Your IP : 3.15.237.229
import abc
import math
import re
import warnings
from datetime import date
from decimal import Decimal, InvalidOperation
from enum import Enum
from pathlib import Path
from types import new_class
from typing import (
TYPE_CHECKING,
Any,
Callable,
ClassVar,
Dict,
FrozenSet,
List,
Optional,
Pattern,
Set,
Tuple,
Type,
TypeVar,
Union,
cast,
overload,
)
from uuid import UUID
from weakref import WeakSet
from . import errors
from .datetime_parse import parse_date
from .utils import import_string, update_not_none
from .validators import (
bytes_validator,
constr_length_validator,
constr_lower,
constr_strip_whitespace,
constr_upper,
decimal_validator,
float_finite_validator,
float_validator,
frozenset_validator,
int_validator,
list_validator,
number_multiple_validator,
number_size_validator,
path_exists_validator,
path_validator,
set_validator,
str_validator,
strict_bytes_validator,
strict_float_validator,
strict_int_validator,
strict_str_validator,
)
__all__ = [
'NoneStr',
'NoneBytes',
'StrBytes',
'NoneStrBytes',
'StrictStr',
'ConstrainedBytes',
'conbytes',
'ConstrainedList',
'conlist',
'ConstrainedSet',
'conset',
'ConstrainedFrozenSet',
'confrozenset',
'ConstrainedStr',
'constr',
'PyObject',
'ConstrainedInt',
'conint',
'PositiveInt',
'NegativeInt',
'NonNegativeInt',
'NonPositiveInt',
'ConstrainedFloat',
'confloat',
'PositiveFloat',
'NegativeFloat',
'NonNegativeFloat',
'NonPositiveFloat',
'FiniteFloat',
'ConstrainedDecimal',
'condecimal',
'UUID1',
'UUID3',
'UUID4',
'UUID5',
'FilePath',
'DirectoryPath',
'Json',
'JsonWrapper',
'SecretField',
'SecretStr',
'SecretBytes',
'StrictBool',
'StrictBytes',
'StrictInt',
'StrictFloat',
'PaymentCardNumber',
'ByteSize',
'PastDate',
'FutureDate',
'ConstrainedDate',
'condate',
]
NoneStr = Optional[str]
NoneBytes = Optional[bytes]
StrBytes = Union[str, bytes]
NoneStrBytes = Optional[StrBytes]
OptionalInt = Optional[int]
OptionalIntFloat = Union[OptionalInt, float]
OptionalIntFloatDecimal = Union[OptionalIntFloat, Decimal]
OptionalDate = Optional[date]
StrIntFloat = Union[str, int, float]
if TYPE_CHECKING:
from typing_extensions import Annotated
from .dataclasses import Dataclass
from .main import BaseModel
from .typing import CallableGenerator
ModelOrDc = Type[Union[BaseModel, Dataclass]]
T = TypeVar('T')
_DEFINED_TYPES: 'WeakSet[type]' = WeakSet()
@overload
def _registered(typ: Type[T]) -> Type[T]:
pass
@overload
def _registered(typ: 'ConstrainedNumberMeta') -> 'ConstrainedNumberMeta':
pass
def _registered(typ: Union[Type[T], 'ConstrainedNumberMeta']) -> Union[Type[T], 'ConstrainedNumberMeta']:
# In order to generate valid examples of constrained types, Hypothesis needs
# to inspect the type object - so we keep a weakref to each contype object
# until it can be registered. When (or if) our Hypothesis plugin is loaded,
# it monkeypatches this function.
# If Hypothesis is never used, the total effect is to keep a weak reference
# which has minimal memory usage and doesn't even affect garbage collection.
_DEFINED_TYPES.add(typ)
return typ
class ConstrainedNumberMeta(type):
def __new__(cls, name: str, bases: Any, dct: Dict[str, Any]) -> 'ConstrainedInt': # type: ignore
new_cls = cast('ConstrainedInt', type.__new__(cls, name, bases, dct))
if new_cls.gt is not None and new_cls.ge is not None:
raise errors.ConfigError('bounds gt and ge cannot be specified at the same time')
if new_cls.lt is not None and new_cls.le is not None:
raise errors.ConfigError('bounds lt and le cannot be specified at the same time')
return _registered(new_cls) # type: ignore
# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ BOOLEAN TYPES ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
if TYPE_CHECKING:
StrictBool = bool
else:
class StrictBool(int):
"""
StrictBool to allow for bools which are not type-coerced.
