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

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

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+"""`class_validators` module is a backport module from V1."""
+
+from ._migration import getattr_migration
+
+__getattr__ = getattr_migration(__name__)

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

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+"""Color definitions are used as per the CSS3
+[CSS Color Module Level 3](http://www.w3.org/TR/css3-color/#svg-color) specification.
+
+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".
+
+Warning: Deprecated
+    The `Color` class is deprecated, use `pydantic_extra_types` instead.
+    See [`pydantic-extra-types.Color`](../usage/types/extra_types/color_types.md)
+    for more information.
+"""
+
+import math
+import re
+from colorsys import hls_to_rgb, rgb_to_hls
+from typing import Any, Callable, Optional, Union, cast
+
+from pydantic_core import CoreSchema, PydanticCustomError, core_schema
+from typing_extensions import deprecated
+
+from ._internal import _repr
+from ._internal._schema_generation_shared import GetJsonSchemaHandler as _GetJsonSchemaHandler
+from .json_schema import JsonSchemaValue
+from .warnings import PydanticDeprecatedSince20
+
+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_255 = r'(\d{1,3}(?:\.\d+)?)'
+_r_comma = r'\s*,\s*'
+_r_alpha = r'(\d(?:\.\d+)?|\.\d+|\d{1,2}%)'
+_r_h = r'(-?\d+(?:\.\d+)?|-?\.\d+)(deg|rad|turn)?'
+_r_sl = r'(\d{1,3}(?:\.\d+)?)%'
+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*'
+# CSS3 RGB examples: rgb(0, 0, 0), rgba(0, 0, 0, 0.5), rgba(0, 0, 0, 50%)
+r_rgb = rf'\s*rgba?\(\s*{_r_255}{_r_comma}{_r_255}{_r_comma}{_r_255}(?:{_r_comma}{_r_alpha})?\s*\)\s*'
+# CSS3 HSL examples: hsl(270, 60%, 50%), hsla(270, 60%, 50%, 0.5), hsla(270, 60%, 50%, 50%)
+r_hsl = rf'\s*hsla?\(\s*{_r_h}{_r_comma}{_r_sl}{_r_comma}{_r_sl}(?:{_r_comma}{_r_alpha})?\s*\)\s*'
+# CSS4 RGB examples: rgb(0 0 0), rgb(0 0 0 / 0.5), rgb(0 0 0 / 50%), rgba(0 0 0 / 50%)
+r_rgb_v4_style = rf'\s*rgba?\(\s*{_r_255}\s+{_r_255}\s+{_r_255}(?:\s*/\s*{_r_alpha})?\s*\)\s*'
+# CSS4 HSL examples: hsl(270 60% 50%), hsl(270 60% 50% / 0.5), hsl(270 60% 50% / 50%), hsla(270 60% 50% / 50%)
+r_hsl_v4_style = rf'\s*hsla?\(\s*{_r_h}\s+{_r_sl}\s+{_r_sl}(?:\s*/\s*{_r_alpha})?\s*\)\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
+
+
+@deprecated(
+    'The `Color` class is deprecated, use `pydantic_extra_types` instead. '
+    'See https://docs.pydantic.dev/latest/api/pydantic_extra_types_color/.',
+    category=PydanticDeprecatedSince20,
+)
+class Color(_repr.Representation):
+    """Represents a color."""
+
+    __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 PydanticCustomError(
+                'color_error', 'value is not a valid color: value must be a tuple, list or string'
+            )
+
+        # if we've got here value must be a valid color
+        self._original = value
+
+    @classmethod
+    def __get_pydantic_json_schema__(
+        cls, core_schema: core_schema.CoreSchema, handler: _GetJsonSchemaHandler
+    ) -> JsonSchemaValue:
+        field_schema = {}
+        field_schema.update(type='string', format='color')
+        return field_schema
+
+    def original(self) -> ColorType:
+        """Original value passed to `Color`."""
+        return self._original
+
+    def as_named(self, *, fallback: bool = False) -> str:
+        """Returns the name of the color if it can be found in `COLORS_BY_VALUE` dictionary,
+        otherwise returns the hexadecimal representation of the color or raises `ValueError`.
