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Offline country profiles, coordinate tools, and geography learning utilities

Project description

PyWorldAtlas

A compact, source-aware world atlas for Python that works completely offline.

Source 0.2.1 PyPI Python 3.10–3.14 Runtime dependencies: 0 Offline: yes License: MIT

PyWorldAtlas makes real geographic data feel like ordinary Python. Look up a country by name or code, inspect immutable country and capital objects, explore major cities, calculate geographic relationships, and build reproducible learning material—without an API key, runtime download, database server, or third-party dependency.

from pyworldatlas import Atlas

with Atlas() as atlas:
    japan = atlas.country("Japan")

    print(japan.capital.name)                  # Tokyo
    print(japan.capital.coordinates.as_tuple())
    print(atlas["DO"].name)                    # Dominican Republic
    print("France" in atlas)                   # True

Dataset coverage

The bundled dataset contains every country and area in the captured UN M49 scope, cross-checked against GeoNames country metadata. Version 0.2.1 adds core profile metadata and coordinate calculations to the identity, region, capital, and populated-place records established for 0.1.0.

Current dataset Coverage
Countries and areas 248
Primary capitals 241 / 248
Capital coordinates 241 / 241
Populated-place records 6,265, including retained capitals
Runtime dependencies 0
Bundled databases 1 SQLite file

The 0.2.1 checkout adds richer country profiles, dependency-free coordinate calculations, flag emoji, discovery cards, reproducible sampling, and structured flashcards. Borders, boundary geometry, historical statistics, national leaders, interactive learning applications, and exports remain later work.

Installation

Install the latest published release:

python -m pip install --upgrade pyworldatlas

Install the current source checkout and its separate data builder when contributing:

python -m pip install -e . -e pipeline

You can also test the exact local wheel after running the release build:

python -m pip install --no-index --no-deps dist/pyworldatlas-0.2.1-py3-none-any.whl

The package runtime supports Python 3.10 through 3.14 during the 0.x release series. Python versions are only claimed as release-supported after CI passes.

What works in this checkout

Capability Example
Exact lookup atlas.country("Japan")
Standard identifiers atlas.country("JP"), atlas.country("JPN"), atlas.country("392")
Familiar aliases atlas.country("USA"), atlas.country("Holy See")
Collection behavior atlas["DO"], "France" in atlas, len(atlas)
Ranked search atlas.search_countries("united")
Geographic filtering atlas.countries(continent="Americas")
Capital records country.capital, .coordinates, .timezone_id
Major cities atlas.major_cities("Japan", limit=5)
Rich profile country.population, .currency, .languages, .calling_codes
Flags and calculated facts country.flag_emoji, .population_density
Discovery cards country.discovery_card()
Stable country samples atlas.sample_countries(count=5, seed=42)
Structured flashcards atlas.flashcards(topic="capitals", count=10, seed=42)
City coordinates atlas.coordinates("Tokyo", country="JP")
Distance atlas.distance_between("Tokyo", "Paris", first_country="JP", second_country="FR")
Bearing and midpoint coordinate.bearing_to(other), .midpoint_to(other)
Source inspection country.sources
Official local names country.local_names, country.name_in("pt")
Serialization country.to_dict(), country.to_json()
Version inspection atlas.dataset_info()

Typed country profiles

Public results are frozen typed dataclasses rather than loosely structured dictionaries:

from pyworldatlas import Atlas

with Atlas() as atlas:
    country = atlas.country("Dominican Republic")

    print(country.name)
    print(country.official_name)
    print(country.flag)
    print(country.flag_emoji)
    print(country.codes.alpha2)
    print(country.codes.alpha3)
    print(country.codes.numeric)
    print(country.continent)
    print(country.region)
    print(country.subregion)
    print(country.area_km2)
    print(country.population)
    print(country.population_density)
    print(country.currency)
    print(country.languages)
    print(country.calling_codes)
    print(country.top_level_domain)
    print(country.observed_timezones)

    if country.capital is not None:
        print(country.capital.name)
        print(country.capital.coordinates.as_tuple())
        print(country.capital.population)
        print(country.capital.timezone_id)

Country discovery and education

from pyworldatlas import Atlas

with Atlas() as atlas:
    japan = atlas.country("Japan")
    card = japan.discovery_card()

    print(card.flag_emoji, card.capital, card.population_density)

    for country in atlas.sample_countries(count=5, continent="Africa", seed=42):
        print(country.flag_emoji, country.name)

    for flashcard in atlas.flashcards(topic="capitals", count=3, seed=42):
        print(flashcard.prompt)
        print(flashcard.answer)

Sampling uses a versioned SHA-256 ranking over stable M49 identifiers, so the same dataset, filters, and seed produce the same ordered lesson across supported Python versions. Flashcards are immutable structured values rather than an interactive game. Supported topics cover capitals, flags, country codes, currencies, calling codes, domains, language codes, regions, local names, population, area, and calculated density.

