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Generate realistic fake data for testing without external dependencies

Project description

philiprehberger-test-data

Tests PyPI version License

Generate realistic fake data for testing without external dependencies.

Install

pip install philiprehberger-test-data

Usage

from philiprehberger_test_data import fake

# Basic generators
fake.name()          # "Alice Johnson"
fake.email()         # "bob.smith@example.com"
fake.integer(1, 100) # 42
fake.boolean()       # True
fake.uuid()          # "a1b2c3d4-..."

# Seed for reproducible output
fake.seed(42)
fake.name()  # always the same name with seed 42

# Bulk generation
fake.many(fake.name, 5)   # ["Alice Smith", "Bob Jones", ...]
fake.many(fake.integer, 3, 1, 100)  # [42, 87, 13]

API

Method Description
fake.seed(value) Set random seed for reproducible output
fake.name() Full name (first + last)
fake.first_name() First name
fake.last_name() Last name
fake.email() Email address
fake.integer(low, high) Random integer in [low, high]
fake.floating(low, high) Random float in [low, high]
fake.boolean() Random boolean
fake.choice(items) Random item from list
fake.sentence(words) Random sentence
fake.paragraph(sentences) Random paragraph
fake.uuid() UUID4 string
fake.date(start_year, end_year) Random date
fake.datetime_(start_year, end_year) Random datetime
fake.address() Street address
fake.full_address() Full address with city, state, ZIP
fake.phone() Phone number
fake.company() Company name
fake.hex_color() Hex color code
fake.ip_address() IPv4 address
fake.url() URL
fake.many(generator, count, *args, **kwargs) List of N generated values

License

MIT

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