Загрузить файлы в «venv/Lib/site-packages/pydantic/v1»

venv/Lib/site-packages/pydantic/v1/__init__.py

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+# flake8: noqa
+from pydantic.v1 import dataclasses
+from pydantic.v1.annotated_types import create_model_from_namedtuple, create_model_from_typeddict
+from pydantic.v1.class_validators import root_validator, validator
+from pydantic.v1.config import BaseConfig, ConfigDict, Extra
+from pydantic.v1.decorator import validate_arguments
+from pydantic.v1.env_settings import BaseSettings
+from pydantic.v1.error_wrappers import ValidationError
+from pydantic.v1.errors import *
+from pydantic.v1.fields import Field, PrivateAttr, Required
+from pydantic.v1.main import *
+from pydantic.v1.networks import *
+from pydantic.v1.parse import Protocol
+from pydantic.v1.tools import *
+from pydantic.v1.types import *
+from pydantic.v1.version import VERSION, compiled
+
+__version__ = VERSION
+
+# WARNING __all__ from pydantic.errors is not included here, it will be removed as an export here in v2
+# please use "from pydantic.v1.errors import ..." instead
+__all__ = [
+    # annotated types utils
+    'create_model_from_namedtuple',
+    'create_model_from_typeddict',
+    # dataclasses
+    'dataclasses',
+    # class_validators
+    'root_validator',
+    'validator',
+    # config
+    'BaseConfig',
+    'ConfigDict',
+    'Extra',
+    # decorator
+    'validate_arguments',
+    # env_settings
+    'BaseSettings',
+    # error_wrappers
+    'ValidationError',
+    # fields
+    'Field',
+    'Required',
+    # main
+    'BaseModel',
+    'create_model',
+    'validate_model',
+    # network
+    'AnyUrl',
+    'AnyHttpUrl',
+    'FileUrl',
+    'HttpUrl',
+    'stricturl',
+    'EmailStr',
+    'NameEmail',
+    'IPvAnyAddress',
+    'IPvAnyInterface',
+    'IPvAnyNetwork',
+    'PostgresDsn',
+    'CockroachDsn',
+    'AmqpDsn',
+    'RedisDsn',
+    'MongoDsn',
+    'KafkaDsn',
+    'validate_email',
+    # parse
+    'Protocol',
+    # tools
+    'parse_file_as',
+    'parse_obj_as',
+    'parse_raw_as',
+    'schema_of',
+    'schema_json_of',
+    # types
+    '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',
+    'ConstrainedDate',
+    'condate',
+    'UUID1',
+    'UUID3',
+    'UUID4',
+    'UUID5',
+    'FilePath',
+    'DirectoryPath',
+    'Json',
+    'JsonWrapper',
+    'SecretField',
+    'SecretStr',
+    'SecretBytes',
+    'StrictBool',
+    'StrictBytes',
+    'StrictInt',
+    'StrictFloat',
+    'PaymentCardNumber',
+    'PrivateAttr',
+    'ByteSize',
+    'PastDate',
+    'FutureDate',
+    # version
+    'compiled',
+    'VERSION',
+]

venv/Lib/site-packages/pydantic/v1/_hypothesis_plugin.py

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+"""
+Register Hypothesis strategies for Pydantic custom types.
+
+This enables fully-automatic generation of test data for most Pydantic classes.
+
+Note that this module has *no* runtime impact on Pydantic itself; instead it
+is registered as a setuptools entry point and Hypothesis will import it if
+Pydantic is installed.  See also:
+
+https://hypothesis.readthedocs.io/en/latest/strategies.html#registering-strategies-via-setuptools-entry-points
+https://hypothesis.readthedocs.io/en/latest/data.html#hypothesis.strategies.register_type_strategy
+https://hypothesis.readthedocs.io/en/latest/strategies.html#interaction-with-pytest-cov
+https://docs.pydantic.dev/usage/types/#pydantic-types
+
+Note that because our motivation is to *improve user experience*, the strategies
+are always sound (never generate invalid data) but sacrifice completeness for
+maintainability (ie may be unable to generate some tricky but valid data).
+
+Finally, this module makes liberal use of `# type: ignore[<code>]` pragmas.
+This is because Hypothesis annotates `register_type_strategy()` with
+`(T, SearchStrategy[T])`, but in most cases we register e.g. `ConstrainedInt`
+to generate instances of the builtin `int` type which match the constraints.
+"""
+
+import contextlib
+import datetime
+import ipaddress
+import json
+import math
+from fractions import Fraction
+from typing import Callable, Dict, Type, Union, cast, overload
+
+import hypothesis.strategies as st
+
+import pydantic
+import pydantic.color
+import pydantic.types
+from pydantic.v1.utils import lenient_issubclass
+
+# FilePath and DirectoryPath are explicitly unsupported, as we'd have to create
+# them on-disk, and that's unsafe in general without being told *where* to do so.
+#
+# URLs are unsupported because it's easy for users to define their own strategy for
+# "normal" URLs, and hard for us to define a general strategy which includes "weird"
+# URLs but doesn't also have unpredictable performance problems.
+#
+# conlist() and conset() are unsupported for now, because the workarounds for
+# Cython and Hypothesis to handle parametrized generic types are incompatible.
+# We are rethinking Hypothesis compatibility in Pydantic v2.
+
+# Emails
+try:
+    import email_validator
+except ImportError:  # pragma: no cover
+    pass
+else:
+
+    def is_valid_email(s: str) -> bool:
+        # Hypothesis' st.emails() occasionally generates emails like 0@A0--0.ac
+        # that are invalid according to email-validator, so we filter those out.
+        try:
+            email_validator.validate_email(s, check_deliverability=False)
+            return True
+        except email_validator.EmailNotValidError:  # pragma: no cover
+            return False
+
+    # Note that these strategies deliberately stay away from any tricky Unicode
+    # or other encoding issues; we're just trying to generate *something* valid.
+    st.register_type_strategy(pydantic.EmailStr, st.emails().filter(is_valid_email))  # type: ignore[arg-type]
+    st.register_type_strategy(
+        pydantic.NameEmail,
+        st.builds(
+            '{} <{}>'.format,  # type: ignore[arg-type]
+            st.from_regex('[A-Za-z0-9_]+( [A-Za-z0-9_]+){0,5}', fullmatch=True),
+            st.emails().filter(is_valid_email),
+        ),
+    )
+
+# PyObject - dotted names, in this case taken from the math module.
+st.register_type_strategy(
+    pydantic.PyObject,  # type: ignore[arg-type]
+    st.sampled_from(
+        [cast(pydantic.PyObject, f'math.{name}') for name in sorted(vars(math)) if not name.startswith('_')]
+    ),
+)
+
+# CSS3 Colors; as name, hex, rgb(a) tuples or strings, or hsl strings
+_color_regexes = (
+    '|'.join(
+        (
+            pydantic.color.r_hex_short,
+            pydantic.color.r_hex_long,
+            pydantic.color.r_rgb,
+            pydantic.color.r_rgba,
+            pydantic.color.r_hsl,
+            pydantic.color.r_hsla,
+        )
+    )
+    # Use more precise regex patterns to avoid value-out-of-range errors
+    .replace(pydantic.color._r_sl, r'(?:(\d\d?(?:\.\d+)?|100(?:\.0+)?)%)')
+    .replace(pydantic.color._r_alpha, r'(?:(0(?:\.\d+)?|1(?:\.0+)?|\.\d+|\d{1,2}%))')
+    .replace(pydantic.color._r_255, r'(?:((?:\d|\d\d|[01]\d\d|2[0-4]\d|25[0-4])(?:\.\d+)?|255(?:\.0+)?))')
