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import re
from typing import NamedTuple, NewType
import pydantic.validators
import apischema
# Serialization can only be customized into the enclosing models
class RGB(NamedTuple):
red: int
green: int
blue: int
# If you don't put this method, RGB schema will be:
# {'title': 'Rgb', 'type': 'array', 'items': {}}
@classmethod
def __modify_schema__(cls, field_schema) -> None:
field_schema.update({"type": "string", "pattern": r"#[0-9A-Fa-f]{6}"})
field_schema.pop("items", ...)
@classmethod
def __get_validators__(cls):
yield pydantic.validators.str_validator
yield cls.validate
@classmethod
def validate(cls, value) -> "RGB":
if (
not isinstance(value, str)
or re.fullmatch(r"#[0-9A-Fa-f]{6}", value) is None
):
raise ValueError("Invalid RGB")
return RGB(
red=int(value[1:3], 16), green=int(value[3:5], 16), blue=int(value[5:7], 16)
)
# Simpler with apischema
class RGB(NamedTuple):
red: int
green: int
blue: int
# NewType can be used to add schema to conversion source/target
# but Annotated[str, apischema.schema(pattern=r"#[0-9A-Fa-f]{6}")] would have worked too
HexaRGB = NewType("HexaRGB", str)
# pattern is used in JSON schema and in deserialization validation
apischema.schema(pattern=r"#[0-9A-Fa-f]{6}")(HexaRGB)
@apischema.deserializer # could be declared as a staticmethod of RGB class
def from_hexa(hexa: HexaRGB) -> RGB:
return RGB(int(hexa[1:3], 16), int(hexa[3:5], 16), int(hexa[5:7], 16))
@apischema.serializer # could be declared as a method/property of RGB class
def to_hexa(rgb: RGB) -> HexaRGB:
return HexaRGB(f"#{rgb.red:02x}{rgb.green:02x}{rgb.blue:02x}")
assert ( # schema is inherited from deserialized type
apischema.json_schema.deserialization_schema(RGB)
== apischema.json_schema.deserialization_schema(HexaRGB)
== {
"$schema": "http://json-schema.org/draft/2020-12/schema#",
"type": "string",
"pattern": "#[0-9A-Fa-f]{6}",
}
)
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