"Yes, if you need to process Japanese text. This is the standard Python wrapper for MeCab, has no known vulnerabilities, and prebuilt wheels make installation straightforward on common platforms. The aging maintenance status is not a blocker\u2014the package is stable and widely used\u2014but verify that the MeCab and dictionary versions meet your production requirements. Avoid on musl-based systems (Alpine Linux) or 32-bit Windows without manual MeCab compilation."},"id":"fugashi","links":{"html":"https://skillfed.io/packages/fugashi","md":"https://skillfed.io/packages/fugashi.md","pypi":"https://pypi.org/project/fugashi/"},"maintenance":{"status":"aging"},"meta":{"latest_release":"2025-10-24","license_spdx":"MIT AND BSD-3-Clause","license_treatment":"permissive","name":"fugashi","python_support":"supports_current","summary":"Cython MeCab wrapper for fast, pythonic Japanese tokenization."},"popularity":{"monthly_downloads":1003315,"position":4532,"tier":"top_5000"},"security":{"n_vulnerabilities":0},"version":"1.5.2"}