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Hypothesis plugin

Hypothesis is the Python library for property-based testing. Hypothesis can infer how to construct type-annotated classes, and supports builtin types, many standard library types, and generic types from the typing and typing_extensions modules by default.

From Pydantic v1.8 and Hypothesis v5.29.0, Hypothesis will automatically load support for custom types like PaymentCardNumber and PositiveFloat, so that the st.builds() and st.from_type() strategies support them without any user configuration.

Warning

Please note, while the plugin supports these types, hypothesis will(currently) generate values outside of given args for the constrained function types.

Example tests

import typing
from hypothesis import given, strategies as st
from pydantic import BaseModel, EmailStr, PaymentCardNumber, PositiveFloat


class Model(BaseModel):
    card: PaymentCardNumber
    price: PositiveFloat
    users: typing.List[EmailStr]


@given(st.builds(Model))
def test_property(instance):
    # Hypothesis calls this test function many times with varied Models,
    # so you can write a test that should pass given *any* instance.
    assert 0 < instance.price
    assert all('@' in email for email in instance.users)


@given(st.builds(Model, price=st.floats(100, 200)))
def test_with_discount(instance):
    # This test shows how you can override specific fields,
    # and let Hypothesis fill in any you don't care about.
    assert 100 <= instance.price <= 200
from hypothesis import given, strategies as st
from pydantic import BaseModel, EmailStr, PaymentCardNumber, PositiveFloat


class Model(BaseModel):
    card: PaymentCardNumber
    price: PositiveFloat
    users: list[EmailStr]


@given(st.builds(Model))
def test_property(instance):
    # Hypothesis calls this test function many times with varied Models,
    # so you can write a test that should pass given *any* instance.
    assert 0 < instance.price
    assert all('@' in email for email in instance.users)


@given(st.builds(Model, price=st.floats(100, 200)))
def test_with_discount(instance):
    # This test shows how you can override specific fields,
    # and let Hypothesis fill in any you don't care about.
    assert 100 <= instance.price <= 200

(This script is complete, it should run "as is")

Use with JSON Schemas

To test client-side code, you can use Model.schema() with the hypothesis-jsonschema package to generate arbitrary JSON instances matching the schema. For web API testing, Schemathesis provides a higher-level wrapper and can detect both errors and security vulnerabilities.