randum 1.0.9

Randum - Random Universal Data Generator for Python

Randum

Randum - Random Universal Data Generator for Python. A powerful package that generates fake data for testing, development, and data anonymization.

Overview

Randum is a comprehensive fake data generator based on the popular Faker library. It provides an easy-to-use interface for generating realistic fake data across multiple categories including personal information, addresses, companies, internet data, dates, and much more.

Installation

pip install randum

Or install from source:

git clone https://github.com/kactlabs/randum
cd randum
pip install -e .

Quick Start

from randum import Randum

# Initialize Randum
rand = Randum()

# Generate fake data
print(rand.name())          # 'John Doe'
print(rand.email())         # '[e-mail]'
print(rand.address())       # '123 Main St, Springfield, IL 62701'
print(rand.phone_number())  # '[phone]'
print(rand.company())       # 'Acme Corporation'
print(rand.animal())        # 'Lion'
print(rand.dog_breed())     # 'Labrador Retriever'
print(rand.music_genre())   # 'Rock'
print(rand.song_title())    # 'Dancing in the Moonlight'
print(rand.sport())         # 'Basketball'
print(rand.team_name())     # 'Chicago Bulls'
print(rand.food())          # 'Pizza'
print(rand.dish())          # 'Grilled Salmon with Asparagus'
print(rand.book_title())    # 'The Shadow of Time'
print(rand.author_name())   # 'Jane Smith'
print(rand.vehicle_make_model()) # 'Toyota Camry'
print(rand.license_plate()) # 'ABC-1234'
print(rand.weather())       # 'Sunny'
print(rand.temperature())   # '72°F'
print(rand.medical_profession()) # 'Doctor'
print(rand.disease())       # 'Diabetes'
print(rand.blood_type())    # 'O+'
print(rand.degree())        # 'Bachelor of Science in Computer Science'
print(rand.university_name()) # 'Springfield State University'
print(rand.gpa())           # '3.75'

Features

Personal Information

• Names (first, last, full)
• Email addresses
• Phone numbers
• Social Security Numbers
• Job titles

Address Information

• Full addresses
• Cities, states, countries
• Zip codes
• Coordinates (latitude/longitude)

Company Information

• Company names
• Business emails
• Catch phrases
• Business jargon

Internet & Technology

• Usernames and passwords
• IP addresses (IPv4, IPv6)
• MAC addresses
• URLs and domains
• User agents

Dates & Times

• Random dates
• Past and future dates
• Times and timestamps
• Date ranges

Financial

• Credit card numbers
• Credit card providers
• Currency codes
• IBAN numbers

Text & Lorem Ipsum

• Words, sentences, paragraphs
• Text of various lengths

Colors

• Color names
• Hex colors
• RGB colors

Animals (New!)

• Random animals from all categories
• Mammals, birds, reptiles, amphibians, fish
• Invertebrates
• Domestic and wild animals
• Endangered species
• Dog and cat breeds

Music (New!)

• Music genres and instruments
• Song titles and album names
• Artist and band names
• Record labels and formats
• Streaming platforms
• Concert venues and awards
• Musical terms and keys
• BPM, duration, and track info
• Playlist names

Sports (New!)

• All major sports (team and individual)
• Olympic sports
• Team names and athlete names
• Sport positions and equipment
• Venues and famous stadiums
• Leagues and competitions
• Awards and honors
• Scores, rankings, and records
• Jersey numbers and seasons

Food (New!)

• Fruits, vegetables, meats, and seafood
• Dairy products and grains
• Spices, herbs, and ingredients
• Desserts and beverages
• Cuisines and cooking methods
• Dishes and recipes
• Restaurant types and meal types
• Dietary preferences and taste profiles
• Food prices and nutrition info

Books & Literature (New!)

• Book titles and author names
• Literary genres and publishers
• Book series and chapter titles
• Book formats and editions
• ISBN numbers and publication years
• Literary awards and reading levels
• Book ratings and reviews
• Bookstore types and book clubs
• Literary terms and languages

Vehicles & Automotive (New!)

• Vehicle types and manufacturers
• Car makes and models
• Vehicle years and colors
• Fuel types and transmissions
• Engine sizes and drive types
• Vehicle features and specifications
• License plates and VIN numbers
• Mileage and pricing
• Dealerships and insurance

Weather & Climate (New!)

• Weather conditions and descriptions
• Temperature (Fahrenheit and Celsius)
• Wind speed and direction
• Humidity and precipitation
• Cloud cover and visibility
• Atmospheric pressure
• UV index and air quality
• Weather alerts and seasons
• Moon phases and sunrise/sunset times

Medical & Healthcare (New!)

