Pydantic Types

The types module contains custom types used by pydantic.

StrictBool module-attribute

StrictBool = Annotated[bool, Strict()]

A boolean that must be either True or False.

PositiveInt module-attribute

PositiveInt = Annotated[int, annotated_types.Gt(0)]

An integer that must be greater than zero.

NegativeInt module-attribute

NegativeInt = Annotated[int, annotated_types.Lt(0)]

An integer that must be less than zero.

NonPositiveInt module-attribute

NonPositiveInt = Annotated[int, annotated_types.Le(0)]

An integer that must be less than or equal to zero.

NonNegativeInt module-attribute

NonNegativeInt = Annotated[int, annotated_types.Ge(0)]

An integer that must be greater than or equal to zero.

StrictInt module-attribute

StrictInt = Annotated[int, Strict()]

An integer that must be validated in strict mode.

PositiveFloat module-attribute

PositiveFloat = Annotated[float, annotated_types.Gt(0)]

A float that must be greater than zero.

NegativeFloat module-attribute

NegativeFloat = Annotated[float, annotated_types.Lt(0)]

A float that must be less than zero.

NonPositiveFloat module-attribute

NonPositiveFloat = Annotated[float, annotated_types.Le(0)]

A float that must be less than or equal to zero.

NonNegativeFloat module-attribute

NonNegativeFloat = Annotated[float, annotated_types.Ge(0)]

A float that must be greater than or equal to zero.

StrictFloat module-attribute

StrictFloat = Annotated[float, Strict(True)]

A float that must be validated in strict mode.

FiniteFloat module-attribute

FiniteFloat = Annotated[float, AllowInfNan(False)]

A float that must be finite (not -inf, inf, or nan).

StrictBytes module-attribute

StrictBytes = Annotated[bytes, Strict()]

A bytes that must be validated in strict mode.

StrictStr module-attribute

StrictStr = Annotated[str, Strict()]

A string that must be validated in strict mode.

UUID1 module-attribute

UUID1 = Annotated[UUID, UuidVersion(1)]

A UUID1 annotated type.

UUID3 module-attribute

UUID3 = Annotated[UUID, UuidVersion(3)]

A UUID3 annotated type.

UUID4 module-attribute

UUID4 = Annotated[UUID, UuidVersion(4)]

A UUID4 annotated type.

UUID5 module-attribute

UUID5 = Annotated[UUID, UuidVersion(5)]

A UUID5 annotated type.

FilePath module-attribute

FilePath = Annotated[Path, PathType('file')]

A path that must point to a file.

DirectoryPath module-attribute

DirectoryPath = Annotated[Path, PathType('dir')]

A path that must point to a directory.

NewPath module-attribute

NewPath = Annotated[Path, PathType('new')]

A path for a new file or directory that must not already exist.

Strict dataclass

Bases: _fields.PydanticMetadata, BaseMetadata

A field metadata class to indicate that a field should be validated in strict mode.

Attributes:

Name	Type	Description
strict	bool	Whether to validate the field in strict mode.

Example

from typing_extensions import Annotated

from pydantic.types import Strict

StrictBool = Annotated[bool, Strict()]

AllowInfNan dataclass

Bases: _fields.PydanticMetadata

A field metadata class to indicate that a field should allow -inf, inf, and nan.

StringConstraints dataclass

Bases: annotated_types.GroupedMetadata

Apply constraints to str types.

Attributes:

Name	Type	Description
strip_whitespace	bool | None	Whether to strip whitespace from the string.
to_upper	bool | None	Whether to convert the string to uppercase.
to_lower	bool | None	Whether to convert the string to lowercase.
strict	bool | None	Whether to validate the string in strict mode.
min_length	int | None	The minimum length of the string.
max_length	int | None	The maximum length of the string.
pattern	str | None	A regex pattern that the string must match.

ImportString

A type that can be used to import a type from a string.

Example

from datetime import date
from typing import Type

from pydantic import BaseModel, ImportString


class Foo(BaseModel):
    call_date: ImportString[Type[date]]


foo = Foo(call_date="datetime.date")
assert foo.call_date(2021, 1, 1) == date(2021, 1, 1)

Json

A special type wrapper which loads JSON before parsing.

SecretStr

Bases: _SecretField[str]

A string that is displayed as ********** in reprs and can be used for passwords.