+)
+st.register_type_strategy(
+    pydantic.color.Color,
+    st.one_of(
+        st.sampled_from(sorted(pydantic.color.COLORS_BY_NAME)),
+        st.tuples(
+            st.integers(0, 255),
+            st.integers(0, 255),
+            st.integers(0, 255),
+            st.none() | st.floats(0, 1) | st.floats(0, 100).map('{}%'.format),
+        ),
+        st.from_regex(_color_regexes, fullmatch=True),
+    ),
+)
+
+
+# Card numbers, valid according to the Luhn algorithm
+
+
+def add_luhn_digit(card_number: str) -> str:
+    # See https://en.wikipedia.org/wiki/Luhn_algorithm
+    for digit in '0123456789':
+        with contextlib.suppress(Exception):
+            pydantic.PaymentCardNumber.validate_luhn_check_digit(card_number + digit)
+            return card_number + digit
+    raise AssertionError('Unreachable')  # pragma: no cover
+
+
+card_patterns = (
+    # Note that these patterns omit the Luhn check digit; that's added by the function above
+    '4[0-9]{14}',  # Visa
+    '5[12345][0-9]{13}',  # Mastercard
+    '3[47][0-9]{12}',  # American Express
+    '[0-26-9][0-9]{10,17}',  # other (incomplete to avoid overlap)
+)
+st.register_type_strategy(
+    pydantic.PaymentCardNumber,
+    st.from_regex('|'.join(card_patterns), fullmatch=True).map(add_luhn_digit),  # type: ignore[arg-type]
+)
+
+# UUIDs
+st.register_type_strategy(pydantic.UUID1, st.uuids(version=1))
+st.register_type_strategy(pydantic.UUID3, st.uuids(version=3))
+st.register_type_strategy(pydantic.UUID4, st.uuids(version=4))
+st.register_type_strategy(pydantic.UUID5, st.uuids(version=5))
+
+# Secrets
+st.register_type_strategy(pydantic.SecretBytes, st.binary().map(pydantic.SecretBytes))
+st.register_type_strategy(pydantic.SecretStr, st.text().map(pydantic.SecretStr))
+
+# IP addresses, networks, and interfaces
+st.register_type_strategy(pydantic.IPvAnyAddress, st.ip_addresses())  # type: ignore[arg-type]
+st.register_type_strategy(
+    pydantic.IPvAnyInterface,
+    st.from_type(ipaddress.IPv4Interface) | st.from_type(ipaddress.IPv6Interface),  # type: ignore[arg-type]
+)
+st.register_type_strategy(
+    pydantic.IPvAnyNetwork,
+    st.from_type(ipaddress.IPv4Network) | st.from_type(ipaddress.IPv6Network),  # type: ignore[arg-type]
+)
+
+# We hook into the con***() functions and the ConstrainedNumberMeta metaclass,
+# so here we only have to register subclasses for other constrained types which
+# don't go via those mechanisms.  Then there are the registration hooks below.
+st.register_type_strategy(pydantic.StrictBool, st.booleans())
+st.register_type_strategy(pydantic.StrictStr, st.text())
+
+
+# FutureDate, PastDate
+st.register_type_strategy(pydantic.FutureDate, st.dates(min_value=datetime.date.today() + datetime.timedelta(days=1)))
+st.register_type_strategy(pydantic.PastDate, st.dates(max_value=datetime.date.today() - datetime.timedelta(days=1)))
+
+
+# Constrained-type resolver functions
+#
+# For these ones, we actually want to inspect the type in order to work out a
+# satisfying strategy.  First up, the machinery for tracking resolver functions:
+
+RESOLVERS: Dict[type, Callable[[type], st.SearchStrategy]] = {}  # type: ignore[type-arg]
+
+
+@overload
+def _registered(typ: Type[pydantic.types.T]) -> Type[pydantic.types.T]:
+    pass
+
+
+@overload
+def _registered(typ: pydantic.types.ConstrainedNumberMeta) -> pydantic.types.ConstrainedNumberMeta:
+    pass
+
+
+def _registered(
+    typ: Union[Type[pydantic.types.T], pydantic.types.ConstrainedNumberMeta]
+) -> Union[Type[pydantic.types.T], pydantic.types.ConstrainedNumberMeta]:
+    # This function replaces the version in `pydantic.types`, in order to
+    # effect the registration of new constrained types so that Hypothesis
+    # can generate valid examples.
+    pydantic.types._DEFINED_TYPES.add(typ)
+    for supertype, resolver in RESOLVERS.items():
+        if issubclass(typ, supertype):
+            st.register_type_strategy(typ, resolver(typ))  # type: ignore
+            return typ
+    raise NotImplementedError(f'Unknown type {typ!r} has no resolver to register')  # pragma: no cover
+
+
+def resolves(
+    typ: Union[type, pydantic.types.ConstrainedNumberMeta]
+) -> Callable[[Callable[..., st.SearchStrategy]], Callable[..., st.SearchStrategy]]:  # type: ignore[type-arg]
+    def inner(f):  # type: ignore
+        assert f not in RESOLVERS
+        RESOLVERS[typ] = f
+        return f
+
+    return inner
+
+
+# Type-to-strategy resolver functions
+
+
+@resolves(pydantic.JsonWrapper)
+def resolve_json(cls):  # type: ignore[no-untyped-def]
+    try:
+        inner = st.none() if cls.inner_type is None else st.from_type(cls.inner_type)
+    except Exception:  # pragma: no cover
+        finite = st.floats(allow_infinity=False, allow_nan=False)
+        inner = st.recursive(
+            base=st.one_of(st.none(), st.booleans(), st.integers(), finite, st.text()),
+            extend=lambda x: st.lists(x) | st.dictionaries(st.text(), x),  # type: ignore
+        )
+    inner_type = getattr(cls, 'inner_type', None)
+    return st.builds(
+        cls.inner_type.json if lenient_issubclass(inner_type, pydantic.BaseModel) else json.dumps,
+        inner,
+        ensure_ascii=st.booleans(),
+        indent=st.none() | st.integers(0, 16),
+        sort_keys=st.booleans(),
+    )
+
+
+@resolves(pydantic.ConstrainedBytes)
+def resolve_conbytes(cls):  # type: ignore[no-untyped-def]  # pragma: no cover
+    min_size = cls.min_length or 0
+    max_size = cls.max_length
+    if not cls.strip_whitespace:
+        return st.binary(min_size=min_size, max_size=max_size)
+    # Fun with regex to ensure we neither start nor end with whitespace
+    repeats = '{{{},{}}}'.format(
+        min_size - 2 if min_size > 2 else 0,
+        max_size - 2 if (max_size or 0) > 2 else '',
+    )
+    if min_size >= 2:
+        pattern = rf'\W.{repeats}\W'
+    elif min_size == 1:
+        pattern = rf'\W(.{repeats}\W)?'
+    else:
+        assert min_size == 0
+        pattern = rf'(\W(.{repeats}\W)?)?'