+
+        Args:
+            fallback: If True, falls back to returning the hexadecimal representation of
+                the color instead of raising a ValueError when no named color is found.
+
+        Returns:
+            The name of the color, or the hexadecimal representation of the color.
+
+        Raises:
+            ValueError: When no named color is found and fallback is `False`.
+        """
+        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:
+        """Returns the hexadecimal representation of the color.
+
+        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.
+
+        Returns:
+            The hexadecimal representation of the color.
+        """
+        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:
+        """Returns the color as an RGB or RGBA tuple.
+
+        Args:
+            alpha: Whether to include the alpha channel. There are three options for this input:
+
+                - `None` (default): Include alpha only if it's set. (e.g. not `None`)
+                - `True`: Always include alpha.
+                - `False`: Always omit alpha.
+
+        Returns:
+            A tuple that contains the values of the red, green, and blue channels in the range 0 to 255.
+                If alpha is included, it is in the range 0 to 1.
+        """
+        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:
+        """Returns the color as an HSL or HSLA tuple.
+
+        Args:
+            alpha: Whether to include the alpha channel.
+
+                - `None` (default): Include the alpha channel only if it's set (e.g. not `None`).
+                - `True`: Always include alpha.
+                - `False`: Always omit alpha.
+
+        Returns:
+            The color as a tuple of hue, saturation, lightness, and alpha (if included).
+                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`.
+        """
+        h, l, s = rgb_to_hls(self._rgba.r, self._rgba.g, self._rgba.b)  # noqa: E741
+        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_pydantic_core_schema__(
+        cls, source: type[Any], handler: Callable[[Any], CoreSchema]
+    ) -> core_schema.CoreSchema:
+        return core_schema.with_info_plain_validator_function(
+            cls._validate, serialization=core_schema.to_string_ser_schema()
+        )
+
+    @classmethod
+    def _validate(cls, __input_value: Any, _: Any) -> 'Color':
+        return cls(__input_value)
+
+    def __str__(self) -> str:
+        return self.as_named(fallback=True)
+
+    def __repr_args__(self) -> '_repr.ReprArgs':
+        return [(None, self.as_named(fallback=True))] + [('rgb', self.as_rgb_tuple())]
+
+    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 to get RGBA values.
+
+    Args:
+        value: A tuple or list.
+
+    Returns:
+        An `RGBA` tuple parsed from the input tuple.
+
+    Raises:
+        PydanticCustomError: If tuple is not valid.
+    """
+    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 PydanticCustomError('color_error', 'value is not a valid color: tuples must have length 3 or 4')
+
+
+def parse_str(value: str) -> RGBA:
+    """Parse a string representing a color to an RGBA tuple.
+
+    Possible formats for the input string include:
+
+    * named color, see `COLORS_BY_NAME`
+    * 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>)`
+
+    Args:
+        value: A string representing a color.
+
+    Returns:
+        An `RGBA` tuple parsed from the input string.
+
+    Raises:
+        ValueError: If the input string cannot be parsed to an RGBA tuple.
+    """
+    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) or re.fullmatch(r_rgb_v4_style, value_lower)
+    if m:
+        return ints_to_rgba(*m.groups())  # type: ignore
+
+    m = re.fullmatch(r_hsl, value_lower) or re.fullmatch(r_hsl_v4_style, value_lower)
+    if m:
+        return parse_hsl(*m.groups())  # type: ignore
+
+    raise PydanticCustomError('color_error', 'value is not a valid color: 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] = None) -> RGBA:
+    """Converts integer or string values for RGB color and an optional alpha value to an `RGBA` object.
+
+    Args:
+        r: An integer or string representing the red color value.
+        g: An integer or string representing the green color value.
+        b: An integer or string representing the blue color value.
+        alpha: A float representing the alpha value. Defaults to None.
+
+    Returns:
+        An instance of the `RGBA` class with the corresponding color and alpha values.
+    """
+    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 the color value provided and return a number between 0 and 1.
+
+    Args:
+        value: An integer or string color value.
+        max_val: Maximum range value. Defaults to 255.
+
+    Raises:
+        PydanticCustomError: If the value is not a valid color.
+
+    Returns:
+        A number between 0 and 1.