Example

from pydantic import BaseModel, SecretStr

class User(BaseModel):
    username: str
    password: SecretStr

user = User(username='scolvin', password='password1')

print(user)
#> username='scolvin' password=SecretStr('**********')
print(user.password.get_secret_value())
#> password1

SecretBytes

Bases: _SecretField[bytes]

A bytes that is displayed as ********** in reprs and can be used for passwords.

PaymentCardNumber

PaymentCardNumber(card_number)

Bases: str

Based on: https://en.wikipedia.org/wiki/Payment_card_number.

Source code in pydantic/types.py

def __init__(self, card_number: str):
    self.validate_digits(card_number)

    card_number = self.validate_luhn_check_digit(card_number)

    self.bin = card_number[:6]
    self.last4 = card_number[-4:]
    self.brand = self.validate_brand(card_number)

masked property

masked: str

Mask all but the last 4 digits of the card number.

Returns:

Type	Description
str	A masked card number string.

validate classmethod

validate(__input_value, _)

Validate the card number and return a PaymentCardNumber instance.

Source code in pydantic/types.py

@classmethod
def validate(cls, __input_value: str, _: core_schema.ValidationInfo) -> PaymentCardNumber:
    """Validate the card number and return a `PaymentCardNumber` instance."""
    return cls(__input_value)

validate_digits classmethod

validate_digits(card_number)

Validate that the card number is all digits.

Source code in pydantic/types.py

@classmethod
def validate_digits(cls, card_number: str) -> None:
    """Validate that the card number is all digits."""
    if not card_number.isdigit():
        raise PydanticCustomError('payment_card_number_digits', 'Card number is not all digits')

validate_luhn_check_digit classmethod

validate_luhn_check_digit(card_number)

Based on: https://en.wikipedia.org/wiki/Luhn_algorithm.

Source code in pydantic/types.py

@classmethod
def validate_luhn_check_digit(cls, card_number: str) -> str:
    """Based on: https://en.wikipedia.org/wiki/Luhn_algorithm."""
    sum_ = int(card_number[-1])
    length = len(card_number)
    parity = length % 2
    for i in range(length - 1):
        digit = int(card_number[i])
        if i % 2 == parity:
            digit *= 2
        if digit > 9:
            digit -= 9
        sum_ += digit
    valid = sum_ % 10 == 0
    if not valid:
        raise PydanticCustomError('payment_card_number_luhn', 'Card number is not luhn valid')
    return card_number

validate_brand staticmethod

validate_brand(card_number)

Validate length based on BIN for major brands: https://en.wikipedia.org/wiki/Payment_card_number#Issuer_identification_number_(IIN).

Source code in pydantic/types.py

@staticmethod
def validate_brand(card_number: str) -> PaymentCardBrand:
    """Validate length based on BIN for major brands:
    https://en.wikipedia.org/wiki/Payment_card_number#Issuer_identification_number_(IIN).
    """
    if card_number[0] == '4':
        brand = PaymentCardBrand.visa
    elif 51 <= int(card_number[:2]) <= 55:
        brand = PaymentCardBrand.mastercard
    elif card_number[:2] in {'34', '37'}:
        brand = PaymentCardBrand.amex
    else:
        brand = PaymentCardBrand.other

    required_length: None | int | str = None
    if brand in PaymentCardBrand.mastercard:
        required_length = 16
        valid = len(card_number) == required_length
    elif brand == PaymentCardBrand.visa:
        required_length = '13, 16 or 19'
        valid = len(card_number) in {13, 16, 19}
    elif brand == PaymentCardBrand.amex:
        required_length = 15
        valid = len(card_number) == required_length
    else:
        valid = True

    if not valid:
        raise PydanticCustomError(
            'payment_card_number_brand',
            'Length for a {brand} card must be {required_length}',
            {'brand': brand, 'required_length': required_length},
        )
    return brand

ByteSize

Bases: int

Converts a bytes string with units to the number of bytes.

human_readable

human_readable(decimal=False)

Converts a byte size to a human readable string.

Parameters:

Name	Type	Description	Default
decimal	bool	If True, use decimal units (e.g. 1000 bytes per KB). If False, use binary units (e.g. 1024 bytes per KiB).	False

Returns:

Type	Description
str	A human readable string representation of the byte size.

Source code in pydantic/types.py

def human_readable(self, decimal: bool = False) -> str:
    """Converts a byte size to a human readable string.

