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fix: respect both mulitple_of and minimum/maximum constraints #505

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fix: respect both mulitple_of and minimum/maximum constraints #505

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8881603
fix: respect both multiple_of and minimum/maximum constraints
richardxia Mar 18, 2024
08db6fa
Replace math.ulp with manually implemented code.
richardxia Mar 19, 2024
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117 changes: 66 additions & 51 deletions polyfactory/value_generators/constrained_numbers.py
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Original file line number Diff line number Diff line change
@@ -1,8 +1,9 @@
from __future__ import annotations

from decimal import Decimal
from math import ceil, floor, frexp
from sys import float_info
from typing import TYPE_CHECKING, Any, Protocol, TypeVar, cast
from typing import TYPE_CHECKING, Protocol, TypeVar, cast

from polyfactory.exceptions import ParameterException
from polyfactory.value_generators.primitives import create_random_decimal, create_random_float, create_random_integer
Expand Down Expand Up @@ -99,8 +100,8 @@ def is_multiply_of_multiple_of_in_range(
return False


def passes_pydantic_multiple_validator(value: T, multiple_of: T) -> bool:
"""Determine whether a given value passes the pydantic multiple_of validation.
def is_almost_multiple_of(value: T, multiple_of: T) -> bool:
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We should keep the passes_pydantic_multiple_)validator as it is and deprecate it and then create a new is_almost_multiple_of function as a replacement.

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Actually, we could just do something like this:

def passes_pydantic_multiple_validator(value: T, multiple_of: T)  -> bool:
    return is_almost_mulitple_of(value, multiple_of)

That is, changing the logic in it is fine since it's doing the same, but we would need to keep the old name around.

"""Determine whether a given ``value`` is a close enough to a multiple of ``multiple_of``.

:param value: A numeric value.
:param multiple_of: Another numeric value.
Expand All @@ -110,23 +111,37 @@ def passes_pydantic_multiple_validator(value: T, multiple_of: T) -> bool:
"""
if multiple_of == 0:
return True
mod = float(value) / float(multiple_of) % 1
return almost_equal_floats(mod, 0.0) or almost_equal_floats(mod, 1.0)
mod = value % multiple_of
return almost_equal_floats(float(mod), 0.0) or almost_equal_floats(float(abs(mod)), float(abs(multiple_of)))


def get_increment(t_type: type[T]) -> T:
def get_increment(value: T, t_type: type[T]) -> T:
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This would be a breaking change. Instead, we should have another get_increment_v2 function and deprecate this one.

"""Get a small increment base to add to constrained values, i.e. lt/gt entries.

:param t_type: A value of type T.
:param value: A value of type T.
:param t_type: The type of ``value``.

:returns: An increment T.
"""
values: dict[Any, Any] = {
int: 1,
float: float_info.epsilon,
Decimal: Decimal("0.001"),
}
return cast("T", values[t_type])
# See https://github.com/python/mypy/issues/17045 for why the redundant casts are ignored.
if t_type == int:
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All these checks should maybe use is_safe_subclass so that we handle custom int as well. Same for float and Decimal.

return cast("T", 1)
if t_type == float:
# When ``value`` is large in magnitude, we need to choose an increment that is large enough
# to not be rounded away, but when ``value`` small in magnitude, we need to prevent the
# incerement from vanishing. ``float_info.epsilon`` is defined as the smallest delta that
# can be represented between 1.0 and the next largest number, but it's not sufficient for
# larger values. We instead open up the floating-point representation to grab the exponent
# and calculate our own increment. This can be replaced with ``math.ulp`` in Python 3.9 and
# later.
_, exp = frexp(value)
increment = float_info.radix ** (exp - float_info.mant_dig + 1)
return cast("T", max(increment, float_info.epsilon))
Comment on lines +130 to +139
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I think it's probably fine to use math.ulp in the case of Python 3.9 and then fall back to this in case it's not 3.8. We have a constant called PY_38 in polyfactory.constants.py that you can use to handle this. Or maybe even something like:

if PY_38:
    def get_float_increment(value: float) -> float:
        # the current logic
else:
    def get_float_increment(value: float) -> float:
        # math.ulp based logic

Then we can just call this function without having to worry about the Python version.

if t_type == Decimal:
return cast("T", Decimal("0.001")) # type: ignore[redundant-cast]

msg = f"invalid t_type: {t_type}"
raise AssertionError(msg)


def get_value_or_none(
Expand All @@ -147,14 +162,14 @@ def get_value_or_none(
if ge is not None:
minimum_value = ge
elif gt is not None:
minimum_value = gt + get_increment(t_type)
minimum_value = gt + get_increment(gt, t_type)
else:
minimum_value = None

if le is not None:
maximum_value = le
elif lt is not None:
maximum_value = lt - get_increment(t_type)
maximum_value = lt - get_increment(lt, t_type)
else:
maximum_value = None
return minimum_value, maximum_value
Expand Down Expand Up @@ -210,33 +225,36 @@ def get_constrained_number_range(
return minimum, maximum


def generate_constrained_number(
def generate_constrained_multiple_of(
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Same as above regarding it being breaking changes.

random: Random,
minimum: T | None,
maximum: T | None,
multiple_of: T | None,
method: "NumberGeneratorProtocol[T]",
multiple_of: T,
) -> T:
"""Generate a constrained number, output depends on the passed in callbacks.
"""Generate a constrained multiple of ``multiple_of``.