"""
@classmethod
def __modify_schema__(cls, field_schema: Dict[str, Any]) -> None:
field_schema.update(type='boolean')
@classmethod
def __get_validators__(cls) -> 'CallableGenerator':
yield cls.validate
@classmethod
def validate(cls, value: Any) -> bool:
"""
Ensure that we only allow bools.
"""
if isinstance(value, bool):
return value
raise errors.StrictBoolError()
# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ INTEGER TYPES ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
class ConstrainedInt(int, metaclass=ConstrainedNumberMeta):
strict: bool = False
gt: OptionalInt = None
ge: OptionalInt = None
lt: OptionalInt = None
le: OptionalInt = None
multiple_of: OptionalInt = None
@classmethod
def __modify_schema__(cls, field_schema: Dict[str, Any]) -> None:
update_not_none(
field_schema,
exclusiveMinimum=cls.gt,
exclusiveMaximum=cls.lt,
minimum=cls.ge,
maximum=cls.le,
multipleOf=cls.multiple_of,
)
@classmethod
def __get_validators__(cls) -> 'CallableGenerator':
yield strict_int_validator if cls.strict else int_validator
yield number_size_validator
yield number_multiple_validator
def conint(
*,
strict: bool = False,
gt: Optional[int] = None,
ge: Optional[int] = None,
lt: Optional[int] = None,
le: Optional[int] = None,
multiple_of: Optional[int] = None,
) -> Type[int]:
# use kwargs then define conf in a dict to aid with IDE type hinting
namespace = dict(strict=strict, gt=gt, ge=ge, lt=lt, le=le, multiple_of=multiple_of)
return type('ConstrainedIntValue', (ConstrainedInt,), namespace)
if TYPE_CHECKING:
PositiveInt = int
NegativeInt = int
NonPositiveInt = int
NonNegativeInt = int
StrictInt = int
else:
class PositiveInt(ConstrainedInt):
gt = 0
class NegativeInt(ConstrainedInt):
lt = 0
class NonPositiveInt(ConstrainedInt):
le = 0
class NonNegativeInt(ConstrainedInt):
ge = 0
class StrictInt(ConstrainedInt):
strict = True
# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ FLOAT TYPES ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
class ConstrainedFloat(float, metaclass=ConstrainedNumberMeta):
strict: bool = False
gt: OptionalIntFloat = None
ge: OptionalIntFloat = None
lt: OptionalIntFloat = None
le: OptionalIntFloat = None
multiple_of: OptionalIntFloat = None
allow_inf_nan: Optional[bool] = None
@classmethod
def __modify_schema__(cls, field_schema: Dict[str, Any]) -> None:
update_not_none(
field_schema,
exclusiveMinimum=cls.gt,
exclusiveMaximum=cls.lt,
minimum=cls.ge,
maximum=cls.le,
multipleOf=cls.multiple_of,
)
# Modify constraints to account for differences between IEEE floats and JSON
if field_schema.get('exclusiveMinimum') == -math.inf:
del field_schema['exclusiveMinimum']
if field_schema.get('minimum') == -math.inf:
del field_schema['minimum']
if field_schema.get('exclusiveMaximum') == math.inf:
del field_schema['exclusiveMaximum']
if field_schema.get('maximum') == math.inf:
del field_schema['maximum']
@classmethod
def __get_validators__(cls) -> 'CallableGenerator':
yield strict_float_validator if cls.strict else float_validator
yield number_size_validator
yield number_multiple_validator
yield float_finite_validator
def confloat(
*,
strict: bool = False,
gt: float = None,
ge: float = None,
lt: float = None,
le: float = None,
multiple_of: float = None,
allow_inf_nan: Optional[bool] = None,
) -> Type[float]:
# use kwargs then define conf in a dict to aid with IDE type hinting
namespace = dict(strict=strict, gt=gt, ge=ge, lt=lt, le=le, multiple_of=multiple_of, allow_inf_nan=allow_inf_nan)
return type('ConstrainedFloatValue', (ConstrainedFloat,), namespace)
if TYPE_CHECKING:
PositiveFloat = float
NegativeFloat = float
NonPositiveFloat = float
NonNegativeFloat = float
StrictFloat = float
FiniteFloat = float
else:
class PositiveFloat(ConstrainedFloat):
