更新:在Python 3.10中,有一个新的
dataclasses.KW_ONLY
像这样工作的哨兵:
@dataclasses.dataclass
class Example:
a: int
b: int
_: dataclasses.KW_ONLY
c: int
d: int
之后的任何字段
KW_ONLY
伪字段仅为关键字。
还有一个
kw_only
参数设置为
dataclasses.dataclass
decorator,使所有字段仅为关键字:
@dataclasses.dataclass(kw_only=True)
class Example:
a: int
b: int
也可以通过
kw_only=True
到
dataclasses.field
将单个字段标记为仅关键字。
如果仅关键字字段位于非仅关键字字段之后(可以通过继承或单独将字段标记为仅关键字),则仅关键字字段将
reordered
在其他字段之后,专门用于
__init__
。其他数据类功能将保持声明的顺序。这种重新排序令人困惑,可能应该避免。
Python 3.10之前版本答案:
你不会从
dataclasses
执行此操作时。不能说字段应该由关键字only参数初始化
__post_init__
hook不知道原始构造函数参数是否是通过关键字传递的。还有,没有好的方法来反省
InitVar
s、 更不用说马克了
初始值
s仅作为关键字。
至少,您必须替换生成的
__初始化__
.可能最简单的方法就是定义
__初始化__
手工如果不想这样做,最可靠的方法可能是创建字段对象并在
metadata
,然后在您自己的decorator中检查元数据。这比听起来还要复杂:
import dataclasses
import functools
import inspect
# Helper to make calling field() less verbose
def kwonly(default=dataclasses.MISSING, **kwargs):
kwargs.setdefault('metadata', {})
kwargs['metadata']['kwonly'] = True
return dataclasses.field(default=default, **kwargs)
def mydataclass(_cls, *, init=True, **kwargs):
if _cls is None:
return functools.partial(mydataclass, **kwargs)
no_generated_init = (not init or '__init__' in _cls.__dict__)
_cls = dataclasses.dataclass(_cls, **kwargs)
if no_generated_init:
# No generated __init__. The user will have to provide __init__,
# and they probably already have. We assume their __init__ does
# what they want.
return _cls
fields = dataclasses.fields(_cls)
if any(field.metadata.get('kwonly') and not field.init for field in fields):
raise TypeError('Non-init field marked kwonly')
# From this point on, ignore non-init fields - but we don't know
# about InitVars yet.
init_fields = [field for field in fields if field.init]
for i, field in enumerate(init_fields):
if field.metadata.get('kwonly'):
first_kwonly = field.name
num_kwonly = len(init_fields) - i
break
else:
# No kwonly fields. Why were we called? Assume there was a reason.
return _cls
if not all(field.metadata.get('kwonly') for field in init_fields[-num_kwonly:]):
raise TypeError('non-kwonly init fields following kwonly fields')
required_kwonly = [field.name for field in init_fields[-num_kwonly:]
if field.default is field.default_factory is dataclasses.MISSING]
original_init = _cls.__init__
# Time to handle InitVars. This is going to get ugly.
# InitVars don't show up in fields(). They show up in __annotations__,
# but the current dataclasses implementation doesn't understand string
# annotations, and we want an implementation that's robust against
# changes in string annotation handling.
# We could inspect __post_init__, except there doesn't have to be a
# __post_init__. (It'd be weird to use InitVars with no __post_init__,
# but it's allowed.)
# As far as I can tell, that leaves inspecting __init__ parameters as
# the only option.
init_params = tuple(inspect.signature(original_init).parameters)
if init_params[-num_kwonly] != first_kwonly:
# InitVars following kwonly fields. We could adopt a convention like
# "InitVars after kwonly are kwonly" - in fact, we could have adopted
# "all fields after kwonly are kwonly" too - but it seems too likely
# to cause confusion with inheritance.
raise TypeError('InitVars after kwonly fields.')
# -1 to exclude self from this count.
max_positional = len(init_params) - num_kwonly - 1
@functools.wraps(original_init)
def __init__(self, *args, **kwargs):
if len(args) > max_positional:
raise TypeError('Too many positional arguments')
check_required_kwargs(kwargs, required_kwonly)
return original_init(self, *args, **kwargs)
_cls.__init__ = __init__
return _cls
def check_required_kwargs(kwargs, required):
# Not strictly necessary, but if we don't do this, error messages for
# required kwonly args will list them as positional instead of
# keyword-only.
missing = [name for name in required if name not in kwargs]
if not missing:
return
# We don't bother to exactly match the built-in logic's exception
raise TypeError(f"__init__ missing required keyword-only argument(s): {missing}")
用法示例:
@mydataclass
class S3Obj:
bucket: str
key: str
storage_class: str = kwonly('Standard')
这是经过一些测试的,但没有我想要的那么彻底。
你无法获得你所建议的语法
...
因为
。。。
不做元类或装饰器可以看到的任何事情。您可以获得一些非常接近于触发名称查找或赋值的内容,例如
kwonly_start = True
,因此元类可以看到它的发生。然而,这方面的健壮实现编写起来很复杂,因为有很多事情需要专门处理。遗产
typing.ClassVar
,则,
dataclasses.InitVar
,注释中的转发引用等,如果不小心处理,都会导致问题。继承可能会导致大多数问题。
无法处理所有复杂位的概念验证可能如下所示:
# Does not handle inheritance, InitVar, ClassVar, or anything else
# I'm forgetting.
class POCMetaDict(dict):
def __setitem__(self, key, item):
# __setitem__ instead of __getitem__ because __getitem__ is
# easier to trigger by accident.
if key == 'kwonly_start':
self['__non_kwonly'] = len(self['__annotations__'])
super().__setitem__(key, item)
class POCMeta(type):
@classmethod
def __prepare__(cls, name, bases, **kwargs):
return POCMetaDict()
def __new__(cls, name, bases, classdict, **kwargs):
classdict.pop('kwonly_start')
non_kwonly = classdict.pop('__non_kwonly')
newcls = super().__new__(cls, name, bases, classdict, **kwargs)
newcls = dataclass(newcls)
if non_kwonly is None:
return newcls
original_init = newcls.__init__
@functools.wraps(original_init)
def __init__(self, *args, **kwargs):
if len(args) > non_kwonly:
raise TypeError('Too many positional arguments')
return original_init(self, *args, **kwargs)
newcls.__init__ = __init__
return newcls
你会像这样使用它
class S3Obj(metaclass=POCMeta):
bucket: str
key: str
kwonly_start = True
storage_class: str = 'Standard'
这是未经测试的。
