{"categories":[{"label":"Text Processing","url":"https://skillfed.io/packages/category/text-processing/3"}],"enrichment":{"capability":"Geotext extracts mentions of countries and cities from unstructured text, returning them as structured data with optional filtering by country code.","skillfed_tags":["nlp","geolocation","lightweight"],"use_cases":["Extract city and country names from user-generated content, reviews, or social media posts for geographic analysis.","Filter travel or news articles by location mentions to organize content by region or country.","Preprocess text data for geospatial machine learning pipelines that require structured location labels.","Identify geographic scope in customer feedback or support tickets without external API calls.","Build lightweight location-aware search or tagging systems where offline extraction is preferred."],"what_it_does":"Geotext is a lightweight Python library that identifies and extracts country and city names from plain text. It parses input strings and returns structured results: a list of detected cities, a list of detected countries, and a frequency count of country mentions by ISO code. You can optionally filter results to cities within a specific country by passing a country code.\n\nThe package relies on a built-in geographic database derived from geonames.org data and has no external runtime dependencies, making it fast and simple to integrate. It was last updated in 2018 and is no longer maintained; the repository is archived. While the core extraction logic remains functional, the underlying geographic data may not reflect recent city or country name changes, and compatibility with modern Python versions is untested.","worth_installing":"Yes, if you need simple, offline geographic entity extraction and can tolerate an unmaintained codebase. The lack of dependencies and low install friction make it attractive for lightweight projects. However, do not use it if you require current geographic data, active bug fixes, or support for modern Python versions\u2014consider an actively maintained alternative for production systems."},"id":"geotext","links":{"html":"https://skillfed.io/packages/geotext","md":"https://skillfed.io/packages/geotext.md","pypi":"https://pypi.org/project/geotext/"},"maintenance":{"status":"abandoned"},"meta":{"latest_release":"2018-07-30","license_spdx":null,"license_treatment":"permissive","name":"geotext","python_support":"unspecified","summary":"Geotext extracts countriy and city mentions from text"},"popularity":{"monthly_downloads":98627,"position":13070,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"0.4.0"}