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Polyfactory

Polyfactory is a simple and powerful mock data generation library, based around type hints and supporting dataclasses, typed-dicts, pydantic models, msgspec structs and more.

Polyfactory part of the Litestar project and as such actively maintained by a community of maintainers and contributors.

Example

from dataclasses import dataclass

from polyfactory.factories import DataclassFactory


@dataclass
class Person:
    name: str
    age: float
    height: float
    weight: float


class PersonFactory(DataclassFactory[Person]):
    ...


def test_is_person() -> None:
    person_instance = PersonFactory.build()
    assert isinstance(person_instance, Person)

That's it - with almost no work, we are able to create a mock data object fitting the Person class model definition.

This is possible because of the typing information available on the dataclass, which are used as a source of truth for data generation.

The factory parses the information stored in the dataclass and generates a dictionary of kwargs that are passed to Person.

Documentation

Usage and API reference documentation is available on https://polyfactory.litestar.dev/.

Installation

pip install polyfactory

Relation to Pydantic-Factories

Prior to version 2, this library was known as pydantic-factories, a name under which it gained quite a bit of popularity. A main motivator for the 2.0 release was that we wanted to support more than just Pydantic models, something which also required a change to its core architecture. As this library would no longer be directly tied to Pydantic, polyfactory was chosen as its new name to reflect its capabilities; It can generate mock data for dataclasses, typed-dicts, Pydantic, odmantic, and beanie ODM models, as well as custom factories.

Contributing

This library is a community driven open source project. We welcome and encourage contributions. Please check out the GitHub issues, read the contribution guide (at the repository's root), and you're always welcome to join our discord server.

Contributors ✨

Thanks goes to these wonderful people (emoji key):

Na'aman Hirschfeld
Na'aman Hirschfeld

🚧 🚇 ⚠️ 💻 📖
Jacob Coffee
Jacob Coffee

🚧 📖 ⚠️
Janek Nouvertné
Janek Nouvertné

🚧 📖 ⚠️ 💻
Peter Schutt
Peter Schutt

🚧 ⚠️ 💻 📖
Marek Czaplicki
Marek Czaplicki

💻 ⚠️
Piotr Przybyło
Piotr Przybyło

💻
sygutss
sygutss

🐛 💻
chrisbeardy
chrisbeardy

📖
guacs
guacs

💻 🚇 📖 ⚠️ 🚧
Vadim
Vadim

💻
Simske
Simske

💻
Sondre Lillebø Gundersen
Sondre Lillebø Gundersen

💻
Mateusz Ciszczoń
Mateusz Ciszczoń

💻
Pedro Bernardes
Pedro Bernardes

💻
Martin Roy
Martin Roy

💻
Matthew Aylward
Matthew Aylward

💻
Elton H.Y. Chou
Elton H.Y. Chou

💻
Thang
Thang

💻
Daan
Daan

💻
Lyz
Lyz

💻
Thorin Schiffer
Thorin Schiffer

💻
Iipin
Iipin

💻
avihai-yosef
avihai-yosef

💻
anthonyh209
anthonyh209

💻
Roman Reznikov
Roman Reznikov

💻
gigelu
gigelu

💻
Rodrigo Medina
Rodrigo Medina

💻
Gerrit Egnew
Gerrit Egnew

💻
danielkatzan
danielkatzan

📖
Abdulhaq Emhemmed
Abdulhaq Emhemmed

💻
klimantje
klimantje

💻
Tom Crasset
Tom Crasset

💻
cătălin
cătălin

💻
Andrew Truong
Andrew Truong

💻 📖
Anthony
Anthony

💻 📖 ⚠️
Jonathan Liuti
Jonathan Liuti

💻 📖 ⚠️
Julio Olivera
Julio Olivera

💻 ⚠️
Benoît Godard
Benoît Godard

💻 📖 ⚠️
Henry Sorsky
Henry Sorsky

🚇
Kim Minki
Kim Minki

📖
Tim Joseph Dumol
Tim Joseph Dumol

📖

This project follows the all-contributors specification. Contributions of any kind welcome!

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  • Python 98.6%
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