gt = 0
class NegativeFloat(ConstrainedFloat):
lt = 0
class NonPositiveFloat(ConstrainedFloat):
le = 0
class NonNegativeFloat(ConstrainedFloat):
ge = 0
class StrictFloat(ConstrainedFloat):
strict = True
class FiniteFloat(ConstrainedFloat):
allow_inf_nan = False
# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ BYTES TYPES ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
class ConstrainedBytes(bytes):
strip_whitespace = False
to_upper = False
to_lower = False
min_length: OptionalInt = None
max_length: OptionalInt = None
strict: bool = False
@classmethod
def __modify_schema__(cls, field_schema: Dict[str, Any]) -> None:
update_not_none(field_schema, minLength=cls.min_length, maxLength=cls.max_length)
@classmethod
def __get_validators__(cls) -> 'CallableGenerator':
yield strict_bytes_validator if cls.strict else bytes_validator
yield constr_strip_whitespace
yield constr_upper
yield constr_lower
yield constr_length_validator
def conbytes(
*,
strip_whitespace: bool = False,
to_upper: bool = False,
to_lower: bool = False,
min_length: Optional[int] = None,
max_length: Optional[int] = None,
strict: bool = False,
) -> Type[bytes]:
# use kwargs then define conf in a dict to aid with IDE type hinting
namespace = dict(
strip_whitespace=strip_whitespace,
to_upper=to_upper,
to_lower=to_lower,
min_length=min_length,
max_length=max_length,
strict=strict,
)
return _registered(type('ConstrainedBytesValue', (ConstrainedBytes,), namespace))
if TYPE_CHECKING:
StrictBytes = bytes
else:
class StrictBytes(ConstrainedBytes):
strict = True
# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ STRING TYPES ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
class ConstrainedStr(str):
strip_whitespace = False
to_upper = False
to_lower = False
min_length: OptionalInt = None
max_length: OptionalInt = None
curtail_length: OptionalInt = None
regex: Optional[Union[str, Pattern[str]]] = None
strict = False
@classmethod
def __modify_schema__(cls, field_schema: Dict[str, Any]) -> None:
update_not_none(
field_schema,
minLength=cls.min_length,
maxLength=cls.max_length,
pattern=cls.regex and cls._get_pattern(cls.regex),
)
@classmethod
def __get_validators__(cls) -> 'CallableGenerator':
yield strict_str_validator if cls.strict else str_validator
yield constr_strip_whitespace
yield constr_upper
yield constr_lower
yield constr_length_validator
yield cls.validate
@classmethod
def validate(cls, value: Union[str]) -> Union[str]:
if cls.curtail_length and len(value) > cls.curtail_length:
value = value[: cls.curtail_length]
if cls.regex:
if not re.match(cls.regex, value):
raise errors.StrRegexError(pattern=cls._get_pattern(cls.regex))
return value
@staticmethod
def _get_pattern(regex: Union[str, Pattern[str]]) -> str:
return regex if isinstance(regex, str) else regex.pattern
def constr(
*,
strip_whitespace: bool = False,
to_upper: bool = False,
to_lower: bool = False,
strict: bool = False,
min_length: Optional[int] = None,
max_length: Optional[int] = None,
curtail_length: Optional[int] = None,
regex: Optional[str] = None,
) -> Type[str]:
# use kwargs then define conf in a dict to aid with IDE type hinting
namespace = dict(
strip_whitespace=strip_whitespace,
to_upper=to_upper,
to_lower=to_lower,
strict=strict,
min_length=min_length,
max_length=max_length,
curtail_length=curtail_length,
regex=regex and re.compile(regex),
)
return _registered(type('ConstrainedStrValue', (ConstrainedStr,), namespace))
if TYPE_CHECKING:
StrictStr = str
else:
class StrictStr(ConstrainedStr):
strict = True
# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ SET TYPES ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# This types superclass should be Set[T], but cython chokes on that...
