This repository is a curated, comprehensive geographic database of countries, states, cities, and postcodes, with a strong emphasis on ISO 3166 compliance and data quality. It is primarily a data_research project, though it includes supporting application code (export pipelines, validation tools, CI/CD) that enables multi-format distribution (JSON, CSV, SQL, Parquet, etc.). The raw data lives in the `contributions/` directory as JSON files, which are the source of truth. A rich ecosystem of Python, PHP, and Node.js scripts handles ingestion from community and official sources, idempotent correction, enrichment (timezones, translations), and export to 12+ formats. The repository is actively maintained by a community of contributors and automated bots, with rigorous PR validation (schema, coordinates, duplicates, cross-references) and extensive fix documentation. It answers questions like 'What are the administrative divisions of a country?' and 'What postcodes exist for a given locality?' and is used as a reference data source for applications worldwide.
RESTCountries.NET is a .NET Standard 2.1 library providing offline access to comprehensive country data. It deserializes an embedded JSON dataset (sourced from restcountries.com) into strongly-typed C# models and exposes static query methods for searching by name, code, currency, language, and more. The library requires no network calls at runtime, making it suitable for disconnected or performance-sensitive applications. It includes a full test suite, a benchmark harness, and is distributed via NuGet with automated CI/CD. The architecture is straightforward: a static `RestCountriesService` class loads data on first access and uses LINQ to answer queries. Models cover Country, Currency, Language, Flags, Maps, Translations, and other attributes. The translation support includes 24 languages via ISO 639-3 codes. Overall, it's a well-crafted, single-purpose utility library with professional engineering practices.
This repository is a data engineering pipeline that produces a comprehensive, unified country codes dataset (CSV/JSON) by merging information from multiple authoritative sources: ISO 3166, ISO 4217, UN Statistics, UN Protocol (UNTERM), CLDR, statoids, Geonames, EDGAR, FIFA, and Wikidata. The pipeline is orchestrated via a Makefile that sequentially runs Python scripts to fetch, parse, clean, and join data. The final output contains dozens of columns covering country names in multiple languages, ISO codes, currency codes, dialing codes, and more. The repository is primarily a data transformation project rather than a software application, though it includes sophisticated web scraping and fuzzy matching. The code is modular and well-structured, but reproducibility is hampered by a manual step requiring users to manually download and rename UNSD CSV files. The included GitHub Actions workflow automates monthly updates. Overall, the project is a solid reference data curation effort with moderate complexity.