给定如下数据类：
class MessageHeader(BaseModel):
message_id: uuid.UUID
def dict(self, **kwargs):
return json.loads(self.json())
当我在
dictMessageHeader{'message_id': '383b0bfc-743e-4738-8361-27e6a0753b5a'}
我想避免使用像
pydanticjson.loads(self.json())有没有更好的方法将数据类转换为带有上面字符串文字的字典？
dataclasses.asdictfrom dataclasses import dataclass, asdict
class MessageHeader(BaseModel):
message_id: uuid.UUID
def dict(self):
return {k: str(v) for k, v in asdict(self).items()}
如果您确定您的类只有字符串值，您可以完全跳过字典理解：
class MessageHeader(BaseModel):
message_id: uuid.UUID
dict = asdict
使用此解决方案时要小心，因为如果您在
dataclass__init__asdictvars(x)x.__dict__为了绝对的纯粹、不掺假的速度和无限的效率，甚至可以让像Chuck Norris这样的人停下来，无助地敬畏地看着，我谦虚地推荐这个计划得非常好- out 方法与
__dict__def dict(self):
_dict = self.__dict__.copy()
_dict['message_id'] = str(_dict['message_id'])
return _dict
对于定义
__slots__@dataclass(slots=True)__dict__def dict(self):
body_lines = ','.join(f"'{f}':" + (f'str(self.{f})' if f == 'message_id'
else f'self.{f}') for f in self.__slots__)
# Compute the text of the entire function.
txt = f'def dict(self):\n return {{{body_lines}}}'
ns = {}
exec(txt, locals(), ns)
_dict_fn = self.__class__.dict = ns['dict']
return _dict_fn(self)
万一有人现在在座位边缘摇摇欲坠（我知道，这真的令人难以置信，突破级别的东西）-我已经通过下面的
timeit仅供参考，纯
__dict__dataclasses.asdict()快很多。
注意：尽管
在这种特殊情况下效果更好，但__dict__可能更适合复合字典，例如具有嵌套数据类的字典，或具有可变类型（例如dataclasses.asdict()或dict）的值。list
from dataclasses import dataclass, asdict, field
from uuid import UUID, uuid4
class DictMixin:
"""Mixin class to add a `dict()` method on classes that define a __slots__ attribute"""
def dict(self):
body_lines = ','.join(f"'{f}':" + (f'str(self.{f})' if f == 'message_id'
else f'self.{f}') for f in self.__slots__)
# Compute the text of the entire function.
txt = f'def dict(self):\n return {{{body_lines}}}'
ns = {}
exec(txt, locals(), ns)
_dict_fn = self.__class__.dict = ns['dict']
return _dict_fn(self)
@dataclass
class MessageHeader:
message_id: UUID = field(default_factory=uuid4)
string: str = 'a string'
integer: int = 1000
floating: float = 1.0
def dict1(self):
_dict = self.__dict__.copy()
_dict['message_id'] = str(_dict['message_id'])
return _dict
def dict2(self):
return {k: str(v) if k == 'message_id' else v
for k, v in self.__dict__.items()}
def dict3(self):
return {k: str(v) if k == 'message_id' else v
for k, v in asdict(self).items()}
@dataclass(slots=True)
class MessageHeaderWithSlots(DictMixin):
message_id: UUID = field(default_factory=uuid4)
string: str = 'a string'
integer: int = 1000
floating: float = 1.0
def dict2(self):
return {k: str(v) if k == 'message_id' else v
for k, v in asdict(self).items()}
if __name__ == '__main__':
from timeit import timeit
header = MessageHeader()
header_with_slots = MessageHeaderWithSlots()
n = 10000
print('dict1(): ', timeit('header.dict1()', number=n, globals=globals()))
print('dict2(): ', timeit('header.dict2()', number=n, globals=globals()))
print('dict3(): ', timeit('header.dict3()', number=n, globals=globals()))
print('slots -> dict(): ', timeit('header_with_slots.dict()', number=n, globals=globals()))
print('slots -> dict2(): ', timeit('header_with_slots.dict2()', number=n, globals=globals()))
print()
dict__ = header.dict1()
print(dict__)
asdict__ = header.dict3()
print(asdict__)
assert isinstance(dict__['message_id'], str)
assert isinstance(dict__['integer'], int)
assert header.dict1() == header.dict2() == header.dict3()
assert header_with_slots.dict() == header_with_slots.dict2()
我的 Mac M1 笔记本电脑上的结果：
dict1(): 0.005992999998852611
dict2(): 0.00800508284009993
dict3(): 0.07069579092785716
slots -> dict(): 0.00583599996753037
slots -> dict2(): 0.07395245810039341
{'message_id': 'b4e17ef9-1a58-4007-9cef-39158b094da2', 'string': 'a string', 'integer': 1000, 'floating': 1.0}
{'message_id': 'b4e17ef9-1a58-4007-9cef-39158b094da2', 'string': 'a string', 'integer': 1000, 'floating': 1.0}
注意： 对于
DictMixinSerializableMixin这是“dataclass to dict”的最佳谷歌结果，上面的答案过于复杂。您可能正在寻找这个：
from dataclasses import dataclass
@dataclass
class MessageHeader():
uuid: str = "abcd"
vars(MessageHeader()) # or MessageHeader().__dict__
受到 @rv.kvetch 的回答的启发，我编写了这个装饰器，它将根据类定义动态生成
asdict装饰者：
import typing
def generate_dict_method(
__source: typing.Literal["slots", "annotations"],
__name: str,
/,
**custom_mappings: typing.Callable[[typing.Any], typing.Any]
):
if custom_mappings is None:
custom_mappings = dict()
def decorator(cls):
attributes = set()
for mc in cls.__mro__:
if __source == 'annotations':
attrs = getattr(mc, "__annotations__", None)
if attrs:
attrs = attrs.keys()
elif __source == "slots":
attrs = getattr(mc, "__slots__", None)
else:
raise NotImplementedError(__source)
if attrs:
attributes.update(attrs)
if not attributes:
raise RuntimeError(
f"Unable to generate `{__name}` method for `{cls.__qualname__}` class: "
"no attributes found."
)
funclocals = {}
mapping_to_funcname = {}
for attrname, f in custom_mappings.items():
funcname = f'__parse_{attrname}'
funclocals[funcname] = f
mapping_to_funcname[attrname] = funcname
body_lines = ','.join([
f'"{attrname}": ' + (f'self.{attrname}' if attrname not in custom_mappings
else f'{mapping_to_funcname[attrname]}(self.{attrname})')
for attrname in attributes
])
txt = f'def {__name}(self):\n return {{{body_lines}}}'
d = dict()
exec(txt, funclocals, d)
setattr(cls, __name, d[__name])
return cls
return decorator
用途：
from dataclasses import dataclass
import json
@dataclass(slots=True, kw_only=True)
class TestBase:
i1: int
i2: int
@generate_dict_method("annotations", "asdict", d=(lambda x: "FUNNY" + json.dumps(x) + "JSON"))
@dataclass(slots=True, kw_only=True)
class Test(TestBase):
i: int
b: bool
s: str
d: dict
a = Test(i=1, b=True, s="test", d={"test": "test"}, i1=2, i2=3)
print(a.asdict())
输出：
{'d': 'FUNNY{"test": "test"}JSON', 'i': 1, 'i1': 2, 'b': True, 's': 'test', 'i2': 3}
如您所见，您只需为
**custom_mappings在您的情况下，您可以为
strmessage_id