Install pycountry in Python - Quick Guide

pycountry is a Python library for accessing ISO country, language, and currency data. It simplifies working with standardized codes.

What is pycountry?

pycountry provides easy access to ISO databases. It includes country, language, and currency information. The library is useful for data validation and internationalization tasks.

Installation Methods

You can install pycountry using pip. It requires Python 3.6 or higher.

Install via pip

The simplest way to install pycountry is using pip:

 
# Install pycountry using pip
pip install pycountry

Successfully installed pycountry-22.3.5

Verify Installation

Check if pycountry installed correctly:

 
# Verify installation
import pycountry
print(pycountry.__version__)

22.3.5

Basic Usage Examples

pycountry provides three main datasets: countries, languages, and currencies.

Working with Countries

Get country information using ISO codes:

 
# Get country by alpha-2 code
us = pycountry.countries.get(alpha_2='US')
print(us.name)

United States

Working with Languages

Access language data using ISO 639 codes:

 
# Get language by code
eng = pycountry.languages.get(alpha_2='en')
print(eng.name)

English

Working with Currencies

Retrieve currency information:

 
# Get currency by code
usd = pycountry.currencies.get(alpha_3='USD')
print(usd.name)

US Dollar

Advanced Features

pycountry offers more than basic lookups. You can search and filter data.

Searching Countries

Find countries by name or other attributes:

 
# Search countries by name
for country in pycountry.countries.search_fuzzy('Britain'):
    print(country.name)

United Kingdom

Historical Countries

Access historical country data:

 
# Check for historical countries
ussr = pycountry.historic_countries.get(alpha_3='SUN')
print(ussr.name if ussr else "Not found")

USSR, Union of Soviet Socialist Republics

Common Use Cases

pycountry is useful in many scenarios. Here are some practical applications.

Form Validation

Validate country or language inputs in forms:

 
# Validate country code
def is_valid_country(code):
    return pycountry.countries.get(alpha_2=code) is not None

print(is_valid_country('XX'))  # False
print(is_valid_country('US'))  # True

False
True

Data Normalization

Standardize country names in datasets:

 
# Normalize country names
def normalize_country(name):
    try:
        return pycountry.countries.search_fuzzy(name)[0].name
    except LookupError:
        return name

print(normalize_country('america'))

United States

Troubleshooting

Here are solutions to common issues with pycountry.

Missing Data

Some codes might be missing. Check the ISO standards for updates.

Performance Considerations

For large datasets, consider caching results. Repeated lookups can be slow.

Conclusion

pycountry is a powerful tool for working with ISO country, language, and currency data. It's easy to install and use in Python projects.

For similar geospatial libraries, check our guides on GeoPandas and Cartopy. For data handling, see our Python-docx guide.

The library simplifies internationalization tasks and data validation. It's a valuable addition to any Python developer's toolkit.