Python dataclasses.Field方法代码示例

# 需要导入模块: import dataclasses [as 别名]
# 或者: from dataclasses import Field [as 别名]
def resolve_defaults(func):
    """
    Use this decorator to resolve default field values in the constructor.
    """

    func_params = list(signature(func).parameters.values())

    @functools.wraps(func)
    def wrapper(*args, **kwargs):
        if len(args) > len(func_params):
            raise ValueError(
                f"There are {len(func_params)} parameters in total, "
                f"but args is {len(args)} long. \n"
                f"{args}"
            )
        # go through unprovided default kwargs
        for p in func_params[len(args) :]:
            # only resolve defaults for Fields
            if isinstance(p.default, Field):
                if p.name not in kwargs:
                    kwargs[p.name] = _resolve_default(p.default)
        return func(*args, **kwargs)

    return wrapper 

# 需要导入模块: import dataclasses [as 别名]
# 或者: from dataclasses import Field [as 别名]
def _get_default(catch_all_field: Field) -> Any:
        # access to the default factory currently causes
        # a false-positive mypy error (16. Dec 2019):
        # https://github.com/python/mypy/issues/6910

        # noinspection PyProtectedMember
        has_default = not isinstance(catch_all_field.default,
                                     dataclasses._MISSING_TYPE)
        # noinspection PyProtectedMember
        has_default_factory = not isinstance(catch_all_field.default_factory,
                                             # type: ignore
                                             dataclasses._MISSING_TYPE)
        default_value = _CatchAllUndefinedParameters._SentinelNoDefault
        if has_default:
            default_value = catch_all_field.default
        elif has_default_factory:
            # This might be unwanted if the default factory constructs
            # something expensive,
            # because we have to construct it again just for this test
            default_value = catch_all_field.default_factory()  # type: ignore

        return default_value 

# 需要导入模块: import dataclasses [as 别名]
# 或者: from dataclasses import Field [as 别名]
def _decoder(
    # NOTE: mypy incorrectly thinks `Field` is a generic type
    data: Dict[str, EncodedConfigTypes],
    fields: Collection[Field],  # type: ignore
) -> Iterable[Tuple[str, ConfigTypes]]:
    # NOTE: this code is unwieldly but it satisfies `mypy`
    for field in fields:
        if field.type is Gwei:
            yield field.name, Gwei(cast(int, data[field.name]))
        elif field.type is Slot:
            yield field.name, Slot(cast(int, data[field.name]))
        elif field.type is Epoch:
            yield field.name, Epoch(cast(int, data[field.name]))
        elif field.type is Second:
            yield field.name, Second(cast(int, data[field.name]))
        elif field.type is bytes:
            yield field.name, decode_hex(cast(str, data[field.name]))
        else:
            yield field.name, int(data[field.name]) 

# 需要导入模块: import dataclasses [as 别名]
# 或者: from dataclasses import Field [as 别名]
def _get_fields(cls, base_fields=True) -> List[JsonSchemaField]:

        def _get_fields_uncached():
            dataclass_bases = [
                klass for klass in cls.__bases__ if is_dataclass(klass) and issubclass(klass, JsonSchemaMixin)
            ]
            base_fields_types = set()
            for base in dataclass_bases:
                base_fields_types |= {(f.name, f.type) for f in fields(base)}

            mapped_fields = []
            type_hints = get_type_hints(cls)
            for f in fields(cls):
                # Skip internal fields
                if f.name.startswith("__") or (not base_fields and (f.name, f.type) in base_fields_types):
                    continue
                # Note fields() doesn't resolve forward refs
                f.type = type_hints[f.name]
                mapped_fields.append(JsonSchemaField(f, cls.field_mapping().get(f.name, f.name)))

            if cls.__serialise_properties:
                include_properties = None
                if isinstance(cls.__serialise_properties, tuple):
                    include_properties = set(cls.__serialise_properties)

                members = inspect.getmembers(cls, inspect.isdatadescriptor)
                for name, member in members:
                    if name != "__weakref__" and (include_properties is None or name in include_properties):
                        f = Field(MISSING, None, None, None, None, None, None)
                        f.name = name
                        f.type = member.fget.__annotations__['return']
                        mapped_fields.append(JsonSchemaField(f, name, is_property=True))

            return mapped_fields

        if not base_fields:
            return _get_fields_uncached()

        if not cls.__mapped_fields:
            cls.__mapped_fields = _get_fields_uncached()
        return cls.__mapped_fields  # type: ignore 