+    return st.from_regex(pattern.encode(), fullmatch=True)
+
+
+@resolves(pydantic.ConstrainedDecimal)
+def resolve_condecimal(cls):  # type: ignore[no-untyped-def]
+    min_value = cls.ge
+    max_value = cls.le
+    if cls.gt is not None:
+        assert min_value is None, 'Set `gt` or `ge`, but not both'
+        min_value = cls.gt
+    if cls.lt is not None:
+        assert max_value is None, 'Set `lt` or `le`, but not both'
+        max_value = cls.lt
+    s = st.decimals(min_value, max_value, allow_nan=False, places=cls.decimal_places)
+    if cls.lt is not None:
+        s = s.filter(lambda d: d < cls.lt)
+    if cls.gt is not None:
+        s = s.filter(lambda d: cls.gt < d)
+    return s
+
+
+@resolves(pydantic.ConstrainedFloat)
+def resolve_confloat(cls):  # type: ignore[no-untyped-def]
+    min_value = cls.ge
+    max_value = cls.le
+    exclude_min = False
+    exclude_max = False
+
+    if cls.gt is not None:
+        assert min_value is None, 'Set `gt` or `ge`, but not both'
+        min_value = cls.gt
+        exclude_min = True
+    if cls.lt is not None:
+        assert max_value is None, 'Set `lt` or `le`, but not both'
+        max_value = cls.lt
+        exclude_max = True
+
+    if cls.multiple_of is None:
+        return st.floats(min_value, max_value, exclude_min=exclude_min, exclude_max=exclude_max, allow_nan=False)
+
+    if min_value is not None:
+        min_value = math.ceil(min_value / cls.multiple_of)
+        if exclude_min:
+            min_value = min_value + 1
+    if max_value is not None:
+        assert max_value >= cls.multiple_of, 'Cannot build model with max value smaller than multiple of'
+        max_value = math.floor(max_value / cls.multiple_of)
+        if exclude_max:
+            max_value = max_value - 1
+
+    return st.integers(min_value, max_value).map(lambda x: x * cls.multiple_of)
+
+
+@resolves(pydantic.ConstrainedInt)
+def resolve_conint(cls):  # type: ignore[no-untyped-def]
+    min_value = cls.ge
+    max_value = cls.le
+    if cls.gt is not None:
+        assert min_value is None, 'Set `gt` or `ge`, but not both'
+        min_value = cls.gt + 1
+    if cls.lt is not None:
+        assert max_value is None, 'Set `lt` or `le`, but not both'
+        max_value = cls.lt - 1
+
+    if cls.multiple_of is None or cls.multiple_of == 1:
+        return st.integers(min_value, max_value)
+
+    # These adjustments and the .map handle integer-valued multiples, while the
+    # .filter handles trickier cases as for confloat.
+    if min_value is not None:
+        min_value = math.ceil(Fraction(min_value) / Fraction(cls.multiple_of))
+    if max_value is not None:
+        max_value = math.floor(Fraction(max_value) / Fraction(cls.multiple_of))
+    return st.integers(min_value, max_value).map(lambda x: x * cls.multiple_of)
+
+
+@resolves(pydantic.ConstrainedDate)
+def resolve_condate(cls):  # type: ignore[no-untyped-def]
+    if cls.ge is not None:
+        assert cls.gt is None, 'Set `gt` or `ge`, but not both'
+        min_value = cls.ge
+    elif cls.gt is not None:
+        min_value = cls.gt + datetime.timedelta(days=1)
+    else:
+        min_value = datetime.date.min
+    if cls.le is not None:
+        assert cls.lt is None, 'Set `lt` or `le`, but not both'
+        max_value = cls.le
+    elif cls.lt is not None:
+        max_value = cls.lt - datetime.timedelta(days=1)
+    else:
+        max_value = datetime.date.max
+    return st.dates(min_value, max_value)
+
+
+@resolves(pydantic.ConstrainedStr)
+def resolve_constr(cls):  # type: ignore[no-untyped-def]  # pragma: no cover
+    min_size = cls.min_length or 0
+    max_size = cls.max_length
+
+    if cls.regex is None and not cls.strip_whitespace:
+        return st.text(min_size=min_size, max_size=max_size)
+
+    if cls.regex is not None:
+        strategy = st.from_regex(cls.regex)
+        if cls.strip_whitespace:
+            strategy = strategy.filter(lambda s: s == s.strip())
+    elif cls.strip_whitespace:
+        repeats = '{{{},{}}}'.format(
+            min_size - 2 if min_size > 2 else 0,
+            max_size - 2 if (max_size or 0) > 2 else '',
+        )
+        if min_size >= 2:
+            strategy = st.from_regex(rf'\W.{repeats}\W')
+        elif min_size == 1:
+            strategy = st.from_regex(rf'\W(.{repeats}\W)?')
+        else:
+            assert min_size == 0
+            strategy = st.from_regex(rf'(\W(.{repeats}\W)?)?')
+
+    if min_size == 0 and max_size is None:
+        return strategy
+    elif max_size is None:
+        return strategy.filter(lambda s: min_size <= len(s))
+    return strategy.filter(lambda s: min_size <= len(s) <= max_size)
+
+
+# Finally, register all previously-defined types, and patch in our new function
+for typ in list(pydantic.types._DEFINED_TYPES):
+    _registered(typ)
+pydantic.types._registered = _registered
+st.register_type_strategy(pydantic.Json, resolve_json)

venv/Lib/site-packages/pydantic/v1/annotated_types.py

@@ -0,0 +1,72 @@
+import sys
+from typing import TYPE_CHECKING, Any, Dict, FrozenSet, NamedTuple, Type
+
+from pydantic.v1.fields import Required
+from pydantic.v1.main import BaseModel, create_model
+from pydantic.v1.typing import is_typeddict, is_typeddict_special
+
+if TYPE_CHECKING:
+    from typing_extensions import TypedDict
+
+if sys.version_info < (3, 11):
+
+    def is_legacy_typeddict(typeddict_cls: Type['TypedDict']) -> bool:  # type: ignore[valid-type]
+        return is_typeddict(typeddict_cls) and type(typeddict_cls).__module__ == 'typing'
+
+else:
+
+    def is_legacy_typeddict(_: Any) -> Any:
+        return False
+
+
+def create_model_from_typeddict(
+    # Mypy bug: `Type[TypedDict]` is resolved as `Any` https://github.com/python/mypy/issues/11030
+    typeddict_cls: Type['TypedDict'],  # type: ignore[valid-type]
+    **kwargs: Any,
+) -> Type['BaseModel']:
+    """
+    Create a `BaseModel` based on the fields of a `TypedDict`.
+    Since `typing.TypedDict` in Python 3.8 does not store runtime information about optional keys,
+    we raise an error if this happens (see https://bugs.python.org/issue38834).
+    """
+    field_definitions: Dict[str, Any]
+
+    # Best case scenario: with python 3.9+ or when `TypedDict` is imported from `typing_extensions`
+    if not hasattr(typeddict_cls, '__required_keys__'):
+        raise TypeError(
+            'You should use `typing_extensions.TypedDict` instead of `typing.TypedDict` with Python < 3.9.2. '
+            'Without it, there is no way to differentiate required and optional fields when subclassed.'
+        )
+
+    if is_legacy_typeddict(typeddict_cls) and any(
+        is_typeddict_special(t) for t in typeddict_cls.__annotations__.values()
+    ):
+        raise TypeError(
+            'You should use `typing_extensions.TypedDict` instead of `typing.TypedDict` with Python < 3.11. '
+            'Without it, there is no way to reflect Required/NotRequired keys.'
