object-mother-pattern

name	object-mother-pattern
description	Use this skill whenever a user is writing Python tests, pytest fixtures, validation tests, factories, or generated test data with the object-mother-pattern package. It teaches agents how to choose and call Object Mother classes, compose ListMother and DictMother, create custom BaseMother subclasses, update exports and docs, and avoid brittle random assertions. Trigger when prompts mention object mothers, object_mother_pattern, Object Mother Pattern, test data, invalid values, boundary values, UUIDs, dates, URLs, identifiers, credit cards, or package mother APIs.
compatibility	Python projects using object-mother-pattern. The package supports Python 3.11 and newer; this repository tests Python 3.11, 3.12, 3.13, and 3.14.

Object Mother Pattern

Use this skill to work with the object-mother-pattern Python package in tests, fixtures, and downstream projects. The package provides reusable typed mother classes that generate valid, invalid, boundary, and explicit test data.

First Steps

1. Identify whether the user is consuming the package, changing the package itself, or creating downstream custom mothers.
2. Check the installed package version or local repository when exact API availability matters.
3. Choose the most specific mother that matches the test intent.
4. Use generated values only when assertions check invariants. Use explicit literals or create(value=...) when exact output matters.
5. For negative tests, prefer invalid_type(), invalid_value(), out_of_range(), or category-specific helpers over ad hoc invalid data.

Load References

Read only the references needed for the task:

Need	Read
Full public API, imports, method signatures	references/api-catalog.md
How to choose mothers and compose fixtures	references/usage-patterns.md
Testing strategy and anti-flakiness guidance	references/testing-patterns.md
Creating or editing custom mothers	references/custom-mothers.md

Core Rules

• Prefer existing mothers before inventing new fixture helpers.
• Use generated values for type, shape, and invariant tests.
• Use fixed literals for snapshots, serialization, exact strings, SQL, JSON, URLs, and reproduced bugs.
• Use create(value=...) when a test needs a known value but should still exercise mother validation.
• Keep random values out of exact assertions. Assert properties such as type, length, range, prefix, suffix, UUID version, URL scheme, or parsed components.
• Compose ListMother and DictMother with callables such as IntegerMother.positive, StringMother.create, or lambdas.
• Treat generated financial, identifier, person, and network values as test fixtures only, not real credentials, identities, ownership proof, or production data.

Common Imports

from object_mother_pattern import DateMother, IntegerMother, StringMother
from object_mother_pattern.models import DictMother, ListMother
from object_mother_pattern.mothers.internet import EmailAddressMother, UrlMother
from object_mother_pattern.mothers.identifiers.uuid import UuidV4Mother

Use top-level imports for common primitives, dates, datetimes, and money mothers. Use category imports for specialized internet, identifier, people, extra text, and country-specific mothers.

Quick Examples

Generate valid values when the exact value does not matter:

from object_mother_pattern import IntegerMother
from object_mother_pattern.mothers.internet import EmailAddressMother

email = EmailAddressMother.create()
quantity = IntegerMother.positive()

assert '@' in email
assert quantity > 0

Validate an explicit value when exact data matters:

from object_mother_pattern import StringMother

assert StringMother.create(value='invoice-paid') == 'invoice-paid'

Build a composed payload:

from object_mother_pattern import IntegerMother, StringMother
from object_mother_pattern.models import DictMother

payload = DictMother.of_length(
    length=3,
    key_mother=lambda: StringMother.lowercase(min_length=4, max_length=12),
    value_mother=IntegerMother.positive,
)

assert len(payload) == 3
assert all(value > 0 for value in payload.values())

Test validation failures:

from pytest import raises

from object_mother_pattern import IntegerMother

with raises(TypeError):
    IntegerMother.create(value=IntegerMother.invalid_type())

too_low_or_too_high = IntegerMother.out_of_range(min=1, max=10)
assert too_low_or_too_high < 1 or too_low_or_too_high > 10