관리-도구
편집 파일: types.py
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)