polyfactory

name	polyfactory
description	Auto-activate for polyfactory, ModelFactory, DataclassFactory, MsgspecFactory, AttrsFactory, Use, register_fixture, pytest plugin, __random_seed__, or coverage(). Not for production seeding.

polyfactory

Polyfactory is a typed mock-data factory library: declare ModelFactory[T] (or DataclassFactory, MsgspecFactory, AttrsFactory, TypedDictFactory) and .build() returns a populated instance of T. The matching factory base inspects the model's annotations and supported constraints so tests do not need hand-written happy-path fixtures.

In Litestar projects, polyfactory's pytest plugin is the canonical way to feed TestClient.post(...) / AsyncTestClient.put(...) payloads. The companion skill litestar:litestar-testing covers the request side.

Code Style Rules

• PEP 604 unions: T | None, never Optional[T].
• One factory per model. Don't reuse a factory across unrelated models — clarity beats DRY when the test fails at 3am.
• Pick the right factory base by backend: ModelFactory (Pydantic), DataclassFactory, MsgspecFactory, AttrsFactory, TypedDictFactory. A mismatched base raises ConfigurationException.
• Prefer register_fixture over hand-rolled @pytest.fixture wrappers. Call it in a pytest-discovered test module or conftest.py so the injected fixture is collected.

Quick Reference

Picking the right factory base

Model kind	Factory base	Import
pydantic.BaseModel	ModelFactory	from polyfactory.factories.pydantic_factory import ModelFactory
@dataclass	DataclassFactory	from polyfactory.factories import DataclassFactory
msgspec.Struct	MsgspecFactory	from polyfactory.factories.msgspec_factory import MsgspecFactory
@attrs.define / attr.s	AttrsFactory	from polyfactory.factories.attrs_factory import AttrsFactory
TypedDict	TypedDictFactory	from polyfactory.factories.typed_dict_factory import TypedDictFactory
Beanie / Odmantic / SQLA	dedicated bases	see factories.md

Defining a factory

from dataclasses import dataclass
from polyfactory.factories import DataclassFactory


@dataclass
class Order:
    id: int
    customer_email: str
    total_cents: int
    status: str


class OrderFactory(DataclassFactory[Order]):
    pass


# Use it
one = OrderFactory.build()
many = OrderFactory.batch(10)

The single concrete generic argument lets Polyfactory infer __model__. build() returns one instance, batch(n) returns list[T], and coverage() yields the smallest set of instances that covers the model's supported variants.

Customizing fields

from polyfactory import Use
from polyfactory.factories import DataclassFactory


class OrderFactory(DataclassFactory[Order]):
    # Plain literal — every build returns this exact value
    status = "pending"

    # Callable — re-evaluated per build
    customer_email = Use(lambda: "[e-mail]")

    # Random choice — re-evaluated per build
    total_cents = Use(DataclassFactory.__random__.randint, 100, 10_000)

Use(callable, *args, **kwargs) is re-invoked on every build(), so each generated instance gets a fresh value.

Use PostGenerated when a field depends on values generated for the same instance:

from typing import Any

from polyfactory import PostGenerated


def order_reference(name: str, values: dict[str, Any], prefix: str) -> str:
    return f"{prefix}-{values['id']}"


class OrderFactory(DataclassFactory[Order]):
    reference = PostGenerated(order_reference, "order")

The callback signature is (field_name, generated_values, *args, **kwargs). generated_values contains the non-post-generated fields.

Determinism

class OrderFactory(DataclassFactory[Order]):
    __random_seed__ = 42  # same seed → same output across runs

Set __random_seed__ (or __faker__ = Faker(seed=...) for finer Faker control) when test assertions depend on the exact generated values.

Default factory registration

class CustomerFactory(DataclassFactory[Customer]):
    __set_as_default_factory_for_type__ = True


@dataclass
class Order:
    id: int
    customer: Customer  # automatically populated by CustomerFactory.build()


class OrderFactory(DataclassFactory[Order]):
    pass

When __set_as_default_factory_for_type__ = True, polyfactory uses that factory whenever the type appears as a field on another model — no manual nesting required.

Pytest fixture from a factory

from polyfactory.pytest_plugin import register_fixture
from polyfactory.factories import DataclassFactory


@register_fixture
class OrderFactory(DataclassFactory[Order]):
    pass


def test_order_total(order_factory: type[OrderFactory]) -> None:
    order = order_factory.build()
    assert order.total_cents >= 0

@register_fixture returns the class unchanged and injects a pytest fixture into the caller's module. The fixture name is the snake-cased class name and its value is the factory class.

Cross-model relationships

from polyfactory import Use
from polyfactory.pytest_plugin import register_fixture


@register_fixture
class CustomerFactory(DataclassFactory[Customer]):
    __set_as_default_factory_for_type__ = True


@register_fixture
class OrderFactory(DataclassFactory[Order]):
    customer = Use(CustomerFactory.build)  # explicit local override

__set_as_default_factory_for_type__ = True lets Polyfactory populate nested Customer fields with CustomerFactory. Use Use(CustomerFactory.build) when one parent factory needs an explicit local override.

Workflow

Step 1: Pick the factory base

Match the base to your model backend (table above). A mismatched base fails during factory class creation. If your project uses multiple backends (e.g., Pydantic for HTTP DTOs + msgspec for internal events), import each base separately and don't try to share a factory across backends.

