geotext
Geotext extracts countriy and city mentions from text
Decision gist · record as of 2026-08-14
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—consider an actively maintained alternative for production systems.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Installation is frictionless—the package has no runtime dependencies and ships as a pure Python wheel.
- However, the project is archived and abandoned; the last commit was in 2022 and no releases have occurred since 2018, so maintenance and bug fixes are not forthcoming.
License · maintenance · safety
MIT (permissive) — MIT is a permissive license, so you may use, modify, and distribute geotext freely in commercial and private projects with minimal restrictions. The underlying geographic data is licensed under Creative Commons Attribution 3.0.
last release 2018-07-30 (2937 days) · last repo commit 2022-12-26 · 140 stars · archived
0 known vulnerabilities (OSV.dev, 2026-08-14) · 98,627 downloads/mo, #13,070 on PyPI
Alternatives
Verify before relying
pip install geotext
from geotext import GeoText
places = GeoText("London is a great city")
print(places.cities) # ['London']
print(places.country_mentions) # OrderedDict([(u'GB', 1)])- Whether the geographic database (from geonames.org) is current enough for modern city and country name coverage.
- Compatibility with Python versions beyond 3.6, given the package has not been updated since 2018.
- Accuracy and recall of extraction on non-English text or transliterated place names.
What it is and 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.
The 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 It was last updated in 2018 and is no longer maintained; the repository is archived.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.
Use it for
- 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.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
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—consider an actively maintained alternative for production systems.
Install
geotext on PyPI
Before you install
Installation is frictionless—the package has no runtime dependencies and ships as a pure Python wheel. However, the project is archived and abandoned; the last commit was in 2022 and no releases have occurred since 2018, so maintenance and bug fixes are not forthcoming.
License in practice
MIT is a permissive license, so you may use, modify, and distribute geotext freely in commercial and private projects with minimal restrictions. The underlying geographic data is licensed under Creative Commons Attribution 3.0.
Quickstart
pip install geotext
from geotext import GeoText
places = GeoText("London is a great city")
print(places.cities) # ['London']
print(places.country_mentions) # OrderedDict([(u'GB', 1)])Verify before relying
- Whether the geographic database (from geonames.org) is current enough for modern city and country name coverage.
- Compatibility with Python versions beyond 3.6, given the package has not been updated since 2018.
- Accuracy and recall of extraction on non-English text or transliterated place names.
Package facts
| License | MIT permissive |
| Python support | Not specified |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | None |
| Maintenance | Abandoned 2,937 days since the last release |
| Last repo commit | repository archived |
| First released | |
| Downloads | 98,627 / month, #13,070 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Intended Audience :: DevelopersLicense :: OSI Approved :: MIT LicenseProgramming Language :: Python :: 2.7Programming Language :: Python :: 3.5Programming Language :: Python :: 3.6 |
Evidence: geotext-0.4.0-py2.py3-none-any.whl
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See also geonamescache · reverse-geocode · django-cities-light · pyap2 · countryinfo · pyap · geoip2 · goose3 · reverse_geocoder · IP2Location