class ConstrainedSet(set): # type: ignore
# Needed for pydantic to detect that this is a set
__origin__ = set
__args__: Set[Type[T]] # type: ignore
min_items: Optional[int] = None
max_items: Optional[int] = None
item_type: Type[T] # type: ignore
@classmethod
def __get_validators__(cls) -> 'CallableGenerator':
yield cls.set_length_validator
@classmethod
def __modify_schema__(cls, field_schema: Dict[str, Any]) -> None:
update_not_none(field_schema, minItems=cls.min_items, maxItems=cls.max_items)
@classmethod
def set_length_validator(cls, v: 'Optional[Set[T]]') -> 'Optional[Set[T]]':
if v is None:
return None
v = set_validator(v)
v_len = len(v)
if cls.min_items is not None and v_len < cls.min_items:
raise errors.SetMinLengthError(limit_value=cls.min_items)
if cls.max_items is not None and v_len > cls.max_items:
raise errors.SetMaxLengthError(limit_value=cls.max_items)
return v
def conset(item_type: Type[T], *, min_items: Optional[int] = None, max_items: Optional[int] = None) -> Type[Set[T]]:
# __args__ is needed to conform to typing generics api
namespace = {'min_items': min_items, 'max_items': max_items, 'item_type': item_type, '__args__': [item_type]}
# We use new_class to be able to deal with Generic types
return new_class('ConstrainedSetValue', (ConstrainedSet,), {}, lambda ns: ns.update(namespace))
# This types superclass should be FrozenSet[T], but cython chokes on that...
class ConstrainedFrozenSet(frozenset): # type: ignore
# Needed for pydantic to detect that this is a set
__origin__ = frozenset
__args__: FrozenSet[Type[T]] # type: ignore
min_items: Optional[int] = None
max_items: Optional[int] = None
item_type: Type[T] # type: ignore
@classmethod
def __get_validators__(cls) -> 'CallableGenerator':
yield cls.frozenset_length_validator
@classmethod
def __modify_schema__(cls, field_schema: Dict[str, Any]) -> None:
update_not_none(field_schema, minItems=cls.min_items, maxItems=cls.max_items)
@classmethod
def frozenset_length_validator(cls, v: 'Optional[FrozenSet[T]]') -> 'Optional[FrozenSet[T]]':
if v is None:
return None
v = frozenset_validator(v)
v_len = len(v)
if cls.min_items is not None and v_len < cls.min_items:
raise errors.FrozenSetMinLengthError(limit_value=cls.min_items)
if cls.max_items is not None and v_len > cls.max_items:
raise errors.FrozenSetMaxLengthError(limit_value=cls.max_items)
return v
def confrozenset(
item_type: Type[T], *, min_items: Optional[int] = None, max_items: Optional[int] = None
) -> Type[FrozenSet[T]]:
# __args__ is needed to conform to typing generics api
namespace = {'min_items': min_items, 'max_items': max_items, 'item_type': item_type, '__args__': [item_type]}
# We use new_class to be able to deal with Generic types
return new_class('ConstrainedFrozenSetValue', (ConstrainedFrozenSet,), {}, lambda ns: ns.update(namespace))
# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ LIST TYPES ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# This types superclass should be List[T], but cython chokes on that...
