A Ruby library providing a clean API for accessing and managing geographic country and region data with internationalization support.
Carmen is a Ruby library that provides a repository of geographic data for countries and their subregions, such as states or provinces. It solves the problem of managing and querying structured location data in Ruby applications, offering a clean API and support for internationalization.
Ruby developers building applications that require geographic data, such as e-commerce platforms, user profiling systems, or location-based services.
Developers choose Carmen for its clean, intuitive API, comprehensive and accurate data sourced from iso-codes, and built-in internationalization support, making it a reliable and extensible solution for geographic data in Ruby.
A repository of geographic regions for Ruby
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Provides intuitive methods like `Country.named('United States')` and `Country.alpha_2_coded('GB')`, making geographic data querying straightforward and readable.
Includes complete country and region data sourced from the iso-codes Debian package, ensuring standardized and accurate geographic information.
Offers built-in I18n with customizable backends and locale management, as shown in the localization sections for setting locales like `Carmen.i18n_backend.locale = :es`.
Supports nested subregions (e.g., states, provinces) with consistent querying, demonstrated by examples like Spain's autonomous communities and provinces.
Allows overriding or extending datasets via `Carmen.data_paths`, enabling tailored geographic information, as detailed in the 'Overriding structural data' section.
Relies on the iso-codes Debian package, which may not reflect recent geopolitical changes, and the README lacks clarity on update frequencies or synchronization methods.
Limited to Ruby applications, making it unsuitable for projects using other languages or requiring cross-platform geographic data libraries.
The README warns that `Country.coded` will be deprecated, indicating potential breaking changes and requiring developers to adapt code for future versions.
Customizing data involves manual YAML file creation and path management, which can be cumbersome for simple overrides compared to more streamlined configuration options.