+    """
+    try:
+        color = float(value)
+    except ValueError:
+        raise PydanticCustomError('color_error', 'value is not a valid color: color values must be a valid number')
+    if 0 <= color <= max_val:
+        return color / max_val
+    else:
+        raise PydanticCustomError(
+            'color_error',
+            'value is not a valid color: color values must be in the range 0 to {max_val}',
+            {'max_val': max_val},
+        )
+
+
+def parse_float_alpha(value: Union[None, str, float, int]) -> Optional[float]:
+    """Parse an alpha value checking it's a valid float in the range 0 to 1.
+
+    Args:
+        value: The input value to parse.
+
+    Returns:
+        The parsed value as a float, or `None` if the value was None or equal 1.
+
+    Raises:
+        PydanticCustomError: If the input value cannot be successfully parsed as a float in the expected range.
+    """
+    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 PydanticCustomError('color_error', 'value is not a valid color: alpha values must be a valid float')
+
+    if math.isclose(alpha, 1):
+        return None
+    elif 0 <= alpha <= 1:
+        return alpha
+    else:
+        raise PydanticCustomError('color_error', 'value is not a valid color: 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.
+
+    Args:
+        h: The hue value.
+        h_units: The unit for hue value.
+        sat: The saturation value.
+        light: The lightness value.
+        alpha: Alpha value.
+
+    Returns:
+        An instance of `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, parse_float_alpha(alpha))
+
+
+def float_to_255(c: float) -> int:
+    """Converts a float value between 0 and 1 (inclusive) to an integer between 0 and 255 (inclusive).
+
+    Args:
+        c: The float value to be converted. Must be between 0 and 1 (inclusive).
+
+    Returns:
+        The integer equivalent of the given float value rounded to the nearest whole number.
+
+    Raises:
+        ValueError: If the given float value is outside the acceptable range of 0 to 1 (inclusive).
+    """
+    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()}

venv/Lib/site-packages/pydantic/dataclasses.py

@@ -0,0 +1,413 @@
+"""Provide an enhanced dataclass that performs validation."""
+
+from __future__ import annotations as _annotations
+
+import dataclasses
+import functools
+import sys
+import types
+from typing import TYPE_CHECKING, Any, Callable, Generic, Literal, NoReturn, TypeVar, overload
+from warnings import warn
+
+from typing_extensions import TypeGuard, dataclass_transform
+
+from ._internal import _config, _decorators, _mock_val_ser, _namespace_utils, _typing_extra
+from ._internal import _dataclasses as _pydantic_dataclasses
+from ._migration import getattr_migration
+from .config import ConfigDict
+from .errors import PydanticUserError
+from .fields import Field, FieldInfo, PrivateAttr
+
+if TYPE_CHECKING:
+    from ._internal._dataclasses import PydanticDataclass
+    from ._internal._namespace_utils import MappingNamespace
+
+__all__ = 'dataclass', 'rebuild_dataclass'
+
+_T = TypeVar('_T')
+
+if sys.version_info >= (3, 10):
+
+    @dataclass_transform(field_specifiers=(dataclasses.field, Field, PrivateAttr))
+    @overload
+    def dataclass(
+        *,
+        init: Literal[False] = False,
+        repr: bool = True,
+        eq: bool = True,
+        order: bool = False,
+        unsafe_hash: bool = False,
+        frozen: bool = False,
+        config: ConfigDict | type[object] | None = None,
+        validate_on_init: bool | None = None,
+        kw_only: bool = ...,
+        slots: bool = ...,
+    ) -> Callable[[type[_T]], type[PydanticDataclass]]:  # type: ignore
+        ...
+
+    @dataclass_transform(field_specifiers=(dataclasses.field, Field, PrivateAttr))
+    @overload
+    def dataclass(
+        _cls: type[_T],  # type: ignore
+        *,
+        init: Literal[False] = False,
+        repr: bool = True,
+        eq: bool = True,
+        order: bool = False,
+        unsafe_hash: bool = False,
+        frozen: bool | None = None,
+        config: ConfigDict | type[object] | None = None,
+        validate_on_init: bool | None = None,
+        kw_only: bool = ...,
+        slots: bool = ...,
+    ) -> type[PydanticDataclass]: ...