class ConstrainedList(list): # type: ignore
# Needed for pydantic to detect that this is a list
__origin__ = list
__args__: Tuple[Type[T], ...] # type: ignore
min_items: Optional[int] = None
max_items: Optional[int] = None
unique_items: Optional[bool] = None
item_type: Type[T] # type: ignore
@classmethod
def __get_validators__(cls) -> 'CallableGenerator':
yield cls.list_length_validator
if cls.unique_items:
yield cls.unique_items_validator
@classmethod
def __modify_schema__(cls, field_schema: Dict[str, Any]) -> None:
update_not_none(field_schema, minItems=cls.min_items, maxItems=cls.max_items, uniqueItems=cls.unique_items)
@classmethod
def list_length_validator(cls, v: 'Optional[List[T]]') -> 'Optional[List[T]]':
if v is None:
return None
v = list_validator(v)
v_len = len(v)
if cls.min_items is not None and v_len < cls.min_items:
raise errors.ListMinLengthError(limit_value=cls.min_items)
if cls.max_items is not None and v_len > cls.max_items:
raise errors.ListMaxLengthError(limit_value=cls.max_items)
return v
@classmethod
def unique_items_validator(cls, v: 'Optional[List[T]]') -> 'Optional[List[T]]':
if v is None:
return None
for i, value in enumerate(v, start=1):
if value in v[i:]:
raise errors.ListUniqueItemsError()
return v
def conlist(
item_type: Type[T], *, min_items: Optional[int] = None, max_items: Optional[int] = None, unique_items: bool = None
) -> Type[List[T]]:
# __args__ is needed to conform to typing generics api
namespace = dict(
min_items=min_items, max_items=max_items, unique_items=unique_items, item_type=item_type, __args__=(item_type,)
)
# We use new_class to be able to deal with Generic types
return new_class('ConstrainedListValue', (ConstrainedList,), {}, lambda ns: ns.update(namespace))
# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ PYOBJECT TYPE ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
if TYPE_CHECKING:
PyObject = Callable[..., Any]
else:
class PyObject:
validate_always = True
@classmethod
def __get_validators__(cls) -> 'CallableGenerator':
yield cls.validate
@classmethod
def validate(cls, value: Any) -> Any:
if isinstance(value, Callable):
return value
try:
value = str_validator(value)
except errors.StrError:
raise errors.PyObjectError(error_message='value is neither a valid import path not a valid callable')
try:
return import_string(value)
except ImportError as e:
raise errors.PyObjectError(error_message=str(e))
# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ DECIMAL TYPES ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
class ConstrainedDecimal(Decimal, metaclass=ConstrainedNumberMeta):
gt: OptionalIntFloatDecimal = None
ge: OptionalIntFloatDecimal = None
lt: OptionalIntFloatDecimal = None
le: OptionalIntFloatDecimal = None
max_digits: OptionalInt = None
decimal_places: OptionalInt = None
multiple_of: OptionalIntFloatDecimal = None
@classmethod
def __modify_schema__(cls, field_schema: Dict[str, Any]) -> None:
update_not_none(
field_schema,
exclusiveMinimum=cls.gt,
exclusiveMaximum=cls.lt,
minimum=cls.ge,
maximum=cls.le,
multipleOf=cls.multiple_of,
)
@classmethod
def __get_validators__(cls) -> 'CallableGenerator':
yield decimal_validator
yield number_size_validator
yield number_multiple_validator
yield cls.validate
@classmethod
def validate(cls, value: Decimal) -> Decimal:
try:
normalized_value = value.normalize()
except InvalidOperation:
normalized_value = value
digit_tuple, exponent = normalized_value.as_tuple()[1:]
if exponent in {'F', 'n', 'N'}:
raise errors.DecimalIsNotFiniteError()
if exponent >= 0:
# A positive exponent adds that many trailing zeros.
digits = len(digit_tuple) + exponent
decimals = 0
else:
