Getting started

Internacia is reference data for countries (256 records) and international organizations / groups (“intblocks”, 1037 records; 78 blocktypes). It is part of the Dateno open-source project. Data and documentation are licensed CC-BY-4.0; code is MIT.

Fastest path (spreadsheet)

1. Decompress data/datasets/countries-lite.csv.zst (zstd -d …) or open countries-lite.parquet.
2. Filter code_status = official_iso3166_1 for the 249 current ISO countries.
3. For organizations, use intblocks-lite.csv.zst or join memberships via memberships.csv.zst (intblock_id ↔ country_code). Full flattened tables are countries.csv.zst / intblocks.csv.zst.

See also the Frictionless index: datapackage.json.

Lookups (DuckDB / Python)

# One-liner membership check
duckdb data/datasets/internacia.duckdb \
  -c "SELECT country_code, status FROM memberships WHERE intblock_id='NATO' ORDER BY 1;"

import duckdb
con = duckdb.connect("data/datasets/internacia.duckdb")
con.execute("SELECT code, name FROM countries WHERE code = 'XK'").fetchall()

Lookups (internacia-python SDK)

This is the most convenient path for LLM-generated code: it handles database download/caching, then exposes small Python methods for the common lookup/join patterns.

pip install internacia

from internacia import InternaciaClient

client = InternaciaClient()

# Country lookup (ISO 3166-1 alpha-2)
country = client.countries.get_by_code("US")
print(country["name"])

# Organizations/blocks containing a country (membership roster)
blocks_for_us = client.intblocks.get_by_member("US")
for b in blocks_for_us[:5]:
    print(b["id"], b["name"])

# Fuzzy search across countries and blocks (multilingual)
results = client.search.fuzzy("United States", limit=5)
for r in results:
    print(r["type"], r["name"])

Prefer DuckDB/Parquet over parsing YAML under data/countries/ or data/intblocks/.

Citation

Internacia Datasets (Dateno). CC-BY-4.0.
DOI: https://doi.org/10.5281/zenodo.21452328
https://github.com/datenoio/internacia-db

Version: read data/datasets/countries.manifest.json or SELECT dataset, version, schema_hash FROM _meta; in DuckDB.

Next steps

Goal	Doc
Join keys & gotchas	ai-consumers.md
Verified SQL recipes	query-examples.md
Verified Polars recipes	query-examples-polars.md
Verified R / dplyr recipes	query-examples-r.md
Observable / Plot recipes	query-examples-observable.md
Edit YAML	CONTRIBUTING.md, agents/contribute.md
Field reference	data-dictionary.md
Versioning / API posture	versioning-policy.md
Country / entity policy	country-code-policy.md, entity-classification-policy.md
Intblock inclusion	intblock-inclusion-policy.md