:param random: An instance of random.
:param minimum: A minimum value.
:param maximum: A maximum value.
:param multiple_of: A multiple of value.
:param method: A function that generates numbers of type T.

:returns: A value of type T.
"""
if minimum is None or maximum is None:
return multiple_of if multiple_of is not None else method(random=random)
if multiple_of is None:
return method(random=random, minimum=minimum, maximum=maximum)
if multiple_of >= minimum:
return multiple_of
result = minimum
while not passes_pydantic_multiple_validator(result, multiple_of):
result = round(method(random=random, minimum=minimum, maximum=maximum) / multiple_of) * multiple_of
return result

# Regardless of the type of ``multiple_of``, we can generate a valid multiple of it by
# multiplying it with any integer, which we call a multiplier. We will randomly generate the
# multiplier as a random integer, but we need to translate the original bounds, if any, to the
# correct bounds on the multiplier so that the resulting product will meet the original
# constraints.

if multiple_of < 0:
minimum, maximum = maximum, minimum

multiplier_min = ceil(minimum / multiple_of) if minimum is not None else None
multiplier_max = floor(maximum / multiple_of) if maximum is not None else None
multiplier = create_random_integer(random=random, minimum=multiplier_min, maximum=multiplier_max)

return multiplier * multiple_of


def handle_constrained_int(
Expand Down Expand Up @@ -269,13 +287,11 @@ def handle_constrained_int(
multiple_of=multiple_of,
random=random,
)
return generate_constrained_number(
random=random,
minimum=minimum,
maximum=maximum,
multiple_of=multiple_of,
method=create_random_integer,
)

if multiple_of is None:
return create_random_integer(random=random, minimum=minimum, maximum=maximum)

return generate_constrained_multiple_of(random=random, minimum=minimum, maximum=maximum, multiple_of=multiple_of)


def handle_constrained_float(
Expand Down Expand Up @@ -308,13 +324,10 @@ def handle_constrained_float(
random=random,
)

return generate_constrained_number(
random=random,
minimum=minimum,
maximum=maximum,
multiple_of=multiple_of,
method=create_random_float,
)
if multiple_of is None:
return create_random_float(random=random, minimum=minimum, maximum=maximum)

return generate_constrained_multiple_of(random=random, minimum=minimum, maximum=maximum, multiple_of=multiple_of)


def validate_max_digits(
Expand Down Expand Up @@ -422,13 +435,15 @@ def handle_constrained_decimal(
if max_digits is not None:
validate_max_digits(max_digits=max_digits, minimum=minimum, decimal_places=decimal_places)

generated_decimal = generate_constrained_number(
random=random,
minimum=minimum,
maximum=maximum,
multiple_of=multiple_of,
method=create_random_decimal,
)
if multiple_of is None:
generated_decimal = create_random_decimal(random=random, minimum=minimum, maximum=maximum)
else:
generated_decimal = generate_constrained_multiple_of(
random=random,
minimum=minimum,
maximum=maximum,
multiple_of=multiple_of,
)

if max_digits is not None or decimal_places is not None:
return handle_decimal_length(
Expand Down
61 changes: 43 additions & 18 deletions tests/constraints/test_decimal_constraints.py
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Original file line number Diff line number Diff line change
Expand Up @@ -3,7 +3,7 @@
from typing import Optional, cast

import pytest
from hypothesis import given
from hypothesis import assume, given
from hypothesis.strategies import decimals, integers

from pydantic import BaseModel, condecimal
Expand All @@ -13,11 +13,24 @@
from polyfactory.value_generators.constrained_numbers import (
handle_constrained_decimal,
handle_decimal_length,
is_almost_multiple_of,
is_multiply_of_multiple_of_in_range,
passes_pydantic_multiple_validator,
)


def assume_max_digits(x: Decimal, max_digits: int) -> None:
"""
Signal to Hypothesis that ``x`` should have at most ``max_digits`` significant digits.

This is different than the ``decimals()`` strategy function's ``places`` keyword argument, which
only counts the digits after the decimal point when the number is written without an exponent.