# If the absolute value of the negative exponent is larger than the
# number of digits, then it's the same as the number of digits,
# because it'll consume all of the digits in digit_tuple and then
# add abs(exponent) - len(digit_tuple) leading zeros after the
# decimal point.
if abs(exponent) > len(digit_tuple):
digits = decimals = abs(exponent)
else:
digits = len(digit_tuple)
decimals = abs(exponent)
whole_digits = digits - decimals
if cls.max_digits is not None and digits > cls.max_digits:
raise errors.DecimalMaxDigitsError(max_digits=cls.max_digits)
if cls.decimal_places is not None and decimals > cls.decimal_places:
raise errors.DecimalMaxPlacesError(decimal_places=cls.decimal_places)
if cls.max_digits is not None and cls.decimal_places is not None:
expected = cls.max_digits - cls.decimal_places
if whole_digits > expected:
raise errors.DecimalWholeDigitsError(whole_digits=expected)
return value
def condecimal(
*,
gt: Decimal = None,
ge: Decimal = None,
lt: Decimal = None,
le: Decimal = None,
max_digits: Optional[int] = None,
decimal_places: Optional[int] = None,
multiple_of: Decimal = None,
) -> Type[Decimal]:
# use kwargs then define conf in a dict to aid with IDE type hinting
namespace = dict(
gt=gt, ge=ge, lt=lt, le=le, max_digits=max_digits, decimal_places=decimal_places, multiple_of=multiple_of
)
return type('ConstrainedDecimalValue', (ConstrainedDecimal,), namespace)
# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ UUID TYPES ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
if TYPE_CHECKING:
UUID1 = UUID
UUID3 = UUID
UUID4 = UUID
UUID5 = UUID
else:
class UUID1(UUID):
_required_version = 1
@classmethod
def __modify_schema__(cls, field_schema: Dict[str, Any]) -> None:
field_schema.update(type='string', format=f'uuid{cls._required_version}')
class UUID3(UUID1):
_required_version = 3
class UUID4(UUID1):
_required_version = 4
class UUID5(UUID1):
_required_version = 5
# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ PATH TYPES ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
if TYPE_CHECKING:
FilePath = Path
DirectoryPath = Path
else:
class FilePath(Path):
@classmethod
def __modify_schema__(cls, field_schema: Dict[str, Any]) -> None:
field_schema.update(format='file-path')
@classmethod
def __get_validators__(cls) -> 'CallableGenerator':
yield path_validator
yield path_exists_validator
yield cls.validate
@classmethod
def validate(cls, value: Path) -> Path:
if not value.is_file():
raise errors.PathNotAFileError(path=value)
return value
class DirectoryPath(Path):
@classmethod
def __modify_schema__(cls, field_schema: Dict[str, Any]) -> None:
field_schema.update(format='directory-path')
@classmethod
def __get_validators__(cls) -> 'CallableGenerator':
yield path_validator
yield path_exists_validator
yield cls.validate
@classmethod
def validate(cls, value: Path) -> Path:
if not value.is_dir():
raise errors.PathNotADirectoryError(path=value)
return value
# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ JSON TYPE ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
class JsonWrapper:
pass
class JsonMeta(type):
def __getitem__(self, t: Type[Any]) -> Type[JsonWrapper]:
if t is Any:
return Json # allow Json[Any] to replecate plain Json
return _registered(type('JsonWrapperValue', (JsonWrapper,), {'inner_type': t}))
if TYPE_CHECKING:
Json = Annotated[T, ...] # Json[list[str]] will be recognized by type checkers as list[str]
else:
class Json(metaclass=JsonMeta):
@classmethod
def __modify_schema__(cls, field_schema: Dict[str, Any]) -> None:
field_schema.update(type='string', format='json-string')
# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ SECRET TYPES ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
class SecretField(abc.ABC):
"""
Note: this should be implemented as a generic like `SecretField(ABC, Generic[T])`,
the `__init__()` should be part of the abstract class and the
`get_secret_value()` method should use the generic `T` type.
However Cython doesn't support very well generics at the moment and
the generated code fails to be imported (see
https://github.com/cython/cython/issues/2753).
