如何使用数据类创建"仅关键字"字段？

Question

从3.0开始,只支持创建一个参数关键字:

class S3Obj:
    def __init__(self, bucket, key, *, storage_class='Standard'):
        self.bucket = bucket
        self.key = key
        self.storage_class = storage_class

如何使用数据类获得这种签名？像这样的东西,但最好没有SyntaxError:

@dataclass
class S3Obj:
    bucket: str
    key: str
    *
    storage_class: str = 'Standard'

理想情况下是声明性的,但是使用__post_init__钩子和/或替换类装饰器也很好 - 只要代码是可重用的.

编辑:可能是这样的语法,使用省略号文字

@mydataclass
class S3Obj:
    bucket: str
    key: str
    ...
    storage_class: str = 'Standard'

Answer 1

dataclasses这样做时你不会得到太多帮助.没有办法说一个字段应该只通过keyword-only参数初始化,并且__post_init__钩子不知道原始的构造函数参数是否是由关键字传递的.此外,没有好的方法来内省InitVars,更不用说将InitVars 标记为仅限关键字.

至少,您必须替换生成的__init__.可能最简单的方法是__init__手工定义.如果您不想这样做,可能最强大的方法是创建字段对象并将其标记为kwonly metadata,然后检查您自己的装饰器中的元数据.这比听起来更复杂:

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')

这有点经过考验,但并不像我想的那么彻底.

你不能得到你提出的语法...,因为...没有做任何元类或装饰者可以看到的东西.你可以通过实际触发名称查找或赋值的东西获得非常接近的东西kwonly_start = True,因此,元类可以看到它发生.但是,强大的实现这一点很难编写,因为有很多东西需要专门的处理.传承typing.ClassVar,dataclasses.InitVar在注释等向前引用将如处理不当造成的所有问题.继承可能会导致最多的问题.

不能处理所有繁琐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

你会喜欢它

class S3Obj(metaclass=POCMeta):
    bucket: str
    key: str

    kwonly_start = True

    storage_class: str = 'Standard'

这是未经测试的.

Answer 2

我想知道为什么这不是数据类 API 的一部分，这对我来说似乎很重要。

如果所有参数都是关键字参数，也许它更简单一些，下面的就足够了？

from dataclasses import dataclass
from functools import wraps

def kwargs_only(cls):
    
    @wraps(cls)
    def call(**kwargs):
        return cls(**kwargs)
    
    return call

@kwargs_only
@dataclass
class Coordinates:
    latitude: float = 0
    longitude: float = 0

这并不完美，因为使用位置参数时的错误指的是call：

--------------------------------------------------------
TypeError              Traceback (most recent call last)
<ipython-input-24-fb588c816ecf> in <module>
----> 1 c = Coordinates(1, longitude=2)
      2 help(c)

TypeError: call() takes 0 positional arguments but 1 was given

同样，数据类的构造函数文档已过时，并且不反映新的约束。

如果只有一些关键字字段，也许是这个？

def kwargs(*keywords):
    
    def decorator(cls):
        @wraps(cls)
        def call(*args, **kwargs):
            if any(kw not in kwargs for kw in keywords):
                raise TypeError(f"{cls.__name__}.__init__() requires {keywords} as keyword arguments")
            return cls(*args, **kwargs)
        
        return call

    return decorator


@kwargs('longitude')
@dataclass(frozen=True)
class Coordinates:
    latitude: float
    longitude: float = 0