Since 3.0支持仅使参数关键字:
class S3Obj:
def __init__(self, bucket, key, *, storage_class='Standard'):
self.bucket = bucket
self.key = key
self.storage_class = storage_class
如何使用dataclasses获得这种签名?这样的东西,但最好没有SyntaxError
:
@dataclass
class S3Obj:
bucket: str
key: str
*
storage_class: str = 'Standard'
理想的情况是声明性的,但是使用__post_init__
钩子和/或替换类装饰器也可以-只要代码可重用即可。
编辑:也许像这样的语法,使用省略号
@mydataclass
class S3Obj:
bucket: str
key: str
...
storage_class: str = 'Standard'
参考方案
这样做时,您不会从dataclasses
获得太多帮助。没有办法说一个字段应该由仅关键字参数初始化,而__post_init__
钩子不知道原始构造函数参数是否由关键字传递。此外,也没有很好的方法来反射Reflection InitVar
,更不用说将InitVar
标记为仅关键字。
至少,您必须替换生成的__init__
。可能最简单的方法是手动定义__init__
。如果您不想这样做,则最可靠的方法可能是创建字段对象,并在metadata
中将它们标记为kwonly,然后在自己的装饰器中检查元数据。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')
这已经过一些测试,但是没有我想要的彻底。
您无法获得使用...
提议的语法,因为...
不会执行元类或装饰器可以看到的任何操作。您可以通过实际触发名称查找或赋值的东西(例如kwonly_start = True
)获得非常接近的东西,以便元类可以看到它的发生。但是,由于许多事情需要专门处理,因此编写此函数的可靠实现很复杂。如果不仔细处理,继承,typing.ClassVar
,dataclasses.InitVar
,批注中的前向引用等都将导致问题。继承可能导致最多的问题。
无法处理所有杂乱无章的概念验证可能看起来像这样:
# 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
你会用它像
class S3Obj(metaclass=POCMeta):
bucket: str
key: str
kwonly_start = True
storage_class: str = 'Standard'
这未经测试。
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