+        )
+
+    required_keys: FrozenSet[str] = typeddict_cls.__required_keys__  # type: ignore[attr-defined]
+    field_definitions = {
+        field_name: (field_type, Required if field_name in required_keys else None)
+        for field_name, field_type in typeddict_cls.__annotations__.items()
+    }
+
+    return create_model(typeddict_cls.__name__, **kwargs, **field_definitions)
+
+
+def create_model_from_namedtuple(namedtuple_cls: Type['NamedTuple'], **kwargs: Any) -> Type['BaseModel']:
+    """
+    Create a `BaseModel` based on the fields of a named tuple.
+    A named tuple can be created with `typing.NamedTuple` and declared annotations
+    but also with `collections.namedtuple`, in this case we consider all fields
+    to have type `Any`.
+    """
+    # With python 3.10+, `__annotations__` always exists but can be empty hence the `getattr... or...` logic
+    namedtuple_annotations: Dict[str, Type[Any]] = getattr(namedtuple_cls, '__annotations__', None) or {
+        k: Any for k in namedtuple_cls._fields
+    }
+    field_definitions: Dict[str, Any] = {
+        field_name: (field_type, Required) for field_name, field_type in namedtuple_annotations.items()
+    }
+    return create_model(namedtuple_cls.__name__, **kwargs, **field_definitions)

venv/Lib/site-packages/pydantic/v1/class_validators.py

@@ -0,0 +1,361 @@
+import warnings
+from collections import ChainMap
+from functools import partial, partialmethod, wraps
+from itertools import chain
+from types import FunctionType
+from typing import TYPE_CHECKING, Any, Callable, Dict, Iterable, List, Optional, Set, Tuple, Type, Union, overload
+
+from pydantic.v1.errors import ConfigError
+from pydantic.v1.typing import AnyCallable
+from pydantic.v1.utils import ROOT_KEY, in_ipython
+
+if TYPE_CHECKING:
+    from pydantic.v1.typing import AnyClassMethod
+
+
+class Validator:
+    __slots__ = 'func', 'pre', 'each_item', 'always', 'check_fields', 'skip_on_failure'
+
+    def __init__(
+        self,
+        func: AnyCallable,
+        pre: bool = False,
+        each_item: bool = False,
+        always: bool = False,
+        check_fields: bool = False,
+        skip_on_failure: bool = False,
+    ):
+        self.func = func
+        self.pre = pre
+        self.each_item = each_item
+        self.always = always
+        self.check_fields = check_fields
+        self.skip_on_failure = skip_on_failure
+
+
+if TYPE_CHECKING:
+    from inspect import Signature
+
+    from pydantic.v1.config import BaseConfig
+    from pydantic.v1.fields import ModelField
+    from pydantic.v1.types import ModelOrDc
+
+    ValidatorCallable = Callable[[Optional[ModelOrDc], Any, Dict[str, Any], ModelField, Type[BaseConfig]], Any]
+    ValidatorsList = List[ValidatorCallable]
+    ValidatorListDict = Dict[str, List[Validator]]
+
+_FUNCS: Set[str] = set()
+VALIDATOR_CONFIG_KEY = '__validator_config__'
+ROOT_VALIDATOR_CONFIG_KEY = '__root_validator_config__'
+
+
+def validator(
+    *fields: str,
+    pre: bool = False,
+    each_item: bool = False,
+    always: bool = False,
+    check_fields: bool = True,
+    whole: Optional[bool] = None,
+    allow_reuse: bool = False,
+) -> Callable[[AnyCallable], 'AnyClassMethod']:
+    """
+    Decorate methods on the class indicating that they should be used to validate fields
+    :param fields: which field(s) the method should be called on
+    :param pre: whether or not this validator should be called before the standard validators (else after)
+    :param each_item: for complex objects (sets, lists etc.) whether to validate individual elements rather than the
+      whole object
+    :param always: whether this method and other validators should be called even if the value is missing
+    :param check_fields: whether to check that the fields actually exist on the model
+    :param allow_reuse: whether to track and raise an error if another validator refers to the decorated function
+    """
+    if not fields:
+        raise ConfigError('validator with no fields specified')
+    elif isinstance(fields[0], FunctionType):
+        raise ConfigError(
+            "validators should be used with fields and keyword arguments, not bare. "  # noqa: Q000
+            "E.g. usage should be `@validator('<field_name>', ...)`"
+        )
+    elif not all(isinstance(field, str) for field in fields):
+        raise ConfigError(
+            "validator fields should be passed as separate string args. "  # noqa: Q000
+            "E.g. usage should be `@validator('<field_name_1>', '<field_name_2>', ...)`"
+        )
+
+    if whole is not None:
+        warnings.warn(
+            'The "whole" keyword argument is deprecated, use "each_item" (inverse meaning, default False) instead',
+            DeprecationWarning,
+        )
+        assert each_item is False, '"each_item" and "whole" conflict, remove "whole"'
+        each_item = not whole
+
+    def dec(f: AnyCallable) -> 'AnyClassMethod':
+        f_cls = _prepare_validator(f, allow_reuse)
+        setattr(
+            f_cls,
+            VALIDATOR_CONFIG_KEY,
+            (
+                fields,
+                Validator(func=f_cls.__func__, pre=pre, each_item=each_item, always=always, check_fields=check_fields),
+            ),
+        )
+        return f_cls
+
+    return dec
+
+
+@overload
+def root_validator(_func: AnyCallable) -> 'AnyClassMethod':
+    ...
+
+
+@overload
+def root_validator(
+    *, pre: bool = False, allow_reuse: bool = False, skip_on_failure: bool = False
+) -> Callable[[AnyCallable], 'AnyClassMethod']:
+    ...
+
+
+def root_validator(
+    _func: Optional[AnyCallable] = None, *, pre: bool = False, allow_reuse: bool = False, skip_on_failure: bool = False
+) -> Union['AnyClassMethod', Callable[[AnyCallable], 'AnyClassMethod']]:
+    """
+    Decorate methods on a model indicating that they should be used to validate (and perhaps modify) data either
+    before or after standard model parsing/validation is performed.
+    """
+    if _func:
+        f_cls = _prepare_validator(_func, allow_reuse)
+        setattr(
+            f_cls, ROOT_VALIDATOR_CONFIG_KEY, Validator(func=f_cls.__func__, pre=pre, skip_on_failure=skip_on_failure)
+        )
+        return f_cls
+
+    def dec(f: AnyCallable) -> 'AnyClassMethod':
+        f_cls = _prepare_validator(f, allow_reuse)
+        setattr(
+            f_cls, ROOT_VALIDATOR_CONFIG_KEY, Validator(func=f_cls.__func__, pre=pre, skip_on_failure=skip_on_failure)
+        )
+        return f_cls
+
+    return dec
+
+
+def _prepare_validator(function: AnyCallable, allow_reuse: bool) -> 'AnyClassMethod':
+    """
+    Avoid validators with duplicated names since without this, validators can be overwritten silently
+    which generally isn't the intended behaviour, don't run in ipython (see #312) or if allow_reuse is False.
+    """
+    f_cls = function if isinstance(function, classmethod) else classmethod(function)
+    if not in_ipython() and not allow_reuse:
+        ref = (
+            getattr(f_cls.__func__, '__module__', '<No __module__>')
+            + '.'