+
+else:
+
+    @dataclass_transform(field_specifiers=(dataclasses.field, Field, PrivateAttr))
+    @overload
+    def dataclass(
+        *,
+        init: Literal[False] = False,
+        repr: bool = True,
+        eq: bool = True,
+        order: bool = False,
+        unsafe_hash: bool = False,
+        frozen: bool | None = None,
+        config: ConfigDict | type[object] | None = None,
+        validate_on_init: bool | None = None,
+    ) -> Callable[[type[_T]], type[PydanticDataclass]]:  # type: ignore
+        ...
+
+    @dataclass_transform(field_specifiers=(dataclasses.field, Field, PrivateAttr))
+    @overload
+    def dataclass(
+        _cls: type[_T],  # type: ignore
+        *,
+        init: Literal[False] = False,
+        repr: bool = True,
+        eq: bool = True,
+        order: bool = False,
+        unsafe_hash: bool = False,
+        frozen: bool | None = None,
+        config: ConfigDict | type[object] | None = None,
+        validate_on_init: bool | None = None,
+    ) -> type[PydanticDataclass]: ...
+
+
+@dataclass_transform(field_specifiers=(dataclasses.field, Field, PrivateAttr))
+def dataclass(
+    _cls: type[_T] | None = None,
+    *,
+    init: Literal[False] = False,
+    repr: bool = True,
+    eq: bool = True,
+    order: bool = False,
+    unsafe_hash: bool = False,
+    frozen: bool | None = None,
+    config: ConfigDict | type[object] | None = None,
+    validate_on_init: bool | None = None,
+    kw_only: bool = False,
+    slots: bool = False,
+) -> Callable[[type[_T]], type[PydanticDataclass]] | type[PydanticDataclass]:
+    """!!! abstract "Usage Documentation"
+        [`dataclasses`](../concepts/dataclasses.md)
+
+    A decorator used to create a Pydantic-enhanced dataclass, similar to the standard Python `dataclass`,
+    but with added validation.
+
+    This function should be used similarly to `dataclasses.dataclass`.
+
+    Args:
+        _cls: The target `dataclass`.
+        init: Included for signature compatibility with `dataclasses.dataclass`, and is passed through to
+            `dataclasses.dataclass` when appropriate. If specified, must be set to `False`, as pydantic inserts its
+            own  `__init__` function.
+        repr: A boolean indicating whether to include the field in the `__repr__` output.
+        eq: Determines if a `__eq__` method should be generated for the class.
+        order: Determines if comparison magic methods should be generated, such as `__lt__`, but not `__eq__`.
+        unsafe_hash: Determines if a `__hash__` method should be included in the class, as in `dataclasses.dataclass`.
+        frozen: Determines if the generated class should be a 'frozen' `dataclass`, which does not allow its
+            attributes to be modified after it has been initialized. If not set, the value from the provided `config` argument will be used (and will default to `False` otherwise).
+        config: The Pydantic config to use for the `dataclass`.
+        validate_on_init: A deprecated parameter included for backwards compatibility; in V2, all Pydantic dataclasses
+            are validated on init.
+        kw_only: Determines if `__init__` method parameters must be specified by keyword only. Defaults to `False`.
+        slots: Determines if the generated class should be a 'slots' `dataclass`, which does not allow the addition of
+            new attributes after instantiation.
+
+    Returns:
+        A decorator that accepts a class as its argument and returns a Pydantic `dataclass`.
+
+    Raises:
+        AssertionError: Raised if `init` is not `False` or `validate_on_init` is `False`.
+    """
+    assert init is False, 'pydantic.dataclasses.dataclass only supports init=False'
+    assert validate_on_init is not False, 'validate_on_init=False is no longer supported'
+
+    if sys.version_info >= (3, 10):
+        kwargs = {'kw_only': kw_only, 'slots': slots}
+    else:
+        kwargs = {}
+
+    def create_dataclass(cls: type[Any]) -> type[PydanticDataclass]:
+        """Create a Pydantic dataclass from a regular dataclass.
+
+        Args:
+            cls: The class to create the Pydantic dataclass from.