    Args:
        decimal: If True, use decimal units (e.g. 1000 bytes per KB). If False, use binary units
            (e.g. 1024 bytes per KiB).

    Returns:
        A human readable string representation of the byte size.
    """
    if decimal:
        divisor = 1000
        units = 'B', 'KB', 'MB', 'GB', 'TB', 'PB'
        final_unit = 'EB'
    else:
        divisor = 1024
        units = 'B', 'KiB', 'MiB', 'GiB', 'TiB', 'PiB'
        final_unit = 'EiB'

    num = float(self)
    for unit in units:
        if abs(num) < divisor:
            if unit == 'B':
                return f'{num:0.0f}{unit}'
            else:
                return f'{num:0.1f}{unit}'
        num /= divisor

    return f'{num:0.1f}{final_unit}'

to

to(unit)

Converts a byte size to another unit.

Parameters:

Name	Type	Description	Default
unit	str	The unit to convert to. Must be one of the following: B, KB, MB, GB, TB, PB, EiB, KiB, MiB, GiB, TiB, PiB, EiB.	required

Returns:

Type	Description
float	The byte size in the new unit.

Source code in pydantic/types.py

def to(self, unit: str) -> float:
    """Converts a byte size to another unit.

    Args:
        unit: The unit to convert to. Must be one of the following: B, KB, MB, GB, TB, PB, EiB,
            KiB, MiB, GiB, TiB, PiB, EiB.

    Returns:
        The byte size in the new unit.
    """
    try:
        unit_div = BYTE_SIZES[unit.lower()]
    except KeyError:
        raise PydanticCustomError('byte_size_unit', 'Could not interpret byte unit: {unit}', {'unit': unit})

    return self / unit_div

PastDate

A date in the past.

FutureDate

A date in the future.

AwareDatetime

A datetime that requires timezone info.

NaiveDatetime

A datetime that doesn't require timezone info.

PastDatetime

A datetime that must be in the past.

FutureDatetime

A datetime that must be in the future.

EncoderProtocol

Bases: Protocol

Protocol for encoding and decoding data to and from bytes.

decode classmethod

decode(data)

Decode the data using the encoder.

Parameters:

Name	Type	Description	Default
data	bytes	The data to decode.	required

Returns:

Type	Description
bytes	The decoded data.

Source code in pydantic/types.py

@classmethod
def decode(cls, data: bytes) -> bytes:
    """Decode the data using the encoder.

    Args:
        data: The data to decode.

    Returns:
        The decoded data.
    """
    ...

encode classmethod

encode(value)

Encode the data using the encoder.

Parameters:

Name	Type	Description	Default
value	bytes	The data to encode.	required

Returns:

Type	Description
bytes	The encoded data.

Source code in pydantic/types.py

@classmethod
def encode(cls, value: bytes) -> bytes:
    """Encode the data using the encoder.

    Args:
        value: The data to encode.

    Returns:
        The encoded data.
    """
    ...

get_json_format classmethod

get_json_format()

Get the JSON format for the encoded data.

Returns:

Type	Description
str	The JSON format for the encoded data.

Source code in pydantic/types.py

@classmethod
def get_json_format(cls) -> str:
    """Get the JSON format for the encoded data.

    Returns:
        The JSON format for the encoded data.
    """
    ...

Base64Encoder

Bases: EncoderProtocol

Base64 encoder.

decode classmethod

decode(data)

Decode the data from base64 encoded bytes to original bytes data.

Parameters:

Name	Type	Description	Default
data	bytes	The data to decode.	required

Returns:

Type	Description
bytes	The decoded data.

Source code in pydantic/types.py

@classmethod
def decode(cls, data: bytes) -> bytes:
    """Decode the data from base64 encoded bytes to original bytes data.

    Args:
        data: The data to decode.

    Returns:
        The decoded data.
    """
    try:
        return base64.decodebytes(data)
    except ValueError as e:
        raise PydanticCustomError('base64_decode', "Base64 decoding error: '{error}'", {'error': str(e)})

encode classmethod

encode(value)

Encode the data from bytes to a base64 encoded bytes.

Parameters:

Name	Type	Description	Default
value	bytes	The data to encode.	required

Returns:

Type	Description
bytes	The encoded data.