E.g. 12.51 has 4 significant digits but 2 decimal places.
"""

assume(len(x.as_tuple().digits) <= max_digits)


def test_handle_constrained_decimal_without_constraints() -> None:
result = handle_constrained_decimal(
random=Random(),
Expand Down Expand Up @@ -162,7 +175,7 @@ def test_handle_constrained_decimal_handles_multiple_of(multiple_of: Decimal) ->
random=Random(),
multiple_of=multiple_of,
)
assert passes_pydantic_multiple_validator(result, multiple_of)
assert is_almost_multiple_of(result, multiple_of)
else:
with pytest.raises(ParameterException):
handle_constrained_decimal(
Expand All @@ -185,15 +198,17 @@ def test_handle_constrained_decimal_handles_multiple_of(multiple_of: Decimal) ->
max_value=1000000000,
),
)
def test_handle_constrained_decimal_handles_multiple_of_with_lt(val1: Decimal, val2: Decimal) -> None:
multiple_of, max_value = sorted([val1, val2])
def test_handle_constrained_decimal_handles_multiple_of_with_lt(max_value: Decimal, multiple_of: Decimal) -> None:
if multiple_of != Decimal("0"):
assume_max_digits(max_value, 10)
assume_max_digits(multiple_of, 10)
result = handle_constrained_decimal(
random=Random(),
multiple_of=multiple_of,
lt=max_value,
)
assert passes_pydantic_multiple_validator(result, multiple_of)
assert result < max_value
assert is_almost_multiple_of(result, multiple_of)
else:
with pytest.raises(ParameterException):
handle_constrained_decimal(
Expand All @@ -217,15 +232,17 @@ def test_handle_constrained_decimal_handles_multiple_of_with_lt(val1: Decimal, v
max_value=1000000000,
),
)
def test_handle_constrained_decimal_handles_multiple_of_with_le(val1: Decimal, val2: Decimal) -> None:
multiple_of, max_value = sorted([val1, val2])
def test_handle_constrained_decimal_handles_multiple_of_with_le(max_value: Decimal, multiple_of: Decimal) -> None:
if multiple_of != Decimal("0"):
assume_max_digits(max_value, 10)
assume_max_digits(multiple_of, 10)
result = handle_constrained_decimal(
random=Random(),
multiple_of=multiple_of,
le=max_value,
)
assert passes_pydantic_multiple_validator(result, multiple_of)
assert result <= max_value
assert is_almost_multiple_of(result, multiple_of)
else:
with pytest.raises(ParameterException):
handle_constrained_decimal(
Expand All @@ -249,15 +266,17 @@ def test_handle_constrained_decimal_handles_multiple_of_with_le(val1: Decimal, v
max_value=1000000000,
),
)
def test_handle_constrained_decimal_handles_multiple_of_with_ge(val1: Decimal, val2: Decimal) -> None:
min_value, multiple_of = sorted([val1, val2])
def test_handle_constrained_decimal_handles_multiple_of_with_ge(min_value: Decimal, multiple_of: Decimal) -> None:
if multiple_of != Decimal("0"):
assume_max_digits(min_value, 10)
assume_max_digits(multiple_of, 10)
result = handle_constrained_decimal(
random=Random(),
multiple_of=multiple_of,
ge=min_value,
)
assert passes_pydantic_multiple_validator(result, multiple_of)
assert min_value <= result
assert is_almost_multiple_of(result, multiple_of)
else:
with pytest.raises(ParameterException):
handle_constrained_decimal(
Expand All @@ -281,15 +300,17 @@ def test_handle_constrained_decimal_handles_multiple_of_with_ge(val1: Decimal, v
max_value=1000000000,
),
)
def test_handle_constrained_decimal_handles_multiple_of_with_gt(val1: Decimal, val2: Decimal) -> None:
min_value, multiple_of = sorted([val1, val2])
def test_handle_constrained_decimal_handles_multiple_of_with_gt(min_value: Decimal, multiple_of: Decimal) -> None:
if multiple_of != Decimal("0"):
assume_max_digits(min_value, 10)
assume_max_digits(multiple_of, 10)
result = handle_constrained_decimal(
random=Random(),
multiple_of=multiple_of,
gt=min_value,
)
assert passes_pydantic_multiple_validator(result, multiple_of)
assert min_value < result
assert is_almost_multiple_of(result, multiple_of)
else:
with pytest.raises(ParameterException):
handle_constrained_decimal(
Expand Down Expand Up @@ -322,21 +343,25 @@ def test_handle_constrained_decimal_handles_multiple_of_with_gt(val1: Decimal, v
def test_handle_constrained_decimal_handles_multiple_of_with_ge_and_le(
val1: Decimal,
val2: Decimal,
val3: Decimal,
multiple_of: Decimal,
) -> None:
min_value, multiple_of, max_value = sorted([val1, val2, val3])
min_value, max_value = sorted([val1, val2])
if multiple_of != Decimal("0") and is_multiply_of_multiple_of_in_range(
minimum=min_value,
maximum=max_value,
multiple_of=multiple_of,
):
assume_max_digits(min_value, 10)
assume_max_digits(max_value, 10)
assume_max_digits(multiple_of, 10)
result = handle_constrained_decimal(
random=Random(),
multiple_of=multiple_of,
ge=min_value,
le=max_value,
)
assert passes_pydantic_multiple_validator(result, multiple_of)
assert min_value <= result <= max_value
assert is_almost_multiple_of(result, multiple_of)
else:
with pytest.raises(ParameterException):
handle_constrained_decimal(
Expand Down
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