pyworldatlas 0.8.1

Offline country profiles, physical geography, cities, distances, and learning tools

PyWorldAtlas: offline world geography for Python

Offline country profiles, physical geography, cities, distances, and learning tools for Python.

248 profiles · 6,265 populated places · 319 reviewed land borders · 0 runtime dependencies

Documentation · Playground · Learning lab · Five-minute tour · Recipes · API reference

No installation needed: open the browser playground and run the guided Python examples.

PyWorldAtlas is an offline world-geography Python package built around one bundled, source-aware database. It turns country profiles, physical geography, cities, distances, borders, and learning tools into ordinary Python objects for developers, classrooms, and curious learners. No API key or runtime download is required.

Install

python -m pip install --upgrade pyworldatlas

PyWorldAtlas supports Python 3.10 through 3.14. The installed package works offline and has no third-party runtime dependencies.

Meet a country

from pyworldatlas import Atlas

with Atlas() as atlas:
    brazil = atlas.country("Brazil")
    print(brazil.summary())

🇧🇷 Brazil · Brasil
Formal name: Federative Republic of Brazil
Capital: Brasília
Location: Americas · South America
Population snapshot: 209,469,333
Currency: Brazilian Real (BRL, R$)
Languages: English (en), Spanish (es), French (fr), Portuguese (pt-BR)
Anthem title: Hino Nacional Brasileiro · Brazilian National Anthem
Motto: Ordem e Progresso · Order and Progress
Highest point: Pico da Neblina (2,994 m)
Dominant climate class: Aw · Tropical, savannah
Source-listed rivers: Amazon, Río de la Plata/Paraná, Tocantins
Source-listed lakes: Lagoa dos Patos, Lagoa Mirim

Atlas opens a bundled, read-only SQLite database. Results are immutable, typed models rather than loosely structured dictionaries, and loaded records remain usable after the atlas is closed.

What you can explore

Area	Included capabilities
Country profiles	Codes, names, capitals, population, currencies, languages, timezones, postal formats, anthem titles, reviewed mottos, and demonyms
Names and writing systems	English identities, selected local-language names, scripts, reviewed official forms, and source-provided romanization
Physical geography	Land and water area, coastline, elevation extremes, rivers, lakes, and climate summaries
Places and measurement	6,265 cities and capitals with search, nearby-place discovery, readable coordinates, distance, compass direction, bearing, and midpoint calculations
Land connections	Reviewed neighbors, shared neighbors, shortest border paths, crossings, and connected components
Learning tools	Readable profiles, stable samples, flashcards, deterministic multiple-choice questions, rankings, discovery cards, and Unicode-preserving JSON

Explore with small, readable programs

Look up countries by familiar name or standard code:

with Atlas() as atlas:
    assert atlas.country("Japan") == atlas.country("JP")
    assert atlas.country("JPN") == atlas.country("392")
    print(atlas.country("Japan").name_in("ja"))

Measure and connect places:

with Atlas() as atlas:
    tokyo = atlas.city("Tokyo", country="JP")
    paris = atlas.city("Paris", country="FR")

    print(tokyo.coordinates.format())
    print(tokyo.coordinates.dms())
    print(f"{atlas.distance_between(tokyo, paris):,.0f} km")
    print(tokyo.coordinates.compass_direction_to(paris.coordinates))

    nearby = atlas.nearest_cities(tokyo, within_country="JP", limit=3)
    print([result.city.name for result in nearby])

    route = atlas.border_path("Portugal", "China")
    print(" → ".join(route.names))

Build a repeatable lesson:

with Atlas() as atlas:
    questions = atlas.quiz(topic="local_names", count=5, seed=42)

    for question in questions:
        print(question.prompt)
        for number, choice in enumerate(question.choices, 1):
            print(f"  {number}. {choice}")
        print("Answer:", question.answer_number)

Distances are great-circle surface measurements, not road or flight routes. Border paths use the reviewed land-border graph and do not infer maritime or boundary geometry.

Built for learning

• Offline: lessons and programs do not depend on an external service.
• Repeatable: seeded samples, flashcards, and quizzes produce stable results.
• Source-aware: provenance and coverage limits are documented.
• Beginner-friendly: common tasks use small Python objects and methods.
• Honest about missing data: unavailable values remain None or empty tuples.

The project provides factual geography and transparent calculations, not political commentary or opinion. Read the educational and neutrality policy for the formal publication standard.

Coverage at a glance

Library 0.8.1 includes dataset 2026.07.22.7 and schema 7.

Dataset area	Coverage
Countries and areas	248
Primary capitals	241 / 248
Populated places	6,265
Selected local-language identities	248 / 248
Anthem titles	234 / 248
Reviewed land-border relationships	319
Highest and lowest points	240 / 248
Köppen-Geiger climate profiles	241 / 248

See the generated project status for complete coverage and data quality for interpretation limits.

Data and trust

Field families use defined source roles rather than one unreviewed compilation. The builder retains source snapshots, checksums, review decisions, and exact coverage gates. Sources include United Nations M49, GeoNames, Unicode CLDR, UNGEGN, Natural Earth, the CIA World Factbook, Wikidata, IANA registries, and the Beck et al. Köppen-Geiger dataset.

• Data sources and freshness
• Data quality and limitations
• Educational purpose and editorial policy
• Third-party notices

Documentation and community

• Run Python in the browser
• Try the classroom-friendly learning lab
• Browse complete recipes
• Read the country-profile guide
• Explore physical geography
• Review the API
• See the roadmap

Questions, factual corrections, documentation improvements, and focused code contributions are welcome. Start with CONTRIBUTING.md, follow the code of conduct, and report security concerns through SECURITY.md.

Development

python maintain.py bootstrap
python maintain.py check

maintain.py check runs tests, builds both distributions, installs the wheel in isolation, executes examples, builds strict documentation and doctests, and audits the release contents.

License

PyWorldAtlas code is available under the MIT License. Bundled data retains its original terms and attribution; see THIRD_PARTY_NOTICES.md.