Source code in pydantic/types.py

@classmethod
def encode(cls, value: bytes) -> bytes:
    """Encode the data from bytes to a base64 encoded bytes.

    Args:
        value: The data to encode.

    Returns:
        The encoded data.
    """
    return base64.encodebytes(value)

get_json_format classmethod

get_json_format()

Get the JSON format for the encoded data.

Returns:

Type	Description
Literal['base64']	The JSON format for the encoded data.

Source code in pydantic/types.py

@classmethod
def get_json_format(cls) -> Literal['base64']:
    """Get the JSON format for the encoded data.

    Returns:
        The JSON format for the encoded data.
    """
    return 'base64'

EncodedBytes dataclass

A bytes type that is encoded and decoded using the specified encoder.

decode

decode(data, _)

Decode the data using the specified encoder.

Parameters:

Name	Type	Description	Default
data	bytes	The data to decode.	required

Returns:

Type	Description
bytes	The decoded data.

Source code in pydantic/types.py

def decode(self, data: bytes, _: core_schema.ValidationInfo) -> bytes:
    """Decode the data using the specified encoder.

    Args:
        data: The data to decode.

    Returns:
        The decoded data.
    """
    return self.encoder.decode(data)

encode

encode(value)

Encode the data using the specified encoder.

Parameters:

Name	Type	Description	Default
value	bytes	The data to encode.	required

Returns:

Type	Description
bytes	The encoded data.

Source code in pydantic/types.py

def encode(self, value: bytes) -> bytes:
    """Encode the data using the specified encoder.

    Args:
        value: The data to encode.

    Returns:
        The encoded data.
    """
    return self.encoder.encode(value)

EncodedStr

Bases: EncodedBytes

A str type that is encoded and decoded using the specified encoder.

decode_str

decode_str(data, _)

Decode the data using the specified encoder.

Parameters:

Name	Type	Description	Default
data	bytes	The data to decode.	required

Returns:

Type	Description
str	The decoded data.

Source code in pydantic/types.py

def decode_str(self, data: bytes, _: core_schema.ValidationInfo) -> str:
    """Decode the data using the specified encoder.

    Args:
        data: The data to decode.

    Returns:
        The decoded data.
    """
    return data.decode()

encode_str

encode_str(value)

Encode the data using the specified encoder.

Parameters:

Name	Type	Description	Default
value	str	The data to encode.	required

Returns:

Type	Description
str	The encoded data.

Source code in pydantic/types.py

def encode_str(self, value: str) -> str:
    """Encode the data using the specified encoder.

    Args:
        value: The data to encode.

    Returns:
        The encoded data.
    """
    return super().encode(value=value.encode()).decode()

GetPydanticSchema dataclass

A convenience class for creating an annotation that provides pydantic custom type hooks.

This class is intended to eliminate the need to create a custom "marker" which defines the __get_pydantic_core_schema__ and __get_pydantic_json_schema__ custom hook methods.

For example, to have a field treated by type checkers as int, but by pydantic as Any, you can do:

from typing import Any

from typing_extensions import Annotated

from pydantic import BaseModel, GetPydanticSchema

HandleAsAny = GetPydanticSchema(lambda _s, h: h(Any))

class Model(BaseModel):
    x: Annotated[int, HandleAsAny]  # pydantic sees `x: Any`

print(repr(Model(x='abc').x))
#> 'abc'

conint

conint(
    *,
    strict=None,
    gt=None,
    ge=None,
    lt=None,
    le=None,
    multiple_of=None
)

A wrapper around int that allows for additional constraints.

Parameters:

Name	Type	Description	Default
strict	bool | None	Whether to validate the integer in strict mode. Defaults to None.	None
gt	int | None	The value must be greater than this.	None
ge	int | None	The value must be greater than or equal to this.	None
lt	int | None	The value must be less than this.	None
le	int | None	The value must be less than or equal to this.	None
multiple_of	int | None	The value must be a multiple of this.	None

Returns:

Type	Description
type[int]	The wrapped integer type.

Source code in pydantic/types.py

def conint(
    *,
    strict: bool | None = None,
    gt: int | None = None,
    ge: int | None = None,
    lt: int | None = None,
    le: int | None = None,
    multiple_of: int | None = None,
) -> type[int]:
    """A wrapper around `int` that allows for additional constraints.

