pytest-bonsai 0.0.1

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pytest bonsai

pytest-bonsai is a plugin that brings elegant, declarative, and composable test data to your test suite.

pytest-bonsai helps you grow minimal, yet expressive dependency trees using Python dataclasses, fixtures, and dynamic parameter resolution.

Installation

$ pip install pytest-bonsai

---

Basics: Dataclass Fixtures

Bonsai is built around indirect parametrization, but instead of using parametrization to multiply the number of test, it uses it to customize test setup.

A trivial example

from dataclasses import dataclass

from pytest_bonsai import parametrized_fixture, FixtureRequest


@dataclass
class User:
    name: str


@dataclass
class UserParam:
    name: str = "Alice"


@parametrized_fixture(User)
def user(request: FixtureRequest[UserParam]) -> User:
    return User(
        name=request.param.name,
    )


def test_alice(user: User):
    assert user.name == "Alice"


@user.parametrize(name="Bob")
def test_bob(user: User):
    assert user.name == "Bob"

A more interesting case

The UserParam dataclass can use other fixtures to set its default values:

from dataclasses import dataclass
import pytest

from pytest_bonsai import parametrized_fixture, FixtureRequest


@dataclass
class User:
    name: str


@pytest.fixture
def username():
    return "Charlie"


@dataclass
class UserParam:
    name: str = field(default_factory=username)


@parametrized_fixture(User)
def user(request: FixtureRequest[UserParam]) -> User:
    return User(
        name=request.param.name,
    )


def test_charlie(user):
    assert user.name == "Charlie"


@pytest.mark.parametrize("username", ["Derek"], indirect=True)
def test_derek(user):
    assert user.name == "Derek"

Always-indirect fixtures

Calling @parametrized_fixture without any arguments makes the fixture always indirect, and return the parameter:

from pytest_bonsai import parametrized_fixture


@parametrized_fixture
def email(request): ...


@email.parametrize('[e-mail]')
def test_edward(email):
    assert email == '[e-mail]')

While by itself it's not very useful, it makes it easier to define extension points like username from the previous example and email in the next one.

Even more interesting: lambdas that take fixtures

from dataclasses import dataclass, field
import pytest

from pytest_bonsai import parametrized_fixture, FixtureRequest


@dataclass
class User:
    name: str


@parametrized_fixture
def email(request): ...


@dataclass
class UserParam:
    name: str = field(default_factory=username)


@parametrized_fixture(User)
def user(request: FixtureRequest[UserParam]) -> User:
    return User(
        name=request.param.name,
    )


def test_charlie(user):
    assert user.name == "Charlie"


@user.parametrize(name=lambda email: email.split('@')[0].title())
@email.parametrize('[e-mail]')
def test_edward(user):
    assert user.name == "Edward"