countries-dictionary 3.1.3

Provides a dictionary contains all members and observer states of the United Nations and information about them

Countries Dictionary

Countries Dictionary provides:

• A dictionary contains all members and observer states of the United Nations and information about them:
  • Formal name
  • Continent(s) of the country's mainland
  • Area and land area (in square kilometre)
  • Population
  • Official language(s)
  • Nominal GDP (in dollar)
  • Human Development Index
  • ISO 3166-1 codes
• Another dictionary contains all federal subjects of the Russian Federation (including occupied zones in Ukraine) and information about them:
  • Federal district
  • Economic region
  • Capital or administrative centre
  • Area (in square kilometre)
  • Population
• Another one contains all provinces and municipalities of the Socialist Republic of Vietnam and information about them:
  • Region
  • Administrative centre
  • Area (in square kilometre)
  • Population
• Another one contains all states, federal district and inhabited territories of the United Nations and information about them:
  • Capital
  • Date of ratification/establishment/acquiring
  • Area (in square kilometre)
  • Population
  • House Representatives
  • Postal code
• Some functions which you might find helpful

I created this module as an offline source of countries' information which is easy to access and use by coders.

See CHANGELOG.md for changes of releases.

Before using, it is recommended to see the code on GitHub or the below section to understand how the module works and how you can use it

Codes

Main Countries Dictionary

Structure

The Countries Dictionary has a structure like this:

COUNTRIES = {
    "Afghanistan": {
        "formal name": "Islamic Emirate of Afghanistan",
        "continents": ["Asia"],
        "area": 652864.0,
        "land area": 652230.0,
        "population": 42045000,
        "official languages": ["Dari", "Pashto"],
        "nominal GDP": 16417000000,
        "HDI": 0.496,
        "ISO 3166-1": {"alpha-2": "AF", "alpha-3": "AFG", "numeric": "004"},
    },
    # ...
}

Usage example

from countries_dictionary import COUNTRIES # Remember to import the module!

# Prints the formal name of the country
print(COUNTRIES["Vietnam"]["formal name"])

# Compares the population of two countries
print(COUNTRIES["North Korea"]["population"] > COUNTRIES["South Korea"]["population"])
print(COUNTRIES["North Korea"]["population"] == COUNTRIES["South Korea"]["population"])
print(COUNTRIES["North Korea"]["population"] < COUNTRIES["South Korea"]["population"])

# Creates the list of all countries
list_of_countries = list(COUNTRIES.keys())
print(list_of_countries)

Russia dictionary

Structure

The Russia dictionary has a structure like this:

RUSSIA = {
    "Adygea": {
        "federal district": "Southern",
        "economic region": "North Caucasus",
        "capital/administrative centre": "Maykop",
        "area": 7792.0,
        "population": 501038},
    # ...
}

Usage example

from countries_dictionary.russia import RUSSIA # Remember to import the module

# Prints the administrative centre of a krai
print(RUSSIA["Primorsky Krai"]["capital/administrative centre"])

# Sees if the two federal subjects are in the same federal district
print(RUSSIA["Tuva"]["federal district"] == RUSSIA["Altai Republic"]["federal district"])

# Creates the list of all federal subjects
list_of_federal_subjects = list(RUSSIA.keys())
print(list_of_federal_subjects)

United States dictionary

Structure

The United States dictionary has a structure like this:

UNITED_STATES = {
    "Alabama": {
        "capital": "Montgomery",
        "date of ratification/establishment/acquiring": "1819.12.14",
        "area": 135767.0,
        "population": 5024279,
        "House Representatives": 7,
        "postal code": "AL",
    }
    # ...
}

Usage example

from countries_dictionary.united_states import UNITED_STATES # Remember to import the module...

# Prints the postal code of a state
print(UNITED_STATES["Ohio"]["postal code"])

# Compares the numbers of House Representatives of two states
print(UNITED_STATES["Oklahoma"]["House Representatives"] > UNITED_STATES["Connecticut"]["House Representatives"])
print(UNITED_STATES["Oklahoma"]["House Representatives"] == UNITED_STATES["Connecticut"]["House Representatives"])
print(UNITED_STATES["Oklahoma"]["House Representatives"] < UNITED_STATES["Connecticut"]["House Representatives"])

# Creates the list of all states
list_of_states = list(UNITED_STATES.keys())
print(list_of_states)

Vietnam dictionary

Structure

The Vietnam dictionary has a structure like this:

VIETNAM = {
    "Hanoi": {
        "region": "Red River Delta",
        "administrative centre": "Hoàn Kiếm ward",
        "area": 3359.84,
        "population": 8807523},
    # ...
}

Usage example

from countries_dictionary.vietnam import VIETNAM # Of course...

# Prints the population of a province
print(VIETNAM["Ho Chi Minh City"]["population"])

# Sees if the two provinces are in the same region
print(VIETNAM["Nghệ An province"]["region"] == VIETNAM["Hà Tĩnh province"]["region"])

# Creates the list of all provinces
list_of_provinces = list(VIETNAM.keys())
print(list_of_provinces)

Quick functions

There are many functions in this submodule.

import countries_dictionary.quick_functions as qf # What have you expected?

# Converts the dictionary into JSON and creates/overwrites a JSON file which contains the converted dictionary
with open("countries_dictionary.json", "w") as f:
    f.write(qf.json_dictionary(indent=4))

# Prints a ISO 3166-2 code of a country
iso = qf.countries_iso_3166_2()
print(iso["Russia"]["ISO 3166-2"])

ISO finder

ISO finder is a module which provides a function which has the same name. ISO finder can find a country based on the provided ISO code. Note that it does not include US states' postal codes.

from countries_dictionary.iso_finder import iso_finder

print(iso_finder("VN"))
print(iso_finder("RUS"))
print(iso_finder("840"))