    Args:
        strict: Whether to validate the integer in strict mode. Defaults to `None`.
        gt: The value must be greater than this.
        ge: The value must be greater than or equal to this.
        lt: The value must be less than this.
        le: The value must be less than or equal to this.
        multiple_of: The value must be a multiple of this.

    Returns:
        The wrapped integer type.
    """
    return Annotated[  # type: ignore[return-value]
        int,
        Strict(strict) if strict is not None else None,
        annotated_types.Interval(gt=gt, ge=ge, lt=lt, le=le),
        annotated_types.MultipleOf(multiple_of) if multiple_of is not None else None,
    ]

confloat

confloat(
    *,
    strict=None,
    gt=None,
    ge=None,
    lt=None,
    le=None,
    multiple_of=None,
    allow_inf_nan=None
)

A wrapper around float that allows for additional constraints.

Parameters:

Name	Type	Description	Default
strict	bool | None	Whether to validate the float in strict mode.	None
gt	float | None	The value must be greater than this.	None
ge	float | None	The value must be greater than or equal to this.	None
lt	float | None	The value must be less than this.	None
le	float | None	The value must be less than or equal to this.	None
multiple_of	float | None	The value must be a multiple of this.	None
allow_inf_nan	bool | None	Whether to allow -inf, inf, and nan.	None

Returns:

Type	Description
type[float]	The wrapped float type.

Source code in pydantic/types.py

def confloat(
    *,
    strict: bool | None = None,
    gt: float | None = None,
    ge: float | None = None,
    lt: float | None = None,
    le: float | None = None,
    multiple_of: float | None = None,
    allow_inf_nan: bool | None = None,
) -> type[float]:
    """A wrapper around `float` that allows for additional constraints.

    Args:
        strict: Whether to validate the float in strict mode.
        gt: The value must be greater than this.
        ge: The value must be greater than or equal to this.
        lt: The value must be less than this.
        le: The value must be less than or equal to this.
        multiple_of: The value must be a multiple of this.
        allow_inf_nan: Whether to allow `-inf`, `inf`, and `nan`.

    Returns:
        The wrapped float type.
    """
    return Annotated[  # type: ignore[return-value]
        float,
        Strict(strict) if strict is not None else None,
        annotated_types.Interval(gt=gt, ge=ge, lt=lt, le=le),
        annotated_types.MultipleOf(multiple_of) if multiple_of is not None else None,
        AllowInfNan(allow_inf_nan) if allow_inf_nan is not None else None,
    ]

conbytes

conbytes(*, min_length=None, max_length=None, strict=None)

A wrapper around bytes that allows for additional constraints.

Parameters:

Name	Type	Description	Default
min_length	int | None	The minimum length of the bytes.	None
max_length	int | None	The maximum length of the bytes.	None
strict	bool | None	Whether to validate the bytes in strict mode.	None

Returns:

Type	Description
type[bytes]	The wrapped bytes type.

Source code in pydantic/types.py

def conbytes(
    *,
    min_length: int | None = None,
    max_length: int | None = None,
    strict: bool | None = None,
) -> type[bytes]:
    """A wrapper around `bytes` that allows for additional constraints.

    Args:
        min_length: The minimum length of the bytes.
        max_length: The maximum length of the bytes.
        strict: Whether to validate the bytes in strict mode.

    Returns:
        The wrapped bytes type.
    """
    return Annotated[  # type: ignore[return-value]
        bytes,
        Strict(strict) if strict is not None else None,
        annotated_types.Len(min_length or 0, max_length),
    ]

constr

constr(
    *,
    strip_whitespace=None,
    to_upper=None,
    to_lower=None,
    strict=None,
    min_length=None,
    max_length=None,
    pattern=None
)

A wrapper around str that allows for additional constraints.

Parameters:

Name	Type	Description	Default
strip_whitespace	bool | None	Whether to strip whitespace from the string.	None
to_upper	bool | None	Whether to convert the string to uppercase.	None
to_lower	bool | None	Whether to convert the string to lowercase.	None
strict	bool | None	Whether to validate the string in strict mode.	None
min_length	int | None	The minimum length of the string.	None
max_length	int | None	The maximum length of the string.	None
pattern	str | None	A regex pattern that the string must match.	None

Returns:

Type	Description
type[str]	The wrapped string type.