"""
def __eq__(self, other: Any) -> bool:
return isinstance(other, self.__class__) and self.get_secret_value() == other.get_secret_value()
def __str__(self) -> str:
return '**********' if self.get_secret_value() else ''
def __hash__(self) -> int:
return hash(self.get_secret_value())
@abc.abstractmethod
def get_secret_value(self) -> Any: # pragma: no cover
...
class SecretStr(SecretField):
min_length: OptionalInt = None
max_length: OptionalInt = None
@classmethod
def __modify_schema__(cls, field_schema: Dict[str, Any]) -> None:
update_not_none(
field_schema,
type='string',
writeOnly=True,
format='password',
minLength=cls.min_length,
maxLength=cls.max_length,
)
@classmethod
def __get_validators__(cls) -> 'CallableGenerator':
yield cls.validate
yield constr_length_validator
@classmethod
def validate(cls, value: Any) -> 'SecretStr':
if isinstance(value, cls):
return value
value = str_validator(value)
return cls(value)
def __init__(self, value: str):
self._secret_value = value
def __repr__(self) -> str:
return f"SecretStr('{self}')"
def __len__(self) -> int:
return len(self._secret_value)
def display(self) -> str:
warnings.warn('`secret_str.display()` is deprecated, use `str(secret_str)` instead', DeprecationWarning)
return str(self)
def get_secret_value(self) -> str:
return self._secret_value
class SecretBytes(SecretField):
min_length: OptionalInt = None
max_length: OptionalInt = None
@classmethod
def __modify_schema__(cls, field_schema: Dict[str, Any]) -> None:
update_not_none(
field_schema,
type='string',
writeOnly=True,
format='password',
minLength=cls.min_length,
maxLength=cls.max_length,
)
@classmethod
def __get_validators__(cls) -> 'CallableGenerator':
yield cls.validate
yield constr_length_validator
@classmethod
def validate(cls, value: Any) -> 'SecretBytes':
if isinstance(value, cls):
return value
value = bytes_validator(value)
return cls(value)
def __init__(self, value: bytes):
self._secret_value = value
def __repr__(self) -> str:
return f"SecretBytes(b'{self}')"
def __len__(self) -> int:
return len(self._secret_value)
def display(self) -> str:
warnings.warn('`secret_bytes.display()` is deprecated, use `str(secret_bytes)` instead', DeprecationWarning)
return str(self)
def get_secret_value(self) -> bytes:
return self._secret_value
# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ PAYMENT CARD TYPES ~~~~~~~~~~~~~~~~~~~~~~~~~~~~
class PaymentCardBrand(str, Enum):
# If you add another card type, please also add it to the
# Hypothesis strategy in `pydantic._hypothesis_plugin`.
amex = 'American Express'
mastercard = 'Mastercard'
visa = 'Visa'
other = 'other'
def __str__(self) -> str:
return self.value
class PaymentCardNumber(str):
"""
Based on: https://en.wikipedia.org/wiki/Payment_card_number
"""
strip_whitespace: ClassVar[bool] = True
min_length: ClassVar[int] = 12
max_length: ClassVar[int] = 19
bin: str
last4: str
brand: PaymentCardBrand
def __init__(self, card_number: str):
self.bin = card_number[:6]
self.last4 = card_number[-4:]
self.brand = self._get_brand(card_number)
@classmethod
def __get_validators__(cls) -> 'CallableGenerator':
yield str_validator
yield constr_strip_whitespace
yield constr_length_validator
yield cls.validate_digits
yield cls.validate_luhn_check_digit
yield cls
yield cls.validate_length_for_brand
@property
def masked(self) -> str:
num_masked = len(self) - 10 # len(bin) + len(last4) == 10
return f'{self.bin}{"*" * num_masked}{self.last4}'
@classmethod
def validate_digits(cls, card_number: str) -> str:
if not card_number.isdigit():
raise errors.NotDigitError
return card_number
@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 errors.LuhnValidationError
return card_number
