A Go library providing structured ISO-standard country, subdivision, currency, and geographic data with translations and borders.
Gountries is a Go library that provides structured access to ISO-standardized data about countries, their subdivisions, currencies, and geographic coordinates. It solves the problem of needing reliable, up-to-date international data for applications dealing with locations, borders, or multi-regional content by offering easy querying and embedded data.
Go developers building applications that require international data, such as geographic services, multi-language platforms, or systems handling country-specific regulations and currencies.
Developers choose Gountries for its comprehensive ISO-standard data, simple API, and embedded data approach, which eliminates external dependencies and ensures consistency across deployments.
Gountries provides: Countries (ISO-3166-1), Country Subdivisions(ISO-3166-2), Currencies (ISO 4217), Geo Coordinates(ISO-6709) as well as translations, country borders and other stuff exposed as struct data.
Open-Awesome is built by the community, for the community. Submit a project, suggest an awesome list, or help improve the catalog on GitHub.
Provides structured access to ISO-3166-1 countries, ISO-3166-2 subdivisions, and ISO 4217 currencies, ensuring data reliability as shown in the README examples with Sweden and Germany.
Uses go-bindata to embed YAML files, eliminating external dependencies and simplifying deployment, as mentioned in the 'Using packed data' section.
Includes country names and official names in multiple languages, demonstrated in the basic example with German translations for Sweden.
Offers intuitive functions like FindCountryByName and FindCountries for flexible data retrieval, as illustrated in the advanced examples with border queries.
The README explicitly states it's a work in progress with missing features like GeoJSON information, which limits its use for advanced geographic applications.
Updating data requires running go-bindata to regenerate embedded files, adding a manual step that complicates automation and real-time data synchronization.
Focuses on country-level data without city or detailed shape support, as evidenced by the todo list and distance calculation examples only using country coordinates.