Source code in pydantic/types.py

def constr(
    *,
    strip_whitespace: bool | None = None,
    to_upper: bool | None = None,
    to_lower: bool | None = None,
    strict: bool | None = None,
    min_length: int | None = None,
    max_length: int | None = None,
    pattern: str | None = None,
) -> type[str]:
    """A wrapper around `str` that allows for additional constraints.

    Args:
        strip_whitespace: Whether to strip whitespace from the string.
        to_upper: Whether to convert the string to uppercase.
        to_lower: Whether to convert the string to lowercase.
        strict: Whether to validate the string in strict mode.
        min_length: The minimum length of the string.
        max_length: The maximum length of the string.
        pattern: A regex pattern that the string must match.

    Returns:
        The wrapped string type.
    """
    return Annotated[  # type: ignore[return-value]
        str,
        StringConstraints(
            strip_whitespace=strip_whitespace,
            to_upper=to_upper,
            to_lower=to_lower,
            strict=strict,
            min_length=min_length,
            max_length=max_length,
            pattern=pattern,
        ),
    ]

conset

conset(item_type, *, min_length=None, max_length=None)

A wrapper around typing.Set that allows for additional constraints.

Parameters:

Name	Type	Description	Default
item_type	type[HashableItemType]	The type of the items in the set.	required
min_length	int | None	The minimum length of the set.	None
max_length	int | None	The maximum length of the set.	None

Returns:

Type	Description
type[set[HashableItemType]]	The wrapped set type.

Source code in pydantic/types.py

def conset(
    item_type: type[HashableItemType], *, min_length: int | None = None, max_length: int | None = None
) -> type[set[HashableItemType]]:
    """A wrapper around `typing.Set` that allows for additional constraints.

    Args:
        item_type: The type of the items in the set.
        min_length: The minimum length of the set.
        max_length: The maximum length of the set.

    Returns:
        The wrapped set type.
    """
    return Annotated[  # type: ignore[return-value]
        Set[item_type], annotated_types.Len(min_length or 0, max_length)  # type: ignore[valid-type]
    ]

confrozenset

confrozenset(
    item_type, *, min_length=None, max_length=None
)

A wrapper around typing.FrozenSet that allows for additional constraints.

Parameters:

Name	Type	Description	Default
item_type	type[HashableItemType]	The type of the items in the frozenset.	required
min_length	int | None	The minimum length of the frozenset.	None
max_length	int | None	The maximum length of the frozenset.	None

Returns:

Type	Description
type[frozenset[HashableItemType]]	The wrapped frozenset type.

Source code in pydantic/types.py

def confrozenset(
    item_type: type[HashableItemType], *, min_length: int | None = None, max_length: int | None = None
) -> type[frozenset[HashableItemType]]:
    """A wrapper around `typing.FrozenSet` that allows for additional constraints.

    Args:
        item_type: The type of the items in the frozenset.
        min_length: The minimum length of the frozenset.
        max_length: The maximum length of the frozenset.

    Returns:
        The wrapped frozenset type.
    """
    return Annotated[  # type: ignore[return-value]
        FrozenSet[item_type],  # type: ignore[valid-type]
        annotated_types.Len(min_length or 0, max_length),
    ]

conlist

conlist(
    item_type,
    *,
    min_length=None,
    max_length=None,
    unique_items=None
)

A wrapper around typing.List that adds validation.

Parameters:

Name	Type	Description	Default
item_type	type[AnyItemType]	The type of the items in the list.	required
min_length	int | None	The minimum length of the list. Defaults to None.	None
max_length	int | None	The maximum length of the list. Defaults to None.	None
unique_items	bool | None	Whether the items in the list must be unique. Defaults to None.	None

Returns:

Type	Description
type[list[AnyItemType]]	The wrapped list type.

Source code in pydantic/types.py

def conlist(
    item_type: type[AnyItemType],
    *,
    min_length: int | None = None,
    max_length: int | None = None,
    unique_items: bool | None = None,
) -> type[list[AnyItemType]]:
    """A wrapper around typing.List that adds validation.

    Args:
        item_type: The type of the items in the list.
        min_length: The minimum length of the list. Defaults to None.
        max_length: The maximum length of the list. Defaults to None.
        unique_items: Whether the items in the list must be unique. Defaults to None.