# 需要导入模块: import dataclasses [as 别名]
# 或者: from dataclasses import Field [as 别名]
def _get_field_meta(cls, field: Field, schema_type: SchemaType) -> Tuple[FieldMeta, bool]:
        required = True
        field_meta = FieldMeta(schema_type=schema_type)
        default_value = MISSING
        if field.default is not MISSING:
            # In case of default value given
            default_value = field.default
        elif field.default_factory is not MISSING and field.default_factory is not None:  # type: ignore
            # In case of a default factory given, we call it
            default_value = field.default_factory()  # type: ignore

        if default_value is not MISSING:
            field_meta.default = cls._encode_field(field.type, default_value, omit_none=False)
            required = False
        if field.metadata is not None:
            if "examples" in field.metadata:
                field_meta.examples = [
                    cls._encode_field(field.type, example, omit_none=False) for example in field.metadata["examples"]
                ]
            if "extensions" in field.metadata:
                field_meta.extensions = field.metadata["extensions"]
            if "description" in field.metadata:
                field_meta.description = field.metadata["description"]
            if "title" in field.metadata:
                field_meta.title = field.metadata["title"]
            if schema_type == SchemaType.OPENAPI_3:
                field_meta.read_only = field.metadata.get("read_only")
                if field_meta.read_only and default_value is MISSING:
                    warnings.warn(f"Read-only fields should have a default value")
                field_meta.write_only = field.metadata.get("write_only")
        return field_meta, required 

# 需要导入模块: import dataclasses [as 别名]
# 或者: from dataclasses import Field [as 别名]
def from_json_dict(cls, json_dict: dict) -> "PatcherConfiguration":
        kwargs = {}

        for field in dataclasses.fields(cls):
            field: dataclasses.Field = field
            if field.name in json_dict:
                kwargs[field.name] = field.type(json_dict[field.name])

        return PatcherConfiguration(**kwargs) 

# 需要导入模块: import dataclasses [as 别名]
# 或者: from dataclasses import Field [as 别名]
def _resolve_default(val):
    if not isinstance(val, Field):
        return val
    if val.default != MISSING:
        return val.default
    if val.default_factory != MISSING:
        return val.default_factory()
    raise ValueError("No default value") 

# 需要导入模块: import dataclasses [as 别名]
# 或者: from dataclasses import Field [as 别名]
def _proxied_class_schema(
    clazz: type, base_schema: Optional[Type[marshmallow.Schema]] = None
) -> Type[marshmallow.Schema]:

    try:
        # noinspection PyDataclass
        fields: Tuple[dataclasses.Field, ...] = dataclasses.fields(clazz)
    except TypeError:  # Not a dataclass
        try:
            return class_schema(dataclasses.dataclass(clazz), base_schema)
        except Exception:
            raise TypeError(
                f"{getattr(clazz, '__name__', repr(clazz))} is not a dataclass and cannot be turned into one."
            )

    # Copy all marshmallow hooks and whitelisted members of the dataclass to the schema.
    attributes = {
        k: v
        for k, v in inspect.getmembers(clazz)
        if hasattr(v, "__marshmallow_hook__") or k in MEMBERS_WHITELIST
    }
    # Update the schema members to contain marshmallow fields instead of dataclass fields
    attributes.update(
        (
            field.name,
            field_for_schema(
                field.type, _get_field_default(field), field.metadata, base_schema
            ),
        )
        for field in fields
        if field.init
    )

    schema_class = type(clazz.__name__, (_base_schema(clazz, base_schema),), attributes)
    return cast(Type[marshmallow.Schema], schema_class) 