@classmethod
def validate_length_for_brand(cls, card_number: 'PaymentCardNumber') -> 'PaymentCardNumber':
"""
Validate length based on BIN for major brands:
https://en.wikipedia.org/wiki/Payment_card_number#Issuer_identification_number_(IIN)
"""
required_length: Union[None, int, str] = None
if card_number.brand in PaymentCardBrand.mastercard:
required_length = 16
valid = len(card_number) == required_length
elif card_number.brand == PaymentCardBrand.visa:
required_length = '13, 16 or 19'
valid = len(card_number) in {13, 16, 19}
elif card_number.brand == PaymentCardBrand.amex:
required_length = 15
valid = len(card_number) == required_length
else:
valid = True
if not valid:
raise errors.InvalidLengthForBrand(brand=card_number.brand, required_length=required_length)
return card_number
@staticmethod
def _get_brand(card_number: str) -> PaymentCardBrand:
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
return brand
# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ BYTE SIZE TYPE ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
BYTE_SIZES = {
'b': 1,
'kb': 10**3,
'mb': 10**6,
'gb': 10**9,
'tb': 10**12,
'pb': 10**15,
'eb': 10**18,
'kib': 2**10,
'mib': 2**20,
'gib': 2**30,
'tib': 2**40,
'pib': 2**50,
'eib': 2**60,
}
BYTE_SIZES.update({k.lower()[0]: v for k, v in BYTE_SIZES.items() if 'i' not in k})
byte_string_re = re.compile(r'^\s*(\d*\.?\d+)\s*(\w+)?', re.IGNORECASE)
class ByteSize(int):
@classmethod
def __get_validators__(cls) -> 'CallableGenerator':
yield cls.validate
@classmethod
def validate(cls, v: StrIntFloat) -> 'ByteSize':
try:
return cls(int(v))
except ValueError:
pass
str_match = byte_string_re.match(str(v))
if str_match is None:
raise errors.InvalidByteSize()
scalar, unit = str_match.groups()
if unit is None:
unit = 'b'
try:
unit_mult = BYTE_SIZES[unit.lower()]
except KeyError:
raise errors.InvalidByteSizeUnit(unit=unit)
return cls(int(float(scalar) * unit_mult))
def human_readable(self, decimal: bool = False) -> str:
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:
return f'{num:0.1f}{unit}'
num /= divisor
return f'{num:0.1f}{final_unit}'
def to(self, unit: str) -> float:
try:
unit_div = BYTE_SIZES[unit.lower()]
except KeyError:
raise errors.InvalidByteSizeUnit(unit=unit)
return self / unit_div
# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ DATE TYPES ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
if TYPE_CHECKING:
PastDate = date
FutureDate = date
else:
class PastDate(date):
@classmethod
def __get_validators__(cls) -> 'CallableGenerator':
yield parse_date
yield cls.validate
@classmethod
def validate(cls, value: date) -> date:
if value >= date.today():
raise errors.DateNotInThePastError()
return value
class FutureDate(date):
@classmethod
def __get_validators__(cls) -> 'CallableGenerator':
yield parse_date
yield cls.validate
@classmethod
def validate(cls, value: date) -> date:
if value <= date.today():
raise errors.DateNotInTheFutureError()
return value
class ConstrainedDate(date, metaclass=ConstrainedNumberMeta):
gt: OptionalDate = None
ge: OptionalDate = None
lt: OptionalDate = None
le: OptionalDate = None
@classmethod
def __modify_schema__(cls, field_schema: Dict[str, Any]) -> None:
update_not_none(field_schema, exclusiveMinimum=cls.gt, exclusiveMaximum=cls.lt, minimum=cls.ge, maximum=cls.le)
@classmethod
def __get_validators__(cls) -> 'CallableGenerator':
yield parse_date
yield number_size_validator
def condate(
*,
gt: date = None,
ge: date = None,
lt: date = None,
le: date = None,
) -> Type[date]:
# use kwargs then define conf in a dict to aid with IDE type hinting
namespace = dict(gt=gt, ge=ge, lt=lt, le=le)
return type('ConstrainedDateValue', (ConstrainedDate,), namespace)