{"categories":[{"label":"HTML","url":"https://skillfed.io/packages/category/text-processing-markup-html"}],"enrichment":{"capability":"Extracts plain text from HTML while filtering out styles, scripts, comments, and normalizing whitespace intelligently to match browser rendering.","skillfed_tags":["web-scraping","text-extraction","nlp-preprocessing"],"use_cases":["Extract readable text from web pages for search indexing or content aggregation","Prepare HTML content as features for text classification or NLP models","Convert web scraping results to plain text for downstream text processing","Remove boilerplate (styles, scripts) while preserving document structure via newlines","Build text-only versions of web content for accessibility or archival"],"what_it_does":"html-text extracts readable text from HTML by removing invisible content (styles, scripts, comments) and normalizing whitespace in a way that mimics how a browser renders the page. Unlike simple XPath or Beautiful Soup text extraction, it adds intelligent spacing around inline elements and can insert newlines after headers and paragraphs to preserve document structure in the output.\n\nThe package provides multiple entry points: a high-level extract_text() function for raw HTML strings, lower-level etree_to_text() for pre-parsed lxml trees, and integration with parsel.Selector for targeted extraction from specific elements. It's designed for both display purposes and machine learning feature extraction, where clean, normalized text is needed as input to classification pipelines.","worth_installing":"Yes, if you need to extract clean text from HTML with structure preservation. Low install friction, permissive license, no known vulnerabilities, and stable API make it a safe choice. Maintenance is aging but the repository remains active; suitable for production use in text extraction pipelines."},"id":"html-text","links":{"html":"https://skillfed.io/packages/html-text","md":"https://skillfed.io/packages/html-text.md","pypi":"https://pypi.org/project/html-text/"},"maintenance":{"status":"aging"},"meta":{"latest_release":"2025-10-06","license_spdx":"MIT","license_treatment":"permissive","name":"html-text","python_support":"supports_current","summary":"Extract text from HTML"},"popularity":{"monthly_downloads":1433260,"position":3908,"tier":"top_5000"},"security":{"n_vulnerabilities":0},"version":"0.7.1"}