Latitude, longitude, and distance

from pyworldatlas import Atlas, Coordinate

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

    print(tokyo.coordinates.latitude, tokyo.coordinates.longitude)
    print(atlas.distance_between(tokyo, paris))             # kilometres
    print(atlas.distance_between(tokyo, paris, unit="mi"))  # miles
    print(tokyo.coordinates.bearing_to(paris.coordinates))
    print(tokyo.coordinates.midpoint_to(paris.coordinates))

london = Coordinate(51.5074, -0.1278)
paris_center = Coordinate(48.8566, 2.3522)
print(london.distance_to(paris_center))

Distances use the haversine formula and WGS84 mean Earth radius. They are surface great-circle distances, not road or flight-routing distances.

Search and filter

with Atlas() as atlas:
    for match in atlas.search_countries("united"):
        print(match.country.name, match.matched_name, match.score)

    for country in atlas.countries(continent="Europe"):
        capital = country.capital.name if country.capital else "not available"
        print(country.name, capital)

Search is case- and accent-insensitive. Exact country lookup accepts common names, reviewed aliases, alpha-2, alpha-3, and M49 numeric codes.

Test every current record

The repository includes playground.py, which checks every current country, capital, and city record before demonstrating the public API.

Run from the repository root:

python playground.py

Focused modes:

python playground.py --audit-only
python playground.py --country Japan
python playground.py --json "Dominican Republic"
python playground.py --country "United States" --all-cities

The playground runs directly from a repository checkout even before an editable installation. Normal applications should install the package.

Small by design

The installed wheel contains only:

  • Python source files.
  • One generated, read-only SQLite database.
  • Standard package metadata.

At runtime PyWorldAtlas does not:

  • Contact the internet.
  • Require an API key.
  • Download or decompress data after installation.
  • Write into site-packages.
  • Load the complete database during Atlas() initialization.
  • Depend on pandas, NumPy, an ORM, a GIS engine, or SQLite extensions.

Data you can trace

The 0.2.1 checkout uses:

  • United Nations M49 for canonical identities, standard codes, regions, and subregions.
  • GeoNames for capitals, populated places, WGS84 coordinates, population snapshots, currencies, language and calling codes, country-code domains, timezone identifiers, and GeoNames IDs.

The reviewed local-name records use the UNGEGN List of Country Names (E/CONF.105/13/CRP.13) for national official short and formal names. Current coverage is five records across Brazil and Switzerland. The captured source artifact and reviewed rows include checksums and exact entry/page locators.

Raw snapshots are preserved with SHA-256 manifests. The separate builder emits inspectable normalized JSON Lines before generating SQLite. Missing values stay missing; unsourced assumptions are never substituted for country facts.

Flag emoji are derived from alpha-2 codes, population density is a transparent ratio of sourced values, and discovery/learning tools only rearrange existing profile data. They introduce no additional country claims or third-party data.

Seven areas have no usable primary-capital record in the current snapshot. Their country.capital value is None. GeoNames-only country rows that do not have a matching identity in the captured UN M49 scope are excluded rather than inferred.

See DATA_SOURCES.md, DATA_QUALITY.md, and THIRD_PARTY_NOTICES.md.

Three different versions

with Atlas() as atlas:
    print(atlas.dataset_info())
  • Library version describes Python behavior and the public API.
  • Schema version describes compatibility with the bundled SQLite structure.
  • Dataset version identifies the captured source snapshot.

For this development checkout they are 0.2.1, 2, and 2026.07.20.1.

Documentation and roadmap

Version 0.2.1 is the country-profile, coordinate, and discovery release. After it is published, 0.3.0 will add reviewed border relationships, neighbors, shared neighbors, and border paths. Later releases extend boundary geometry, historical statistics, institutions, culture, and exports.

License and attribution

PyWorldAtlas code is available under the MIT License. GeoNames data is provided under CC BY 4.0. Other source terms and required notices are recorded in THIRD_PARTY_NOTICES.md.

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