Welcome to Faker’s documentation!

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Faker is a Python package that generates fake data for you. Whether you need to bootstrap your database, create good-looking XML documents, fill-in your persistence to stress test it, or anonymize data taken from a production service, Faker is for you.

Faker is heavily inspired by PHP’s Faker, Perl’s Data::Faker, and by ruby’s Faker.

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Basic Usage

Install with pip:

pip install fake-factory

Use faker.Factory.create() to create and initialize a faker generator, which can generate data by accessing properties named after the type of data you want.

from faker import Factory
fake = Factory.create()

# OR
from faker import Faker
fake = Faker()

fake.name()
# 'Lucy Cechtelar'

fake.address()
# "426 Jordy Lodge
#  Cartwrightshire, SC 88120-6700"

fake.text()
# Sint velit eveniet. Rerum atque repellat voluptatem quia rerum. Numquam excepturi
# beatae sint laudantium consequatur. Magni occaecati itaque sint et sit tempore. Nesciunt
# amet quidem. Iusto deleniti cum autem ad quia aperiam.
# A consectetur quos aliquam. In iste aliquid et aut similique suscipit. Consequatur qui
# quaerat iste minus hic expedita. Consequuntur error magni et laboriosam. Aut aspernatur
# voluptatem sit aliquam. Dolores voluptatum est.
# Aut molestias et maxime. Fugit autem facilis quos vero. Eius quibusdam possimus est.
# Ea quaerat et quisquam. Deleniti sunt quam. Adipisci consequatur id in occaecati.
# Et sint et. Ut ducimus quod nemo ab voluptatum.

Each call to method fake.name() yields a different (random) result. This is because faker forwards faker.Generator.method_name() calls to faker.Generator.format(method_name).

for i in range(0,10):
  print fake.name()

    # Adaline Reichel
    # Dr. Santa Prosacco DVM
    # Noemy Vandervort V
    # Lexi O'Conner
    # Gracie Weber
    # Roscoe Johns
    # Emmett Lebsack
    # Keegan Thiel
    # Wellington Koelpin II
    # Ms. Karley Kiehn V

Providers

Each of the generator properties (like name, address, and lorem) are called Providers. A faker generator has many of them, packaged in “providers”.

Localization

faker.Factory can take a locale as an argument, to return localized data. If no localized provider is found, the factory fallbacks to the default locale (en_EN).

See the full list of included Locales.

Using from shell

In a python environment with faker installed you can use it with:

python -m faker [option] [*args]

[option]:

  • formatter name as text, address: display result of fake

[*args]: pass value to formatter (actually only strings)

$ python -m faker address
968 Bahringer Garden Apt. 722
Kristinaland, NJ 09890

How to create a Provider

from faker import Faker
fake = Faker()

# first, import a similar Provider or use the default one
from faker.providers import BaseProvider

# create new provider class
class MyProvider(BaseProvider):
    def foo(self):
        return 'bar'

# then add new provider to faker instance
fake.add_provider(MyProvider)

# now you can use:
fake.foo()
> 'bar'

How to use with factory-boy

import factory
from faker import Factory as FakerFactory
from myapp.models import Book

faker = FakerFactory.create()


class Book(factory.Factory):
    FACTORY_FOR = Book

    title = factory.LazyAttribute(lambda x: faker.sentence(nb_words=4))
    author_name = factory.LazyAttribute(lambda x: faker.name())

Seeding the Generator

You may want to get always the same generated data - for instance when using Faker for unit testing purposes. The generator offers a seed() method, which seeds the random number generator. Calling the same script twice with the same seed produces the same results.

from faker import Faker
fake = Faker()
fake.seed(4321)

print fake.name()   # Margaret Boehm

Tests

Run tests:

$ python setup.py test

or:

$ python -m unittest -v faker.tests

Write documentation for providers:

$ python -m faker > docs.txt

License

Faker is released under the MIT Licence. See the bundled LICENSE file for details.

Indices and tables