fakeuser 1.0.0

Generate realistic user data with accurate geographic information

Fake User Generator with Realistic Locations

A Python package that generates realistic user data with accurate geographic information for testing location-based searches and applications.

Purpose

This application automatically fetches random users and enriches them with realistic location information by:

• Realistic Country Codes: Uses proper ISO 2-alpha country codes (GB, US, DE, etc.)
• Accurate Coordinates: Provides real latitude/longitude coordinates from actual cities
• Proper Timezones: Assigns correct timezone offsets for each location (356 timezones supported)
• Population Data: Includes city population information for realistic testing
• Smart Caching: Automatically downloads and caches data to avoid repeated downloads

Perfect for testing location search functionality, timezone handling, and geographic data processing in applications.

Quick Start

Installation

pip install fakeuser

Generate Users

# Generate 100 users with realistic locations
fakeuser 100

# Save to a file
fakeuser 500 --output users.json

# Generate users and view cache info
fakeuser 50 --output test.json
fakeuser --show-cache

That's it! The tool automatically:

1. Downloads random users from randomuser.me
2. Downloads cities data from GeoNames (no account required!)
3. Caches everything for future use
4. Enriches users with realistic location data

How It Works

The fakeuser command performs these steps automatically:

1. Fetches Random Users: Downloads user data from randomuser.me API
2. Downloads Cities Data: Gets the latest cities15000.txt from GeoNames (no account required!)
3. Caches Everything: Stores data locally to avoid repeated downloads
4. Enriches Locations: Replaces user cities with real cities from their country
5. Adds Geographic Data: Includes accurate coordinates, timezones, and population data

Data Sources

• Users: randomuser.me - Generates realistic fake user profiles
• Cities: GeoNames.org - Geographic database with ~32,000 cities (population > 15,000)

CLI Usage

# Basic usage
fakeuser 100                          # Generate 100 users

# Save to file  
fakeuser 500 --output users.json     # Save to specific file

# Force refetch users (cities are always cached)
fakeuser 50 --force-users            # Force refetch users

# Custom cache directory
fakeuser 1000 --cache-dir /tmp/cache # Use custom cache directory

# Cache management
fakeuser --show-cache                 # Show cache information
fakeuser --clear-cache               # Clear all cached data

Output Format

The enriched user data includes:

{
  "location": {
    "street": {"number": 123, "name": "Main St"},
    "city": "San Francisco",
    "country": "United States", 
    "countrycode": "US",
    "coordinates": {
      "latitude": "37.77493",
      "longitude": "-122.41942"
    },
    "timezone": {
      "offset": "-8:00",
      "description": "America/Los_Angeles"
    }
  },
  "_city_replacement": {
    "original_city": "Anytown",
    "new_city": "San Francisco",
    "geonames_id": "5391959",
    "population": 864816,
    "country_code": "US"
  }
}

Features

• 🚀 Zero Setup: No manual downloads or account creation required
• 📦 Smart Caching: Downloads data once, uses cached versions thereafter
• 🌍 356 Timezone Mappings: Complete coverage of all timezones in cities15000.txt
• 🏴󠁧󠁢󠁥󠁮󠁧󠁿 Country Code Support: Supports all ISO 2-alpha country codes
• 🎲 Random Selection: Cities are selected randomly, so larger cities aren't favored
• 📊 Metadata Tracking: Keeps track of what was changed for debugging
• ⚡ Fast: Cached data loads instantly on subsequent runs
• 💾 Space Efficient: Automatic cleanup and cache management

Cache Management

The tool automatically creates a .cache directory in your current folder:

.cache/
├── cities15000.txt      # ~7MB - GeoNames cities data
└── users_500.json      # User data cached by count

• Cities data: Downloaded once and cached permanently (never force-refreshed)
• User data: Cached by count (e.g., users_100.json, users_500.json)
• Smart invalidation: Different user counts create separate cache files
• Force refresh: Use --force-users to refetch user data

Requirements

• Python 3.8+
• Internet connection (for initial downloads)
• ~10MB disk space for cache
• requests library (auto-installed)

License

This project uses GeoNames data which is available under Creative Commons Attribution 4.0 License.