+
+        Returns:
+            A Pydantic dataclass.
+        """
+        from ._internal._utils import is_model_class
+
+        if is_model_class(cls):
+            raise PydanticUserError(
+                f'Cannot create a Pydantic dataclass from {cls.__name__} as it is already a Pydantic model',
+                code='dataclass-on-model',
+            )
+
+        original_cls = cls
+
+        # we warn on conflicting config specifications, but only if the class doesn't have a dataclass base
+        # because a dataclass base might provide a __pydantic_config__ attribute that we don't want to warn about
+        has_dataclass_base = any(dataclasses.is_dataclass(base) for base in cls.__bases__)
+        if not has_dataclass_base and config is not None and hasattr(cls, '__pydantic_config__'):
+            warn(
+                f'`config` is set via both the `dataclass` decorator and `__pydantic_config__` for dataclass {cls.__name__}. '
+                f'The `config` specification from `dataclass` decorator will take priority.',
+                category=UserWarning,
+                stacklevel=2,
+            )
+
+        # if config is not explicitly provided, try to read it from the type
+        config_dict = config if config is not None else getattr(cls, '__pydantic_config__', None)
+        config_wrapper = _config.ConfigWrapper(config_dict)
+        decorators = _decorators.DecoratorInfos.build(cls, replace_wrapped_methods=True)
+        decorators.update_from_config(config_wrapper)
+
+        # Keep track of the original __doc__ so that we can restore it after applying the dataclasses decorator
+        # Otherwise, classes with no __doc__ will have their signature added into the JSON schema description,
+        # since dataclasses.dataclass will set this as the __doc__
+        original_doc = cls.__doc__
+
+        if _pydantic_dataclasses.is_stdlib_dataclass(cls):
+            # Vanilla dataclasses include a default docstring (representing the class signature),
+            # which we don't want to preserve.
+            original_doc = None
+
+            # We don't want to add validation to the existing std lib dataclass, so we will subclass it
+            #   If the class is generic, we need to make sure the subclass also inherits from Generic
+            #   with all the same parameters.
+            bases = (cls,)
+            if issubclass(cls, Generic):
+                generic_base = Generic[cls.__parameters__]  # type: ignore
+                bases = bases + (generic_base,)
+            cls = types.new_class(cls.__name__, bases)
+
+        # Respect frozen setting from dataclass constructor and fallback to config setting if not provided
+        if frozen is not None:
+            frozen_ = frozen
+            if config_wrapper.frozen:
+                # It's not recommended to define both, as the setting from the dataclass decorator will take priority.
+                warn(
+                    f'`frozen` is set via both the `dataclass` decorator and `config` for dataclass {cls.__name__!r}.'
+                    'This is not recommended. The `frozen` specification on `dataclass` will take priority.',
+                    category=UserWarning,
+                    stacklevel=2,
+                )
+        else:
+            frozen_ = config_wrapper.frozen or False
+
+        # Make Pydantic's `Field()` function compatible with stdlib dataclasses. As we'll decorate
+        # `cls` with the stdlib `@dataclass` decorator first, there are two attributes, `kw_only` and
+        # `repr` that need to be understood *during* the stdlib creation. We do so in two steps:
+
+        # 1. On the decorated class, wrap `Field()` assignment with `dataclass.field()`, with the
+        # two attributes set (done in `as_dataclass_field()`)
+        cls_anns = _typing_extra.safe_get_annotations(cls)
+        for field_name in cls_anns:
+            # We should look for assignments in `__dict__` instead, but for now we follow
+            # the same behavior as stdlib dataclasses (see https://github.com/python/cpython/issues/88609)
+            field_value = getattr(cls, field_name, None)
+            if isinstance(field_value, FieldInfo):
+                setattr(cls, field_name, _pydantic_dataclasses.as_dataclass_field(field_value))
+
+        # 2. For bases of `cls` that are stdlib dataclasses, we temporarily patch their fields
+        # (see the docstring of the context manager):
+        with _pydantic_dataclasses.patch_base_fields(cls):