    Returns:
        The wrapped list type.
    """
    if unique_items is not None:
        raise PydanticUserError(
            (
                '`unique_items` is removed, use `Set` instead'
                '(this feature is discussed in https://github.com/pydantic/pydantic-core/issues/296)'
            ),
            code='removed-kwargs',
        )
    return Annotated[  # type: ignore[return-value]
        List[item_type],  # type: ignore[valid-type]
        annotated_types.Len(min_length or 0, max_length),
    ]

condecimal

condecimal(
    *,
    strict=None,
    gt=None,
    ge=None,
    lt=None,
    le=None,
    multiple_of=None,
    max_digits=None,
    decimal_places=None,
    allow_inf_nan=None
)

A wrapper around Decimal that adds validation.

Parameters:

Name	Type	Description	Default
strict	bool | None	Whether to validate the value in strict mode. Defaults to None.	None
gt	int | Decimal | None	The value must be greater than this. Defaults to None.	None
ge	int | Decimal | None	The value must be greater than or equal to this. Defaults to None.	None
lt	int | Decimal | None	The value must be less than this. Defaults to None.	None
le	int | Decimal | None	The value must be less than or equal to this. Defaults to None.	None
multiple_of	int | Decimal | None	The value must be a multiple of this. Defaults to None.	None
max_digits	int | None	The maximum number of digits. Defaults to None.	None
decimal_places	int | None	The number of decimal places. Defaults to None.	None
allow_inf_nan	bool | None	Whether to allow infinity and NaN. Defaults to None.	None

Source code in pydantic/types.py

def condecimal(
    *,
    strict: bool | None = None,
    gt: int | Decimal | None = None,
    ge: int | Decimal | None = None,
    lt: int | Decimal | None = None,
    le: int | Decimal | None = None,
    multiple_of: int | Decimal | None = None,
    max_digits: int | None = None,
    decimal_places: int | None = None,
    allow_inf_nan: bool | None = None,
) -> type[Decimal]:
    """A wrapper around Decimal that adds validation.

    Args:
        strict: Whether to validate the value in strict mode. Defaults to `None`.
        gt: The value must be greater than this. Defaults to `None`.
        ge: The value must be greater than or equal to this. Defaults to `None`.
        lt: The value must be less than this. Defaults to `None`.
        le: The value must be less than or equal to this. Defaults to `None`.
        multiple_of: The value must be a multiple of this. Defaults to `None`.
        max_digits: The maximum number of digits. Defaults to `None`.
        decimal_places: The number of decimal places. Defaults to `None`.
        allow_inf_nan: Whether to allow infinity and NaN. Defaults to `None`.
    """
    return Annotated[  # type: ignore[return-value]
        Decimal,
        Strict(strict) if strict is not None else None,
        annotated_types.Interval(gt=gt, ge=ge, lt=lt, le=le),
        annotated_types.MultipleOf(multiple_of) if multiple_of is not None else None,
        _fields.PydanticGeneralMetadata(max_digits=max_digits, decimal_places=decimal_places),
        AllowInfNan(allow_inf_nan) if allow_inf_nan is not None else None,
    ]

condate

condate(*, strict=None, gt=None, ge=None, lt=None, le=None)

A wrapper for date that adds constraints.

Parameters:

Name	Type	Description	Default
strict	bool | None	Whether to validate the date value in strict mode. Defaults to None.	None
gt	date | None	The value must be greater than this. Defaults to None.	None
ge	date | None	The value must be greater than or equal to this. Defaults to None.	None
lt	date | None	The value must be less than this. Defaults to None.	None
le	date | None	The value must be less than or equal to this. Defaults to None.	None

Returns:

Type	Description
type[date]	A date type with the specified constraints.

Source code in pydantic/types.py

def condate(
    *,
    strict: bool | None = None,
    gt: date | None = None,
    ge: date | None = None,
    lt: date | None = None,
    le: date | None = None,
) -> type[date]:
    """A wrapper for date that adds constraints.

    Args:
        strict: Whether to validate the date value in strict mode. Defaults to `None`.
        gt: The value must be greater than this. Defaults to `None`.
        ge: The value must be greater than or equal to this. Defaults to `None`.
        lt: The value must be less than this. Defaults to `None`.
        le: The value must be less than or equal to this. Defaults to `None`.

    Returns:
        A date type with the specified constraints.
    """
    return Annotated[  # type: ignore[return-value]
        date,
        Strict(strict) if strict is not None else None,
        annotated_types.Interval(gt=gt, ge=ge, lt=lt, le=le),
    ]