+            + getattr(f_cls.__func__, '__qualname__', f'<No __qualname__: id:{id(f_cls.__func__)}>')
+        )
+        if ref in _FUNCS:
+            raise ConfigError(f'duplicate validator function "{ref}"; if this is intended, set `allow_reuse=True`')
+        _FUNCS.add(ref)
+    return f_cls
+
+
+class ValidatorGroup:
+    def __init__(self, validators: 'ValidatorListDict') -> None:
+        self.validators = validators
+        self.used_validators = {'*'}
+
+    def get_validators(self, name: str) -> Optional[Dict[str, Validator]]:
+        self.used_validators.add(name)
+        validators = self.validators.get(name, [])
+        if name != ROOT_KEY:
+            validators += self.validators.get('*', [])
+        if validators:
+            return {getattr(v.func, '__name__', f'<No __name__: id:{id(v.func)}>'): v for v in validators}
+        else:
+            return None
+
+    def check_for_unused(self) -> None:
+        unused_validators = set(
+            chain.from_iterable(
+                (
+                    getattr(v.func, '__name__', f'<No __name__: id:{id(v.func)}>')
+                    for v in self.validators[f]
+                    if v.check_fields
+                )
+                for f in (self.validators.keys() - self.used_validators)
+            )
+        )
+        if unused_validators:
+            fn = ', '.join(unused_validators)
+            raise ConfigError(
+                f"Validators defined with incorrect fields: {fn} "  # noqa: Q000
+                f"(use check_fields=False if you're inheriting from the model and intended this)"
+            )
+
+
+def extract_validators(namespace: Dict[str, Any]) -> Dict[str, List[Validator]]:
+    validators: Dict[str, List[Validator]] = {}
+    for var_name, value in namespace.items():
+        validator_config = getattr(value, VALIDATOR_CONFIG_KEY, None)
+        if validator_config:
+            fields, v = validator_config
+            for field in fields:
+                if field in validators:
+                    validators[field].append(v)
+                else:
+                    validators[field] = [v]
+    return validators
+
+
+def extract_root_validators(namespace: Dict[str, Any]) -> Tuple[List[AnyCallable], List[Tuple[bool, AnyCallable]]]:
+    from inspect import signature
+
+    pre_validators: List[AnyCallable] = []
+    post_validators: List[Tuple[bool, AnyCallable]] = []
+    for name, value in namespace.items():
+        validator_config: Optional[Validator] = getattr(value, ROOT_VALIDATOR_CONFIG_KEY, None)
+        if validator_config:
+            sig = signature(validator_config.func)
+            args = list(sig.parameters.keys())
+            if args[0] == 'self':
+                raise ConfigError(
+                    f'Invalid signature for root validator {name}: {sig}, "self" not permitted as first argument, '
+                    f'should be: (cls, values).'
+                )
+            if len(args) != 2:
+                raise ConfigError(f'Invalid signature for root validator {name}: {sig}, should be: (cls, values).')
+            # check function signature
+            if validator_config.pre:
+                pre_validators.append(validator_config.func)
+            else:
+                post_validators.append((validator_config.skip_on_failure, validator_config.func))
+    return pre_validators, post_validators
+
+
+def inherit_validators(base_validators: 'ValidatorListDict', validators: 'ValidatorListDict') -> 'ValidatorListDict':
+    for field, field_validators in base_validators.items():
+        if field not in validators:
+            validators[field] = []
+        validators[field] += field_validators
+    return validators
+
+
+def make_generic_validator(validator: AnyCallable) -> 'ValidatorCallable':
+    """
+    Make a generic function which calls a validator with the right arguments.
+
+    Unfortunately other approaches (eg. return a partial of a function that builds the arguments) is slow,
+    hence this laborious way of doing things.
+
+    It's done like this so validators don't all need **kwargs in their signature, eg. any combination of
+    the arguments "values", "fields" and/or "config" are permitted.
+    """
+    from inspect import signature
+
+    if not isinstance(validator, (partial, partialmethod)):
+        # This should be the default case, so overhead is reduced
+        sig = signature(validator)
+        args = list(sig.parameters.keys())
+    else:
+        # Fix the generated argument lists of partial methods
+        sig = signature(validator.func)
+        args = [
+            k
+            for k in signature(validator.func).parameters.keys()
+            if k not in validator.args | validator.keywords.keys()
+        ]
+
+    first_arg = args.pop(0)
+    if first_arg == 'self':
+        raise ConfigError(
+            f'Invalid signature for validator {validator}: {sig}, "self" not permitted as first argument, '
+            f'should be: (cls, value, values, config, field), "values", "config" and "field" are all optional.'
+        )
+    elif first_arg == 'cls':
+        # assume the second argument is value
+        return wraps(validator)(_generic_validator_cls(validator, sig, set(args[1:])))
+    else:
+        # assume the first argument was value which has already been removed
+        return wraps(validator)(_generic_validator_basic(validator, sig, set(args)))
+
+
+def prep_validators(v_funcs: Iterable[AnyCallable]) -> 'ValidatorsList':
+    return [make_generic_validator(f) for f in v_funcs if f]
+
+
+all_kwargs = {'values', 'field', 'config'}
+
+
+def _generic_validator_cls(validator: AnyCallable, sig: 'Signature', args: Set[str]) -> 'ValidatorCallable':
+    # assume the first argument is value
+    has_kwargs = False
+    if 'kwargs' in args:
+        has_kwargs = True
+        args -= {'kwargs'}
+
+    if not args.issubset(all_kwargs):
+        raise ConfigError(
+            f'Invalid signature for validator {validator}: {sig}, should be: '
+            f'(cls, value, values, config, field), "values", "config" and "field" are all optional.'
+        )
+
+    if has_kwargs:
+        return lambda cls, v, values, field, config: validator(cls, v, values=values, field=field, config=config)
+    elif args == set():
+        return lambda cls, v, values, field, config: validator(cls, v)
+    elif args == {'values'}:
+        return lambda cls, v, values, field, config: validator(cls, v, values=values)
+    elif args == {'field'}:
+        return lambda cls, v, values, field, config: validator(cls, v, field=field)
+    elif args == {'config'}:
+        return lambda cls, v, values, field, config: validator(cls, v, config=config)
+    elif args == {'values', 'field'}:
+        return lambda cls, v, values, field, config: validator(cls, v, values=values, field=field)
+    elif args == {'values', 'config'}:
+        return lambda cls, v, values, field, config: validator(cls, v, values=values, config=config)
+    elif args == {'field', 'config'}:
+        return lambda cls, v, values, field, config: validator(cls, v, field=field, config=config)
+    else:
+        # args == {'values', 'field', 'config'}
+        return lambda cls, v, values, field, config: validator(cls, v, values=values, field=field, config=config)
+
+
+def _generic_validator_basic(validator: AnyCallable, sig: 'Signature', args: Set[str]) -> 'ValidatorCallable':
+    has_kwargs = False
+    if 'kwargs' in args:
+        has_kwargs = True
+        args -= {'kwargs'}
+
+    if not args.issubset(all_kwargs):
+        raise ConfigError(
+            f'Invalid signature for validator {validator}: {sig}, should be: '
+            f'(value, values, config, field), "values", "config" and "field" are all optional.'