+            cls = dataclasses.dataclass(  # pyright: ignore[reportCallIssue]
+                cls,
+                # the value of init here doesn't affect anything except that it makes it easier to generate a signature
+                init=True,
+                repr=repr,
+                eq=eq,
+                order=order,
+                unsafe_hash=unsafe_hash,
+                frozen=frozen_,
+                **kwargs,
+            )
+
+        if config_wrapper.validate_assignment:
+            original_setattr = cls.__setattr__
+
+            @functools.wraps(cls.__setattr__)
+            def validated_setattr(instance: PydanticDataclass, name: str, value: Any, /) -> None:
+                if frozen_:
+                    return original_setattr(instance, name, value)  # pyright: ignore[reportCallIssue]
+                inst_cls = type(instance)
+                attr = getattr(inst_cls, name, None)
+
+                if isinstance(attr, property):
+                    attr.__set__(instance, value)
+                elif isinstance(attr, functools.cached_property):
+                    instance.__dict__.__setitem__(name, value)
+                else:
+                    inst_cls.__pydantic_validator__.validate_assignment(instance, name, value)
+
+            cls.__setattr__ = validated_setattr.__get__(None, cls)  # type: ignore
+
+            if slots and not hasattr(cls, '__setstate__'):
+                # If slots is set, `pickle` (relied on by `copy.copy()`) will use
+                # `__setattr__()` to reconstruct the dataclass. However, the custom
+                # `__setattr__()` set above relies on `validate_assignment()`, which
+                # in turn expects all the field values to be already present on the
+                # instance, resulting in attribute errors.
+                # As such, we make use of `object.__setattr__()` instead.
+                # Note that we do so only if `__setstate__()` isn't already set (this is the
+                # case if on top of `slots`, `frozen` is used).
+
+                # Taken from `dataclasses._dataclass_get/setstate()`:
+                def _dataclass_getstate(self: Any) -> list[Any]:
+                    return [getattr(self, f.name) for f in dataclasses.fields(self)]
+
+                def _dataclass_setstate(self: Any, state: list[Any]) -> None:
+                    for field, value in zip(dataclasses.fields(self), state):
+                        object.__setattr__(self, field.name, value)
+
+                cls.__getstate__ = _dataclass_getstate  # pyright: ignore[reportAttributeAccessIssue]
+                cls.__setstate__ = _dataclass_setstate  # pyright: ignore[reportAttributeAccessIssue]
+
+        # This is an undocumented attribute to distinguish stdlib/Pydantic dataclasses.
+        # It should be set as early as possible:
+        cls.__is_pydantic_dataclass__ = True
+        cls.__pydantic_decorators__ = decorators  # type: ignore
+        cls.__doc__ = original_doc
+        # Can be non-existent for dynamically created classes:
+        firstlineno = getattr(original_cls, '__firstlineno__', None)
+        cls.__module__ = original_cls.__module__
+        if sys.version_info >= (3, 13) and firstlineno is not None:
+            # As per https://docs.python.org/3/reference/datamodel.html#type.__firstlineno__:
+            # Setting the `__module__` attribute removes the `__firstlineno__` item from the type’s dictionary.
+            original_cls.__firstlineno__ = firstlineno
+            cls.__firstlineno__ = firstlineno
+        cls.__qualname__ = original_cls.__qualname__
+        cls.__pydantic_fields_complete__ = classmethod(_pydantic_fields_complete)
+        cls.__pydantic_complete__ = False  # `complete_dataclass` will set it to `True` if successful.
+        # TODO `parent_namespace` is currently None, but we could do the same thing as Pydantic models:
+        # fetch the parent ns using `parent_frame_namespace` (if the dataclass was defined in a function),
+        # and possibly cache it (see the `__pydantic_parent_namespace__` logic for models).
+        _pydantic_dataclasses.complete_dataclass(cls, config_wrapper, raise_errors=False)
+        return cls
+
+    return create_dataclass if _cls is None else create_dataclass(_cls)
+
+
+def _pydantic_fields_complete(cls: type[PydanticDataclass]) -> bool:
+    """Return whether the fields were successfully collected (i.e. type hints were successfully resolved).
+
+    This is a private helper, not meant to be used outside Pydantic.
