{"categories":[{"label":"Software Development","url":"https://skillfed.io/packages/category/software-development/3"},{"label":"Libraries","url":"https://skillfed.io/packages/category/software-development-libraries/2"},{"label":"Scientific/Engineering","url":"https://skillfed.io/packages/category/scientific-engineering/2"},{"label":"Artificial Intelligence","url":"https://skillfed.io/packages/category/scientific-engineering-artificial-intelligence/2"},{"label":"Text Processing","url":"https://skillfed.io/packages/category/text-processing"},{"label":"Information Analysis","url":"https://skillfed.io/packages/category/scientific-engineering-information-analysis"},{"label":"Linguistic","url":"https://skillfed.io/packages/category/text-processing-linguistic"}],"enrichment":{"capability":"Detects sentence boundaries in text using rule-based heuristics, splitting paragraphs into individual sentences while handling edge cases like abbreviations and decimal points.","skillfed_tags":["nlp","sentence-segmentation","rule-based"],"use_cases":["Preprocessing raw text for NLP pipelines that require sentence-level input before tokenization or parsing.","Splitting document text into sentences for downstream tasks like named entity recognition or sentiment analysis.","Handling text with abbreviations and edge-case punctuation where naive split-on-period approaches fail.","Integrating sentence segmentation into spaCy-based NLP workflows via the PySBDFactory component.","Preparing text corpora for machine learning where sentence boundaries must be respected."],"what_it_does":"pySBD is a rule-based sentence segmenter that splits text into individual sentences. It is a Python port of the Ruby Pragmatic Segmenter library, designed to handle edge cases like abbreviations (e.g., \"E. Smith\"), decimal points (e.g., \"p. 55\"), and other punctuation ambiguities without requiring training data. The package works out-of-the-box with minimal configuration.\n\nYou instantiate a Segmenter with a language code and call its segment() method on text to get a list of sentences. It can also be integrated as a spaCy pipeline component. The package has no runtime dependencies, making installation straightforward. However, it is currently English-only and has been abandoned since early 2021, meaning no new language support or bug fixes are being released.","worth_installing":"Yes, if you need English-only sentence segmentation and can tolerate an abandoned package. The rule-based approach is stable and has no dependencies, so it is unlikely to break due to environment changes. However, do not install if you need active maintenance, multi-language support, or assurance of ongoing bug fixes. For production systems, consider whether a maintained alternative better fits your risk tolerance."},"id":"pysbd","links":{"html":"https://skillfed.io/packages/pysbd","md":"https://skillfed.io/packages/pysbd.md","pypi":"https://pypi.org/project/pysbd/"},"maintenance":{"status":"abandoned"},"meta":{"latest_release":"2021-02-11","license_spdx":null,"license_treatment":"permissive","name":"pysbd","python_support":"supports_current","summary":"pysbd (Python Sentence Boundary Disambiguation) is a rule-based sentence boundary detection that works out-of-the-box across many languages."},"popularity":{"monthly_downloads":5792822,"position":2036,"tier":"top_5000"},"security":{"n_vulnerabilities":0},"version":"0.3.4"}