Faker

40.11.1 · active · verified Sat Mar 28

Faker is a Python package that generates fake data such as names, addresses, emails, and more, for various purposes including testing applications, populating databases, creating sample reports, and anonymizing sensitive data. It is currently on version 40.11.1 and maintains an active development cycle with frequent releases.

Warnings

breaking Faker dropped support for Python 2 starting from version 4.0.0, and from version 5.0.0, it only supports Python 3.8 and above. For Python 2 compatibility, install version 3.0.1.
Fix: Upgrade Python to 3.10+ or pin Faker to an older, compatible version (e.g., `Faker==3.0.1` for Python 2).
breaking Calling the `seed()` method on a `Faker` *instance* (e.g., `fake.seed(0)`) is deprecated and will raise a `TypeError`. Seeding should now be done using the class method `Faker.seed(0)` for consistent results across test runs.
Fix: Change `fake_instance.seed(value)` to `Faker.seed(value)`.
gotcha While `Faker.seed()` ensures reproducibility for a given Faker version, the generated data is not guaranteed to be consistent across *patch versions* (e.g., between 40.11.0 and 40.11.1) due to potential dataset updates.
Fix: For strict reproducibility in tests or data generation where results must be identical across environments and time, pin the Faker library to a specific patch version in your `requirements.txt` (e.g., `Faker==40.11.1`).
gotcha The Faker package was previously known as `fake-factory` and was deprecated by the end of 2016. Ensure your project and its dependencies do not rely on the old `fake-factory` package to avoid conflicts or outdated behavior.
Fix: Migrate any lingering `fake-factory` dependencies to `faker`.
gotcha When using the `.unique` property on a Faker generator, be aware that if it struggles to find a unique value after a number of attempts (especially with a small pool of possible values), it will raise a `UniquenessException` to prevent infinite loops.
Fix: Ensure the pool of unique values is sufficiently large or handle `UniquenessException` in your code if uniqueness is critical but the pool is limited.

Install

pip install Faker Install latest version

Imports

Faker
```
from faker import Faker
```
The `Factory.create()` method was the old way to instantiate a Faker generator (pre-v2.0.4) and is now superseded by directly importing and instantiating the `Faker` class.

Quickstart

Initialize the Faker generator and access various fake data providers as properties. Each call generates a different random value by default. Locales can be specified for region-specific data.

from faker import Faker

fake = Faker('en_US') # You can specify a locale

print("Fake Name:", fake.name())
print("Fake Address:", fake.address())
print("Fake Email:", fake.email())
print("Fake Text:", fake.text(max_nb_chars=100))

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