Step 2: Define one factory per model

Subclass the appropriate base with one concrete generic argument and let Polyfactory infer __model__. Set __model__ explicitly only when the generic declaration cannot identify exactly one model. Keep factories in tests/factories.py or tests/<feature>/factories.py, outside production code paths.

Step 3: Customize only what the test cares about

If a field can take any valid value, leave it for the factory to randomize. Override (literal value or Use(...)) only fields the assertion depends on. Tests that pin every field defeat the purpose of using a factory.

Step 4: Register as a pytest fixture (if used widely)

For factories used in many tests, decorate with @register_fixture in a pytest-discovered module and consume the snake-cased fixture name. For one-off use, call Factory.build() directly inline.

Step 5: Wire cross-model relationships

Set __set_as_default_factory_for_type__ = True on a base factory and let nested fields be populated automatically, or use Use(OtherFactory.build) for a local relationship override.

Step 6: Pin determinism only when needed

Tests that assert on specific generated values need __random_seed__. Tests that assert on shape or invariants (e.g., total >= 0) should not — leaving randomization on widens coverage across runs.

Guardrails

• Use one concrete generic argument or set __model__. Polyfactory infers __model__ from DataclassFactory[Order]; an unparameterized concrete factory without __model__ raises ConfigurationException during class creation.
• Don't override fields you're about to assert on with random values. Either pin the value (status = "pending") or assert on shape, not both.
• Don't reuse __random_seed__ across factories that share a Faker instance. They will collide and produce unexpected duplicates. Use a different seed per factory or a single shared seeded __faker__.
• Use the right base for the backend. ModelFactory on a msgspec.Struct raises ConfigurationException; use MsgspecFactory.
• Factories belong under tests/. Importing them from production modules ties test data to runtime code and is a refactor hazard.
• coverage() is not a Cartesian-product generator. It emits a minimal representative set and reuses exhausted field variants; use Hypothesis for exhaustive input-space exploration.
• __allow_none_optionals__ is boolean. True allows random None values during build(); False always generates the wrapped type. It is not a probability.
• Async methods persist data. create_async() and create_batch_async() require __async_persistence__ or a backend factory that supplies it. Polyfactory has no build_async().

Validation Checkpoint

Before delivering polyfactory code, verify:

• Factory base matches the model backend (Pydantic → ModelFactory, dataclass → DataclassFactory, msgspec → MsgspecFactory, attrs → AttrsFactory).
• Each factory has one concrete generic model argument or an explicit __model__.
• Factories live under tests/ (or a sibling test-only module), never in production code.
• Fields overridden in the factory match what the test asserts on; fields the test does not care about are left for randomization.
• If the test asserts on exact values, __random_seed__ is set; otherwise it is not.
• @register_fixture is used for factories shared across more than ~2 test files; one-offs call .build() inline.
• Cross-model relationships use __set_as_default_factory_for_type__ or Use(OtherFactory.build).
• register_fixture is invoked in a pytest-discovered module.
• Async factory calls use create_async() / create_batch_async() only when persistence is configured.

Example: Litestar handler test with msgspec DTOs and polyfactory

# tests/factories.py
from polyfactory.factories.msgspec_factory import MsgspecFactory

from myapp.events import OrderCreatedEvent  # msgspec.Struct


class OrderCreatedEventFactory(MsgspecFactory[OrderCreatedEvent]):
    pass

# tests/conftest.py
from polyfactory.pytest_plugin import register_fixture

from tests.factories import OrderCreatedEventFactory


register_fixture(OrderCreatedEventFactory)

# tests/test_orders.py
from __future__ import annotations  # consumer module — fine to use future annotations

import msgspec
import pytest
from litestar.testing import AsyncTestClient

from tests.factories import OrderCreatedEventFactory


@pytest.mark.anyio
async def test_create_order_emits_event(
    client: AsyncTestClient,
    order_created_event_factory: type[OrderCreatedEventFactory],
) -> None:
    payload = order_created_event_factory.build()
    response = await client.post("/orders", json=msgspec.to_builtins(payload))

    assert response.status_code == 201
    assert response.json()["id"] == payload.id

The factory provides a fully-populated, validation-passing OrderCreatedEvent; the test focuses on the request/response contract instead of constructing fake data inline.

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References Index

For detailed guides, refer to the following documents in references/:

• Factories — Per-backend factory bases, model inference, randomization control, PostGenerated, model coverage, persistence protocols, and SQLAlchemy 3.3 persistence behavior.
• Pytest integration — @register_fixture, separate registration from conftest.py, fixture scoping and naming, collection boundaries, and async persistence.
• Litestar patterns — Using factories with TestClient / AsyncTestClient, parametrizing handler tests via coverage(), integrating with litestar-testing fixtures, msgspec DTOs, advanced-alchemy model factories, and SAQ task payload generation.

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Official References

• https://github.com/litestar-org/polyfactory/tree/v3.3.0/polyfactory — immutable v3.3.0 source
• https://github.com/litestar-org/polyfactory/tree/v3.3.0/tests — immutable v3.3.0 contract tests
• https://github.com/litestar-org/polyfactory/releases/tag/v3.3.0 — v3.3.0 release
• https://polyfactory.litestar.dev/
• https://polyfactory.litestar.dev/usage/index.html
• https://polyfactory.litestar.dev/usage/library_factories/index.html
• https://polyfactory.litestar.dev/usage/decorators.html
• https://polyfactory.litestar.dev/usage/fixtures.html
• https://polyfactory.litestar.dev/usage/configuration.html
• https://github.com/litestar-org/polyfactory

Shared Styleguide Baseline

• General Principles
• Python