+    """
+    return all(field_info._complete for field_info in cls.__pydantic_fields__.values())
+
+
+__getattr__ = getattr_migration(__name__)
+
+if sys.version_info < (3, 11):
+    # Monkeypatch dataclasses.InitVar so that typing doesn't error if it occurs as a type when evaluating type hints
+    # Starting in 3.11, typing.get_type_hints will not raise an error if the retrieved type hints are not callable.
+
+    def _call_initvar(*args: Any, **kwargs: Any) -> NoReturn:
+        """This function does nothing but raise an error that is as similar as possible to what you'd get
+        if you were to try calling `InitVar[int]()` without this monkeypatch. The whole purpose is just
+        to ensure typing._type_check does not error if the type hint evaluates to `InitVar[<parameter>]`.
+        """
+        raise TypeError("'InitVar' object is not callable")
+
+    dataclasses.InitVar.__call__ = _call_initvar
+
+
+def rebuild_dataclass(
+    cls: type[PydanticDataclass],
+    *,
+    force: bool = False,
+    raise_errors: bool = True,
+    _parent_namespace_depth: int = 2,
+    _types_namespace: MappingNamespace | None = None,
+) -> bool | None:
+    """Try to rebuild the pydantic-core schema for the dataclass.
+
+    This may be necessary when one of the annotations is a ForwardRef which could not be resolved during
+    the initial attempt to build the schema, and automatic rebuilding fails.
+
+    This is analogous to `BaseModel.model_rebuild`.
+
+    Args:
+        cls: The class to rebuild the pydantic-core schema for.
+        force: Whether to force the rebuilding of the schema, defaults to `False`.
+        raise_errors: Whether to raise errors, defaults to `True`.
+        _parent_namespace_depth: The depth level of the parent namespace, defaults to 2.
+        _types_namespace: The types namespace, defaults to `None`.
+
+    Returns:
+        Returns `None` if the schema is already "complete" and rebuilding was not required.
+        If rebuilding _was_ required, returns `True` if rebuilding was successful, otherwise `False`.
+    """
+    if not force and cls.__pydantic_complete__:
+        return None
+
+    for attr in ('__pydantic_core_schema__', '__pydantic_validator__', '__pydantic_serializer__'):
+        if attr in cls.__dict__ and not isinstance(getattr(cls, attr), _mock_val_ser.MockValSer):
+            # Deleting the validator/serializer is necessary as otherwise they can get reused in
+            # pydantic-core. Same applies for the core schema that can be reused in schema generation.
+            delattr(cls, attr)
+
+    cls.__pydantic_complete__ = False
+
+    if _types_namespace is not None:
+        rebuild_ns = _types_namespace
+    elif _parent_namespace_depth > 0:
+        rebuild_ns = _typing_extra.parent_frame_namespace(parent_depth=_parent_namespace_depth, force=True) or {}
+    else:
+        rebuild_ns = {}
+
+    ns_resolver = _namespace_utils.NsResolver(
+        parent_namespace=rebuild_ns,
+    )
+
+    return _pydantic_dataclasses.complete_dataclass(
+        cls,
+        _config.ConfigWrapper(cls.__pydantic_config__, check=False),
+        raise_errors=raise_errors,
+        ns_resolver=ns_resolver,
+        # We could provide a different config instead (with `'defer_build'` set to `True`)
+        # of this explicit `_force_build` argument, but because config can come from the
+        # decorator parameter or the `__pydantic_config__` attribute, `complete_dataclass`
+        # will overwrite `__pydantic_config__` with the provided config above:
+        _force_build=True,
+    )
+
+
+def is_pydantic_dataclass(class_: type[Any], /) -> TypeGuard[type[PydanticDataclass]]:
+    """Whether a class is a pydantic dataclass.
+
+    Args:
+        class_: The class.
+
+    Returns:
+        `True` if the class is a pydantic dataclass, `False` otherwise.
+    """
+    try:
+        return '__is_pydantic_dataclass__' in class_.__dict__ and dataclasses.is_dataclass(class_)
+    except AttributeError:
+        return False

venv/Lib/site-packages/pydantic/datetime_parse.py

@@ -0,0 +1,5 @@
+"""The `datetime_parse` module is a backport module from V1."""
+
+from ._migration import getattr_migration
+
+__getattr__ = getattr_migration(__name__)