+        )
+
+    if has_kwargs:
+        return lambda cls, v, values, field, config: validator(v, values=values, field=field, config=config)
+    elif args == set():
+        return lambda cls, v, values, field, config: validator(v)
+    elif args == {'values'}:
+        return lambda cls, v, values, field, config: validator(v, values=values)
+    elif args == {'field'}:
+        return lambda cls, v, values, field, config: validator(v, field=field)
+    elif args == {'config'}:
+        return lambda cls, v, values, field, config: validator(v, config=config)
+    elif args == {'values', 'field'}:
+        return lambda cls, v, values, field, config: validator(v, values=values, field=field)
+    elif args == {'values', 'config'}:
+        return lambda cls, v, values, field, config: validator(v, values=values, config=config)
+    elif args == {'field', 'config'}:
+        return lambda cls, v, values, field, config: validator(v, field=field, config=config)
+    else:
+        # args == {'values', 'field', 'config'}
+        return lambda cls, v, values, field, config: validator(v, values=values, field=field, config=config)
+
+
+def gather_all_validators(type_: 'ModelOrDc') -> Dict[str, 'AnyClassMethod']:
+    all_attributes = ChainMap(*[cls.__dict__ for cls in type_.__mro__])  # type: ignore[arg-type,var-annotated]
+    return {
+        k: v
+        for k, v in all_attributes.items()
+        if hasattr(v, VALIDATOR_CONFIG_KEY) or hasattr(v, ROOT_VALIDATOR_CONFIG_KEY)
+    }

venv/Lib/site-packages/pydantic/v1/color.py

@@ -0,0 +1,494 @@
+"""
+Color definitions are  used as per CSS3 specification:
+http://www.w3.org/TR/css3-color/#svg-color
+
+A few colors have multiple names referring to the sames colors, eg. `grey` and `gray` or `aqua` and `cyan`.
+
+In these cases the LAST color when sorted alphabetically takes preferences,
+eg. Color((0, 255, 255)).as_named() == 'cyan' because "cyan" comes after "aqua".
+"""
+import math
+import re
+from colorsys import hls_to_rgb, rgb_to_hls
+from typing import TYPE_CHECKING, Any, Dict, Optional, Tuple, Union, cast
+
+from pydantic.v1.errors import ColorError
+from pydantic.v1.utils import Representation, almost_equal_floats
+
+if TYPE_CHECKING:
+    from pydantic.v1.typing import CallableGenerator, ReprArgs
+
+ColorTuple = Union[Tuple[int, int, int], Tuple[int, int, int, float]]
+ColorType = Union[ColorTuple, str]
+HslColorTuple = Union[Tuple[float, float, float], Tuple[float, float, float, float]]
+
+
+class RGBA:
+    """
+    Internal use only as a representation of a color.
+    """
+
+    __slots__ = 'r', 'g', 'b', 'alpha', '_tuple'
+
+    def __init__(self, r: float, g: float, b: float, alpha: Optional[float]):
+        self.r = r
+        self.g = g
+        self.b = b
+        self.alpha = alpha
+
+        self._tuple: Tuple[float, float, float, Optional[float]] = (r, g, b, alpha)
+
+    def __getitem__(self, item: Any) -> Any:
+        return self._tuple[item]
+
+
+# these are not compiled here to avoid import slowdown, they'll be compiled the first time they're used, then cached
+r_hex_short = r'\s*(?:#|0x)?([0-9a-f])([0-9a-f])([0-9a-f])([0-9a-f])?\s*'
+r_hex_long = r'\s*(?:#|0x)?([0-9a-f]{2})([0-9a-f]{2})([0-9a-f]{2})([0-9a-f]{2})?\s*'
+_r_255 = r'(\d{1,3}(?:\.\d+)?)'
+_r_comma = r'\s*,\s*'
+r_rgb = fr'\s*rgb\(\s*{_r_255}{_r_comma}{_r_255}{_r_comma}{_r_255}\)\s*'
+_r_alpha = r'(\d(?:\.\d+)?|\.\d+|\d{1,2}%)'
+r_rgba = fr'\s*rgba\(\s*{_r_255}{_r_comma}{_r_255}{_r_comma}{_r_255}{_r_comma}{_r_alpha}\s*\)\s*'
+_r_h = r'(-?\d+(?:\.\d+)?|-?\.\d+)(deg|rad|turn)?'
+_r_sl = r'(\d{1,3}(?:\.\d+)?)%'
+r_hsl = fr'\s*hsl\(\s*{_r_h}{_r_comma}{_r_sl}{_r_comma}{_r_sl}\s*\)\s*'
+r_hsla = fr'\s*hsl\(\s*{_r_h}{_r_comma}{_r_sl}{_r_comma}{_r_sl}{_r_comma}{_r_alpha}\s*\)\s*'
+
+# colors where the two hex characters are the same, if all colors match this the short version of hex colors can be used
+repeat_colors = {int(c * 2, 16) for c in '0123456789abcdef'}
+rads = 2 * math.pi
+
+
+class Color(Representation):
+    __slots__ = '_original', '_rgba'
+
+    def __init__(self, value: ColorType) -> None:
+        self._rgba: RGBA
+        self._original: ColorType
+        if isinstance(value, (tuple, list)):
+            self._rgba = parse_tuple(value)
+        elif isinstance(value, str):
+            self._rgba = parse_str(value)
+        elif isinstance(value, Color):
+            self._rgba = value._rgba
+            value = value._original
+        else:
+            raise ColorError(reason='value must be a tuple, list or string')
+
+        # if we've got here value must be a valid color
+        self._original = value
+
+    @classmethod
+    def __modify_schema__(cls, field_schema: Dict[str, Any]) -> None:
+        field_schema.update(type='string', format='color')
+
+    def original(self) -> ColorType:
+        """
+        Original value passed to Color
+        """
+        return self._original
+
+    def as_named(self, *, fallback: bool = False) -> str:
+        if self._rgba.alpha is None:
+            rgb = cast(Tuple[int, int, int], self.as_rgb_tuple())
+            try:
+                return COLORS_BY_VALUE[rgb]
+            except KeyError as e:
+                if fallback:
+                    return self.as_hex()
+                else:
+                    raise ValueError('no named color found, use fallback=True, as_hex() or as_rgb()') from e
+        else:
+            return self.as_hex()
+
+    def as_hex(self) -> str:
+        """
+        Hex string representing the color can be 3, 4, 6 or 8 characters depending on whether the string
+        a "short" representation of the color is possible and whether there's an alpha channel.
+        """
+        values = [float_to_255(c) for c in self._rgba[:3]]
+        if self._rgba.alpha is not None:
+            values.append(float_to_255(self._rgba.alpha))
+
+        as_hex = ''.join(f'{v:02x}' for v in values)
+        if all(c in repeat_colors for c in values):
+            as_hex = ''.join(as_hex[c] for c in range(0, len(as_hex), 2))
+        return '#' + as_hex
+
+    def as_rgb(self) -> str:
+        """
+        Color as an rgb(<r>, <g>, <b>) or rgba(<r>, <g>, <b>, <a>) string.
+        """
+        if self._rgba.alpha is None:
+            return f'rgb({float_to_255(self._rgba.r)}, {float_to_255(self._rgba.g)}, {float_to_255(self._rgba.b)})'
+        else:
+            return (
+                f'rgba({float_to_255(self._rgba.r)}, {float_to_255(self._rgba.g)}, {float_to_255(self._rgba.b)}, '
+                f'{round(self._alpha_float(), 2)})'
+            )
+
+    def as_rgb_tuple(self, *, alpha: Optional[bool] = None) -> ColorTuple:
+        """
+        Color as an RGB or RGBA tuple; red, green and blue are in the range 0 to 255, alpha if included is
+        in the range 0 to 1.