# 需要导入模块: import dataclasses [as 别名]
# 或者: from dataclasses import Field [as 别名]
def _field_by_type(
    typ: Union[type, Any], base_schema: Optional[Type[marshmallow.Schema]]
) -> Optional[Type[marshmallow.fields.Field]]:
    return (
        base_schema and base_schema.TYPE_MAPPING.get(typ)
    ) or marshmallow.Schema.TYPE_MAPPING.get(typ) 

# 需要导入模块: import dataclasses [as 别名]
# 或者: from dataclasses import Field [as 别名]
def _get_field_default(field: dataclasses.Field):
    """
    Return a marshmallow default value given a dataclass default value

    >>> _get_field_default(dataclasses.field())
    <marshmallow.missing>
    """
    # Remove `type: ignore` when https://github.com/python/mypy/issues/6910 is fixed
    default_factory = field.default_factory  # type: ignore
    if default_factory is not dataclasses.MISSING:
        return default_factory
    elif field.default is dataclasses.MISSING:
        return marshmallow.missing
    return field.default 

# 需要导入模块: import dataclasses [as 别名]
# 或者: from dataclasses import Field [as 别名]
def _get_catch_all_field(cls) -> Field:
        catch_all_fields = list(
            filter(lambda f: f.type == Optional[CatchAllVar], fields(cls)))
        number_of_catch_all_fields = len(catch_all_fields)
        if number_of_catch_all_fields == 0:
            raise UndefinedParameterError(
                "No field of type dataclasses_json.CatchAll defined")
        elif number_of_catch_all_fields > 1:
            raise UndefinedParameterError(
                f"Multiple catch-all fields supplied: "
                f"{number_of_catch_all_fields}.")
        else:
            return catch_all_fields[0] 

# 需要导入模块: import dataclasses [as 别名]
# 或者: from dataclasses import Field [as 别名]
def NewType(
    name: str,
    typ: Type[_U],
    field: Optional[Type[marshmallow.fields.Field]] = None,
    **kwargs,
) -> Callable[[_U], _U]:
    """NewType creates simple unique types
    to which you can attach custom marshmallow attributes.
    All the keyword arguments passed to this function will be transmitted
    to the marshmallow field constructor.

    >>> import marshmallow.validate
    >>> IPv4 = NewType('IPv4', str, validate=marshmallow.validate.Regexp(r'^([0-9]{1,3}\\.){3}[0-9]{1,3}$'))
    >>> @dataclass
    ... class MyIps:
    ...   ips: List[IPv4]
    >>> MyIps.Schema().load({"ips": ["0.0.0.0", "grumble grumble"]})
    Traceback (most recent call last):
    ...
    marshmallow.exceptions.ValidationError: {'ips': {1: ['String does not match expected pattern.']}}
    >>> MyIps.Schema().load({"ips": ["127.0.0.1"]})
    MyIps(ips=['127.0.0.1'])

    >>> Email = NewType('Email', str, field=marshmallow.fields.Email)
    >>> @dataclass
    ... class ContactInfo:
    ...   mail: Email = dataclasses.field(default="anonymous@example.org")
    >>> ContactInfo.Schema().load({})
    ContactInfo(mail='anonymous@example.org')
    >>> ContactInfo.Schema().load({"mail": "grumble grumble"})
    Traceback (most recent call last):
    ...
    marshmallow.exceptions.ValidationError: {'mail': ['Not a valid email address.']}
    """

    def new_type(x: _U):
        return x

    new_type.__name__ = name
    new_type.__supertype__ = typ  # type: ignore
    new_type._marshmallow_field = field  # type: ignore
    new_type._marshmallow_args = kwargs  # type: ignore
    return new_type