Faker

Faker is a Python package that generates fake data for you.

faker Permissive license MIT License Active ★ 19,370 v40.36.0 released 2026-07-24

Install

faker on PyPI

pip

pip install faker

uv

uv add faker

poetry

poetry add faker

Package facts

License	MIT License (permissive)
Python support	supports the current Python release (>=3.10)
Install friction	low — pure-Python wheel
Runtime dependencies	1 — tzdata
Maintenance	actively maintained — 20 days since the last release
Last repo commit	2026-08-03
First released	2010-12-23
Popularity	one of the top 1,000 most-downloaded packages on PyPI (30-day window, as of 2026-08-13)
Known vulnerabilities	none known (OSV.dev, checked 2026-08-13)

Evidence: faker-40.36.0-py3-none-any.whl

Keywords: faker, fixtures, data, test, mock, generator

Development Status :: 5 - Production/StableEnvironment :: ConsoleIntended Audience :: DevelopersLicense :: OSI Approved :: MIT LicenseProgramming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14Programming Language :: Python :: Implementation :: CPythonProgramming Language :: Python :: Implementation :: PyPyTopic :: Software Development :: Libraries :: Python ModulesTopic :: Software Development :: TestingTopic :: Utilities

About Faker

from the package's own PyPI description — quoted content, verbatim

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 Faker, Perl Faker, and by Ruby Faker_.

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Compatibility

Starting from version 4.0.0, Faker dropped support for Python 2 and from version 5.0.0 only supports Python 3.8 and above. If you still need Python 2 compatibility, please install version 3.0.1 in the meantime, and please consider updating your codebase to support Python 3 so you can enjoy the latest features Faker has to offer. Please see the extended docs_ for more details, especially if you are upgrading from version 2.0.4 and below as there might be breaking changes.

This package was also previously called fake-factory...

Read as markdown · JSON record · Source repository · Homepage · Docs

AI interpretation — verify before relying

AI-generated interpretation of the package facts above; every digit, version, license, or vulnerability id it cites is grounded in the facts already shown on this page

Faker generates realistic fake data across many categories—names, addresses, emails, dates, and more—for database bootstrapping, testing, anonymization, and stress-testing applications.

Minimal friction: pure Python wheel with only tzdata as a runtime dependency. Active maintenance with a release 20 days ago signals strong ongoing support.

MIT License (permissive) places no restrictions on commercial or proprietary use, modification, or distribution—standard permissive terms.

Usage

pip install Faker

from faker import Faker
fake = Faker()
print(fake.name())
print(fake.address())

Requires Python 3.10 or above.

Verdict: Faker is a mature, actively maintained package (top_1000 tier on PyPI, zero known vulnerabilities) with low install friction and permissive licensing. It is well-suited for test data generation, database seeding, and anonymization tasks across Python 3.10+.

Needs verification

Whether tzdata is a compiled/system dependency or pure Python (affects true portability).
Performance characteristics when generating large volumes of data with use_weighting enabled.
Community adoption metrics beyond maintenance status.

fake data generatortest data generationmock data for testingdatabase seedinganonymize production datafaker library pythonrandom realistic datafixtures for unit tests