+
+        :param alpha: whether to include the alpha channel, options are
+          None - (default) include alpha only if it's set (e.g. not None)
+          True - always include alpha,
+          False - always omit alpha,
+        """
+        r, g, b = (float_to_255(c) for c in self._rgba[:3])
+        if alpha is None:
+            if self._rgba.alpha is None:
+                return r, g, b
+            else:
+                return r, g, b, self._alpha_float()
+        elif alpha:
+            return r, g, b, self._alpha_float()
+        else:
+            # alpha is False
+            return r, g, b
+
+    def as_hsl(self) -> str:
+        """
+        Color as an hsl(<h>, <s>, <l>) or hsl(<h>, <s>, <l>, <a>) string.
+        """
+        if self._rgba.alpha is None:
+            h, s, li = self.as_hsl_tuple(alpha=False)  # type: ignore
+            return f'hsl({h * 360:0.0f}, {s:0.0%}, {li:0.0%})'
+        else:
+            h, s, li, a = self.as_hsl_tuple(alpha=True)  # type: ignore
+            return f'hsl({h * 360:0.0f}, {s:0.0%}, {li:0.0%}, {round(a, 2)})'
+
+    def as_hsl_tuple(self, *, alpha: Optional[bool] = None) -> HslColorTuple:
+        """
+        Color as an HSL or HSLA tuple, e.g. hue, saturation, lightness and optionally alpha; all elements are in
+        the range 0 to 1.
+
+        NOTE: this is HSL as used in HTML and most other places, not HLS as used in python's colorsys.
+
+        :param alpha: whether to include the alpha channel, options are
+          None - (default) include alpha only if it's set (e.g. not None)
+          True - always include alpha,
+          False - always omit alpha,
+        """
+        h, l, s = rgb_to_hls(self._rgba.r, self._rgba.g, self._rgba.b)
+        if alpha is None:
+            if self._rgba.alpha is None:
+                return h, s, l
+            else:
+                return h, s, l, self._alpha_float()
+        if alpha:
+            return h, s, l, self._alpha_float()
+        else:
+            # alpha is False
+            return h, s, l
+
+    def _alpha_float(self) -> float:
+        return 1 if self._rgba.alpha is None else self._rgba.alpha
+
+    @classmethod
+    def __get_validators__(cls) -> 'CallableGenerator':
+        yield cls
+
+    def __str__(self) -> str:
+        return self.as_named(fallback=True)
+
+    def __repr_args__(self) -> 'ReprArgs':
+        return [(None, self.as_named(fallback=True))] + [('rgb', self.as_rgb_tuple())]  # type: ignore
+
+    def __eq__(self, other: Any) -> bool:
+        return isinstance(other, Color) and self.as_rgb_tuple() == other.as_rgb_tuple()
+
+    def __hash__(self) -> int:
+        return hash(self.as_rgb_tuple())
+
+
+def parse_tuple(value: Tuple[Any, ...]) -> RGBA:
+    """
+    Parse a tuple or list as a color.
+    """
+    if len(value) == 3:
+        r, g, b = (parse_color_value(v) for v in value)
+        return RGBA(r, g, b, None)
+    elif len(value) == 4:
+        r, g, b = (parse_color_value(v) for v in value[:3])
+        return RGBA(r, g, b, parse_float_alpha(value[3]))
+    else:
+        raise ColorError(reason='tuples must have length 3 or 4')
+
+
+def parse_str(value: str) -> RGBA:
+    """
+    Parse a string to an RGBA tuple, trying the following formats (in this order):
+    * named color, see COLORS_BY_NAME below
+    * hex short eg. `<prefix>fff` (prefix can be `#`, `0x` or nothing)
+    * hex long eg. `<prefix>ffffff` (prefix can be `#`, `0x` or nothing)
+    * `rgb(<r>, <g>, <b>) `
+    * `rgba(<r>, <g>, <b>, <a>)`
+    """
+    value_lower = value.lower()
+    try:
+        r, g, b = COLORS_BY_NAME[value_lower]
+    except KeyError:
+        pass
+    else:
+        return ints_to_rgba(r, g, b, None)
+
+    m = re.fullmatch(r_hex_short, value_lower)
+    if m:
+        *rgb, a = m.groups()
+        r, g, b = (int(v * 2, 16) for v in rgb)
+        if a:
+            alpha: Optional[float] = int(a * 2, 16) / 255
+        else:
+            alpha = None
+        return ints_to_rgba(r, g, b, alpha)
+
+    m = re.fullmatch(r_hex_long, value_lower)
+    if m:
+        *rgb, a = m.groups()
+        r, g, b = (int(v, 16) for v in rgb)
+        if a:
+            alpha = int(a, 16) / 255
+        else:
+            alpha = None
+        return ints_to_rgba(r, g, b, alpha)
+
+    m = re.fullmatch(r_rgb, value_lower)
+    if m:
+        return ints_to_rgba(*m.groups(), None)  # type: ignore
+
+    m = re.fullmatch(r_rgba, value_lower)
+    if m:
+        return ints_to_rgba(*m.groups())  # type: ignore
+
+    m = re.fullmatch(r_hsl, value_lower)
+    if m:
+        h, h_units, s, l_ = m.groups()
+        return parse_hsl(h, h_units, s, l_)
+
+    m = re.fullmatch(r_hsla, value_lower)
+    if m:
+        h, h_units, s, l_, a = m.groups()
+        return parse_hsl(h, h_units, s, l_, parse_float_alpha(a))
+
+    raise ColorError(reason='string not recognised as a valid color')
+
+
+def ints_to_rgba(r: Union[int, str], g: Union[int, str], b: Union[int, str], alpha: Optional[float]) -> RGBA:
+    return RGBA(parse_color_value(r), parse_color_value(g), parse_color_value(b), parse_float_alpha(alpha))
+
+
+def parse_color_value(value: Union[int, str], max_val: int = 255) -> float:
+    """
+    Parse a value checking it's a valid int in the range 0 to max_val and divide by max_val to give a number
+    in the range 0 to 1
+    """
+    try:
+        color = float(value)
+    except ValueError:
+        raise ColorError(reason='color values must be a valid number')
+    if 0 <= color <= max_val:
+        return color / max_val
+    else:
+        raise ColorError(reason=f'color values must be in the range 0 to {max_val}')
+
+
+def parse_float_alpha(value: Union[None, str, float, int]) -> Optional[float]:
+    """
+    Parse a value checking it's a valid float in the range 0 to 1
+    """
+    if value is None:
+        return None
+    try:
+        if isinstance(value, str) and value.endswith('%'):
+            alpha = float(value[:-1]) / 100
+        else:
+            alpha = float(value)
+    except ValueError:
+        raise ColorError(reason='alpha values must be a valid float')
+
+    if almost_equal_floats(alpha, 1):
+        return None
+    elif 0 <= alpha <= 1:
+        return alpha
+    else:
+        raise ColorError(reason='alpha values must be in the range 0 to 1')
+
+
+def parse_hsl(h: str, h_units: str, sat: str, light: str, alpha: Optional[float] = None) -> RGBA:
+    """
+    Parse raw hue, saturation, lightness and alpha values and convert to RGBA.