• Medical specialties and professions
• Diseases and symptoms
• Medical tests and procedures
• Medications and dosages
• Medical equipment
• Hospital departments
• Blood types and vital signs
• Blood pressure and heart rate
• Body temperature and oxygen saturation
• Medical record numbers and patient IDs
• Prescription numbers and ICD-10 codes
• BMI and allergies
• Insurance providers

Education (New!)

• Degree types and abbreviations
• Fields of study and majors
• University and school names
• Course names and codes
• Academic subjects and titles
• Student classifications and IDs
• GPA and letter grades
• Academic terms and years
• Campus facilities and departments
• Extracurricular activities
• Academic honors and awards
• Scholarships and tuition fees
• Credit hours and class sizes
• Graduation years and attendance rates

Advanced Usage

Using Locales

Randum supports multiple locales for generating localized data:

from randum import Randum

# French locale
rand_fr = Randum('fr_FR')
print(rand_fr.name())      # 'Jean Dupont'
print(rand_fr.address())   # French address

# Spanish locale
rand_es = Randum('es_ES')
print(rand_es.name())      # 'María García'

# Multiple locales
rand_multi = Randum(['en_US', 'fr_FR', 'es_ES'])
print(rand_multi.name())   # Randomly picks from any locale

Seeding for Reproducibility

from randum import Randum

# Set seed for reproducible results
Randum.seed(12345)
rand = Randum()
print(rand.name())  # Always generates the same name

# Reset seed
Randum.seed(12345)
rand2 = Randum()
print(rand2.name())  # Same as above

Unique Values

from randum import Randum

rand = Randum()

# Generate unique emails
for _ in range(5):
    print(rand.unique.email())

# Clear unique cache
rand.unique.clear()

Optional Values

from randum import Randum

rand = Randum()

# 50% chance of returning None
print(rand.optional.name())

# 80% chance of returning a value
print(rand.optional.email(prob=0.8))

Examples

See example.py for comprehensive usage examples:

python example.py

API Reference

Common Methods

• name() - Full name
• first_name() - First name
• last_name() - Last name
• email() - Email address
• phone_number() - Phone number
• address() - Full address
• city() - City name
• state() - State name
• country() - Country name
• zipcode() - Zip code
• company() - Company name
• job() - Job title
• text() - Random text
• date() - Random date
• time() - Random time
• url() - Random URL
• ipv4() - IPv4 address
• credit_card_number() - Credit card number
• random_int(min, max) - Random integer
• pybool() - Random boolean
• color_name() - Color name
• hex_color() - Hex color code
• animal() - Random animal
• mammal() - Random mammal
• bird() - Random bird
• fish() - Random fish
• dog_breed() - Random dog breed
• cat_breed() - Random cat breed
• music_genre() - Random music genre
• instrument() - Random instrument
• song_title() - Random song title
• artist_name() - Random artist name
• album_name() - Random album name
• sport() - Random sport
• team_sport() - Random team sport
• individual_sport() - Random individual sport
• olympic_sport() - Random Olympic sport
• team_name() - Random team name
• athlete_name() - Random athlete name
• sport_position() - Random sport position
• sport_equipment() - Random sport equipment
• famous_sport_venue() - Famous sport venue
• sport_league() - Random sport league
• sport_award() - Random sport award
• jersey_number() - Random jersey number
• season_year() - Season year format
• score() - Random score
• record() - Win-loss record
• ranking() - Ranking position
• food() - Random food item
• fruit() - Random fruit
• vegetable() - Random vegetable
• meat() - Random meat
• seafood_item() - Random seafood
• dairy_product() - Random dairy product
• grain() - Random grain
• spice() - Random spice or herb
• dessert() - Random dessert
• beverage() - Random beverage
• cuisine() - Random cuisine type
• cooking_method() - Random cooking method
• meal_type() - Random meal type
• dish() - Random dish name
• ingredient() - Random ingredient
• restaurant_type() - Random restaurant type
• dietary_preference() - Random dietary preference
• recipe_name() - Random recipe name
• food_price() - Random food price
• calories() - Random calorie count
• serving_size() - Random serving size
• book_title() - Random book title
• author_name() - Random author name
• literary_genre() - Random literary genre
• publisher() - Random publisher
• book_format() - Random book format
• book_series() - Random book series
• chapter_title() - Random chapter title
• literary_award() - Random literary award
• reading_level() - Random reading level
• book_condition() - Random book condition
• bookstore_type() - Random bookstore type
• publication_year() - Random publication year
• page_count() - Random page count
• isbn() - Random ISBN number
• book_rating() - Random book rating
• review_count() - Random review count
• edition() - Random book edition
• language() - Random language
• vehicle() - Random vehicle type
• vehicle_type() - Random vehicle type
• car_make() - Random car manufacturer
• car_model() - Random car model
• vehicle_make_model() - Random make and model
• vehicle_year() - Random vehicle year
• vehicle_color() - Random vehicle color
• fuel_type() - Random fuel type
• transmission() - Random transmission type
• engine_size() - Random engine size
• drive_type() - Random drive type
• vehicle_feature() - Random vehicle feature
• license_plate() - Random license plate
• vin() - Random VIN number
• vehicle_condition() - Random vehicle condition
• mileage() - Random mileage
• vehicle_price() - Random vehicle price
• dealership_type() - Random dealership type
• insurance_type() - Random insurance type
• mpg() - Random MPG
• horsepower() - Random horsepower
• seating_capacity() - Random seating capacity
• weather() - Random weather condition
• weather_description() - Detailed weather description
• temperature() - Random temperature
• temperature_celsius() - Temperature in Celsius
• temperature_fahrenheit() - Temperature in Fahrenheit
• wind_speed() - Random wind speed
• wind_direction() - Random wind direction
• humidity() - Random humidity percentage
• precipitation() - Random precipitation type
• precipitation_amount() - Random precipitation amount
• cloud_cover() - Random cloud cover level
• visibility() - Random visibility distance
• pressure() - Random atmospheric pressure
• uv_index() - Random UV index
• uv_index_level() - UV index level description
• air_quality() - Random air quality level
• air_quality_index() - Random AQI
• weather_alert() - Random weather alert
• season() - Random season
• moon_phase() - Random moon phase
• sunrise_time() - Random sunrise time
• sunset_time() - Random sunset time
• feels_like_temperature() - Feels like temperature
• dew_point() - Random dew point
• chance_of_rain() - Chance of rain percentage
• medical_specialty() - Random medical specialty
• medical_profession() - Random medical profession
• disease() - Random disease
• symptom() - Random symptom
• medical_test() - Random medical test
• medication() - Random medication
• medical_equipment() - Random medical equipment
• hospital_department() - Random hospital department
• blood_type() - Random blood type
• medical_abbreviation() - Random medical abbreviation
• body_system() - Random body system
• blood_pressure() - Random blood pressure
• heart_rate() - Random heart rate
• respiratory_rate() - Random respiratory rate
• body_temperature() - Random body temperature
• oxygen_saturation() - Random oxygen saturation
• medical_record_number() - Random medical record number
• patient_id() - Random patient ID
• prescription_number() - Random prescription number
• icd10_code() - Random ICD-10 code
• dosage() - Random medication dosage
• frequency() - Random medication frequency
• bmi() - Random BMI
• allergy() - Random allergy
• insurance_provider() - Random insurance provider
• diagnosis() - Random diagnosis
• degree_type() - Random degree type
• degree_abbr() - Random degree abbreviation
• degree() - Full degree name
• field_of_study() - Random field of study
• university_name() - Random university name
• school_level() - Random school level
• school_name() - Random school name
• academic_subject() - Random academic subject
• course_name() - Random course name
• course_code() - Random course code
• academic_title() - Random academic title
• extracurricular_activity() - Random extracurricular activity
• academic_honor() - Random academic honor
• letter_grade() - Random letter grade
• gpa() - Random GPA
• academic_term() - Random academic term
• academic_year() - Random academic year
• campus_facility() - Random campus facility
• student_classification() - Random student classification
• student_id() - Random student ID
• academic_department() - Random academic department
• credit_hours() - Random credit hours
• graduation_year() - Random graduation year
• class_size() - Random class size
• tuition_fee() - Random tuition fee
• scholarship_name() - Random scholarship name
• scholarship_amount() - Random scholarship amount
• attendance_rate() - Random attendance rate
• study_hours() - Random study hours per week

Requirements

• Python >= 3.10
• numpy
• pandas

License

MIT License - see LICENSE file for details

Credits

Randum is based on the excellent Faker library by joke2k and contributors. We are grateful for their work in creating such a comprehensive and well-maintained fake data generation library.

Original Faker Library:

• Repository: https://github.com/joke2k/faker
• Author: joke2k
• License: MIT

Randum has been customized and rebranded with additional features and modifications while maintaining the core functionality and spirit of the original Faker library.

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

Support

For issues and questions, please open an issue on GitHub: https://github.com/kactlabs/randum/issues