fake.py 0.6.7

Minimalistic, standalone alternative fake data generator with no dependencies.

Minimalistic, standalone alternative fake data generator with no dependencies.

fake.py is a standalone, portable library designed for generating various random data types for testing.

It offers a simplified, dependency-free alternative for creating random texts, (person) names, URLs, dates, file names, IPs, primitive Python data types (such as uuid, str, int, float, bool) and byte content for multiple file formats including PDF, DOCX, PNG, SVG, BMP, and GIF.

The package also supports file creation on the filesystem and includes factories (dynamic fixtures) compatible with Django, TortoiseORM, Pydantic and SQLAlchemy.

Features

• Generation of random texts, (person) names, emails, URLs, dates, IPs, and primitive Python data types.

• Support for various file formats (PDF, DOCX, TXT, PNG, SVG, BMP, GIF) and file creation on the filesystem.

• Basic factories for integration with Django, Pydantic, TortoiseORM and SQLAlchemy.

Prerequisites

Python 3.8+

Installation

pip

pip install fake.py

Download and copy

fake.py is the sole, self-contained module of the package. It includes tests too. If it’s more convenient to you, you could simply download the fake.py module and include it in your repository.

Since tests are included, it won’t have a negative impact on your test coverage (you might need to apply tweaks to your coverage configuration).

Documentation

• Documentation is available on Read the Docs.

• For various ready to use code examples see the Recipes.

• For tips on how to use the factories see the Factories.

• For customization tips see the Customization.

• For tips on PDF creation see Creating PDF.

• For tips on DOCX creation see Creating DOCX.

• For tips on images creation see Creating images.

• For guidelines on contributing check the Contributor guidelines.

• For various implementation examples, see the Examples.

Usage

Generate data

Person names

from fake import FAKER

FAKER.first_name()
FAKER.last_name()
FAKER.name()
FAKER.username()

Random texts

from fake import FAKER

FAKER.slug()
FAKER.word()
FAKER.sentence()
FAKER.paragraph()
FAKER.text()

Internet

from fake import FAKER

FAKER.email()
FAKER.url()
FAKER.ipv4()

Filenames

from fake import FAKER

FAKER.filename()

Primitive data types

from fake import FAKER

FAKER.pyint()
FAKER.pybool()
FAKER.pystr()
FAKER.pyfloat()

Dates

from fake import FAKER

FAKER.date()
FAKER.date_time()

Generate files

As bytes

from fake import FAKER

FAKER.pdf()
FAKER.docx()
FAKER.png()
FAKER.svg()
FAKER.bmp()
FAKER.gif()

As files on the file system

from fake import FAKER

FAKER.pdf_file()
FAKER.docx_file()
FAKER.png_file()
FAKER.svg_file()
FAKER.bmp_file()
FAKER.gif_file()
FAKER.txt_file()

Factories

This is how you could define factories for Django’s built-in Group and User models.

from django.contrib.auth.models import Group, User
from fake import (
    DjangoModelFactory,
    FACTORY,
    PostSave,
    PreSave,
    trait,
)


class GroupFactory(DjangoModelFactory):
    """Group factory."""

    name = FACTORY.word()

    class Meta:
        model = Group
        get_or_create = ("name",)


def set_password(user: User, password: str) -> None:
    """Helper function for setting password for the User."""
    user.set_password(password)


def add_to_group(user: User, name: str) -> None:
    """Helper function for adding the User to a Group."""
    group = GroupFactory(name=name)
    user.groups.add(group)


class UserFactory(DjangoModelFactory):
    """User factory."""

    username = FACTORY.username()
    first_name = FACTORY.first_name()
    last_name = FACTORY.last_name()
    email = FACTORY.email()
    date_joined = FACTORY.date_time()
    last_login = FACTORY.date_time()
    is_superuser = False
    is_staff = False
    is_active = FACTORY.pybool()
    password = PreSave(set_password, password="test1234")
    group = PostSave(add_to_group, name="Test group")

    class Meta:
        model = User
        get_or_create = ("username",)

    @trait
    def is_admin_user(self, instance: User) -> None:
        """Trait."""
        instance.is_superuser = True
        instance.is_staff = True
        instance.is_active = True

And this is how you could use it:

# Create just one user
user = UserFactory()

# Create 5 users
users = UserFactory.create_batch(5)

# Create a user using `is_admin_user` trait
user = UserFactory(is_admin_user=True)

# Create a user with custom password
user = UserFactory(
    password=PreSave(set_password, password="another-password"),
)

# Add a user to another group
user = UserFactory(
    group=PostSave(add_to_group, name="Another group"),
)

# Or even add user to multiple groups at once
user = UserFactory(
    group_1=PostSave(add_to_group, name="Another group"),
    group_2=PostSave(add_to_group, name="Yet another group"),
)

Customize

Make your own custom providers and utilize factories with them.

import random
import string

from fake import Faker, Factory, provider


class CustomFaker(Faker):

    @provider
    def postal_code(self) -> str:
        number_part = "".join(random.choices(string.digits, k=4))
        letter_part = "".join(random.choices(string.ascii_uppercase, k=2))
        return f"{number_part} {letter_part}"


FAKER = CustomFaker()
FACTORY = Factory(FAKER)

Now you can use it as follows (make sure to import your custom instances of FAKER and FACTORY):

FAKER.postal_code()

from fake import ModelFactory


class AddressFactory(ModelFactory):

    # ... other definitions
    postal_code = FACTORY.postal_code()
    # ... other definitions

    class Meta:
        model = Address

Tests

Run the tests with unittest:

python -m unittest fake.py

Or pytest:

pytest

Differences with alternatives

fake.py is Faker + factory_boy + faker-file in one package, radically simplified and reduced in features, but without any external dependencies (not even Pillow or dateutil).

fake.py is modeled after the famous Faker package. Its’ API is highly compatible, although drastically reduced. It’s not multilingual and does not support postal codes or that many RAW file formats. However, you could easily include it in your production setup without worrying about yet another dependency.

On the other hand, fake.py factories look quite similar to factory_boy factories, although again - drastically simplified and reduced in features.

The file generation part of fake.py are modelled after the faker-file. You don’t get a large variety of file types supported and you don’t have that much control over the content of the files generated, but you get dependency-free valid files and if that’s all you need, you don’t need to look further.

However, at any point, if you discover that you “need more”, go for Faker, factory_boy and faker-file combination.

License

MIT

Support

For security issues contact me at the e-mail given in the Author section.

For overall issues, go to GitHub.

Author

Artur Barseghyan <[e-mail]>