+    """
+    s_value, l_value = parse_color_value(sat, 100), parse_color_value(light, 100)
+
+    h_value = float(h)
+    if h_units in {None, 'deg'}:
+        h_value = h_value % 360 / 360
+    elif h_units == 'rad':
+        h_value = h_value % rads / rads
+    else:
+        # turns
+        h_value = h_value % 1
+
+    r, g, b = hls_to_rgb(h_value, l_value, s_value)
+    return RGBA(r, g, b, alpha)
+
+
+def float_to_255(c: float) -> int:
+    return int(round(c * 255))
+
+
+COLORS_BY_NAME = {
+    'aliceblue': (240, 248, 255),
+    'antiquewhite': (250, 235, 215),
+    'aqua': (0, 255, 255),
+    'aquamarine': (127, 255, 212),
+    'azure': (240, 255, 255),
+    'beige': (245, 245, 220),
+    'bisque': (255, 228, 196),
+    'black': (0, 0, 0),
+    'blanchedalmond': (255, 235, 205),
+    'blue': (0, 0, 255),
+    'blueviolet': (138, 43, 226),
+    'brown': (165, 42, 42),
+    'burlywood': (222, 184, 135),
+    'cadetblue': (95, 158, 160),
+    'chartreuse': (127, 255, 0),
+    'chocolate': (210, 105, 30),
+    'coral': (255, 127, 80),
+    'cornflowerblue': (100, 149, 237),
+    'cornsilk': (255, 248, 220),
+    'crimson': (220, 20, 60),
+    'cyan': (0, 255, 255),
+    'darkblue': (0, 0, 139),
+    'darkcyan': (0, 139, 139),
+    'darkgoldenrod': (184, 134, 11),
+    'darkgray': (169, 169, 169),
+    'darkgreen': (0, 100, 0),
+    'darkgrey': (169, 169, 169),
+    'darkkhaki': (189, 183, 107),
+    'darkmagenta': (139, 0, 139),
+    'darkolivegreen': (85, 107, 47),
+    'darkorange': (255, 140, 0),
+    'darkorchid': (153, 50, 204),
+    'darkred': (139, 0, 0),
+    'darksalmon': (233, 150, 122),
+    'darkseagreen': (143, 188, 143),
+    'darkslateblue': (72, 61, 139),
+    'darkslategray': (47, 79, 79),
+    'darkslategrey': (47, 79, 79),
+    'darkturquoise': (0, 206, 209),
+    'darkviolet': (148, 0, 211),
+    'deeppink': (255, 20, 147),
+    'deepskyblue': (0, 191, 255),
+    'dimgray': (105, 105, 105),
+    'dimgrey': (105, 105, 105),
+    'dodgerblue': (30, 144, 255),
+    'firebrick': (178, 34, 34),
+    'floralwhite': (255, 250, 240),
+    'forestgreen': (34, 139, 34),
+    'fuchsia': (255, 0, 255),
+    'gainsboro': (220, 220, 220),
+    'ghostwhite': (248, 248, 255),
+    'gold': (255, 215, 0),
+    'goldenrod': (218, 165, 32),
+    'gray': (128, 128, 128),
+    'green': (0, 128, 0),
+    'greenyellow': (173, 255, 47),
+    'grey': (128, 128, 128),
+    'honeydew': (240, 255, 240),
+    'hotpink': (255, 105, 180),
+    'indianred': (205, 92, 92),
+    'indigo': (75, 0, 130),
+    'ivory': (255, 255, 240),
+    'khaki': (240, 230, 140),
+    'lavender': (230, 230, 250),
+    'lavenderblush': (255, 240, 245),
+    'lawngreen': (124, 252, 0),
+    'lemonchiffon': (255, 250, 205),
+    'lightblue': (173, 216, 230),
+    'lightcoral': (240, 128, 128),
+    'lightcyan': (224, 255, 255),
+    'lightgoldenrodyellow': (250, 250, 210),
+    'lightgray': (211, 211, 211),
+    'lightgreen': (144, 238, 144),
+    'lightgrey': (211, 211, 211),
+    'lightpink': (255, 182, 193),
+    'lightsalmon': (255, 160, 122),
+    'lightseagreen': (32, 178, 170),
+    'lightskyblue': (135, 206, 250),
+    'lightslategray': (119, 136, 153),
+    'lightslategrey': (119, 136, 153),
+    'lightsteelblue': (176, 196, 222),
+    'lightyellow': (255, 255, 224),
+    'lime': (0, 255, 0),
+    'limegreen': (50, 205, 50),
+    'linen': (250, 240, 230),
+    'magenta': (255, 0, 255),
+    'maroon': (128, 0, 0),
+    'mediumaquamarine': (102, 205, 170),
+    'mediumblue': (0, 0, 205),
+    'mediumorchid': (186, 85, 211),
+    'mediumpurple': (147, 112, 219),
+    'mediumseagreen': (60, 179, 113),
+    'mediumslateblue': (123, 104, 238),
+    'mediumspringgreen': (0, 250, 154),
+    'mediumturquoise': (72, 209, 204),
+    'mediumvioletred': (199, 21, 133),
+    'midnightblue': (25, 25, 112),
+    'mintcream': (245, 255, 250),
+    'mistyrose': (255, 228, 225),
+    'moccasin': (255, 228, 181),
+    'navajowhite': (255, 222, 173),
+    'navy': (0, 0, 128),
+    'oldlace': (253, 245, 230),
+    'olive': (128, 128, 0),
+    'olivedrab': (107, 142, 35),
+    'orange': (255, 165, 0),
+    'orangered': (255, 69, 0),
+    'orchid': (218, 112, 214),
+    'palegoldenrod': (238, 232, 170),
+    'palegreen': (152, 251, 152),
+    'paleturquoise': (175, 238, 238),
+    'palevioletred': (219, 112, 147),
+    'papayawhip': (255, 239, 213),
+    'peachpuff': (255, 218, 185),
+    'peru': (205, 133, 63),
+    'pink': (255, 192, 203),
+    'plum': (221, 160, 221),
+    'powderblue': (176, 224, 230),
+    'purple': (128, 0, 128),
+    'red': (255, 0, 0),
+    'rosybrown': (188, 143, 143),
+    'royalblue': (65, 105, 225),
+    'saddlebrown': (139, 69, 19),
+    'salmon': (250, 128, 114),
+    'sandybrown': (244, 164, 96),
+    'seagreen': (46, 139, 87),
+    'seashell': (255, 245, 238),
+    'sienna': (160, 82, 45),
+    'silver': (192, 192, 192),
+    'skyblue': (135, 206, 235),
+    'slateblue': (106, 90, 205),
+    'slategray': (112, 128, 144),
+    'slategrey': (112, 128, 144),
+    'snow': (255, 250, 250),
+    'springgreen': (0, 255, 127),
+    'steelblue': (70, 130, 180),
+    'tan': (210, 180, 140),
+    'teal': (0, 128, 128),
+    'thistle': (216, 191, 216),
+    'tomato': (255, 99, 71),
+    'turquoise': (64, 224, 208),
+    'violet': (238, 130, 238),
+    'wheat': (245, 222, 179),
+    'white': (255, 255, 255),
+    'whitesmoke': (245, 245, 245),
+    'yellow': (255, 255, 0),
+    'yellowgreen': (154, 205, 50),
+}
+
+COLORS_BY_VALUE = {v: k for k, v in COLORS_BY_NAME.items()}