我还没有看到一个直截了当的答案。想法很简单:

使用__init__作为“基本”构造函数，因为python只允许一个__init__方法 使用@classmethod创建任何其他构造函数并调用基本构造函数

这是一个新的尝试。

 class Person:
    def __init__(self, name, age):
        self.name = name
        self.age = age

    @classmethod
    def fromBirthYear(cls, name, birthYear):
        return cls(name, date.today().year - birthYear)

用法:

p = Person('tim', age=18)
p = Person.fromBirthYear('tim', birthYear=2004)

实际上，对于“魔幻”价值观来说，None要好得多:

class Cheese():
    def __init__(self, num_holes = None):
        if num_holes is None:
            ...

现在，如果你想要完全自由地添加更多参数:

class Cheese():
    def __init__(self, *args, **kwargs):
        #args -- tuple of anonymous arguments
        #kwargs -- dictionary of named arguments
        self.num_holes = kwargs.get('num_holes',random_holes())

为了更好地解释*args和**kwargs的概念(实际上您可以更改这些名称):

def f(*args, **kwargs):
   print 'args: ', args, ' kwargs: ', kwargs

>>> f('a')
args:  ('a',)  kwargs:  {}
>>> f(ar='a')
args:  ()  kwargs:  {'ar': 'a'}
>>> f(1,2,param=3)
args:  (1, 2)  kwargs:  {'param': 3}

http://docs.python.org/reference/expressions.html#calls

概述

对于特定的cheese示例，我同意使用默认值来表示随机初始化或使用静态工厂方法的许多其他答案。但是，在您想到的相关场景中，使用其他简洁的方法调用构造函数而不影响形参名称或类型信息的质量是有价值的。

自Python 3.8和functools开始。在许多情况下，Singledispatchmethod可以帮助实现这一点(更灵活的multimethod可以应用于更多的场景)。(这篇相关文章描述了如何在没有库的情况下在Python 3.4中实现同样的功能。)我还没有在文档中看到这两种方法的例子，具体显示重载__init__，因为你问，但似乎重载任何成员方法的相同原则适用(如下所示)。

"Single dispatch" (available in the standard library) requires that there be at least one positional parameter and that the type of the first argument be sufficient to distinguish among the possible overloaded options. For the specific Cheese example, this doesn't hold since you wanted random holes when no parameters were given, but multidispatch does support the very same syntax and can be used as long as each method version can be distinguish based on the number and type of all arguments together.

例子

下面是一个如何使用这两种方法的例子(一些细节是为了取悦我的ypy，这是我第一次把这些放在一起的目标):

from functools import singledispatchmethod as overload
# or the following more flexible method after `pip install multimethod`
# from multimethod import multidispatch as overload


class MyClass:

    @overload  # type: ignore[misc]
    def __init__(self, a: int = 0, b: str = 'default'):
        self.a = a
        self.b = b

    @__init__.register
    def _from_str(self, b: str, a: int = 0):
        self.__init__(a, b)  # type: ignore[misc]

    def __repr__(self) -> str:
        return f"({self.a}, {self.b})"


print([
    MyClass(1, "test"),
    MyClass("test", 1),
    MyClass("test"),
    MyClass(1, b="test"),
    MyClass("test", a=1),
    MyClass("test"),
    MyClass(1),
    # MyClass(),  # `multidispatch` version handles these 3, too.
    # MyClass(a=1, b="test"),
    # MyClass(b="test", a=1),
])

输出:

[(1, test), (1, test), (0, test), (1, test), (1, test), (0, test), (1, default)]

注:

I wouldn't usually make the alias called overload, but it helped make the diff between using the two methods just a matter of which import you use. The # type: ignore[misc] comments are not necessary to run, but I put them in there to please mypy which doesn't like decorating __init__ nor calling __init__ directly. If you are new to the decorator syntax, realize that putting @overload before the definition of __init__ is just sugar for __init__ = overload(the original definition of __init__). In this case, overload is a class so the resulting __init__ is an object that has a __call__ method so that it looks like a function but that also has a .register method which is being called later to add another overloaded version of __init__. This is a bit messy, but it please mypy becuase there are no method names being defined twice. If you don't care about mypy and are planning to use the external library anyway, multimethod also has simpler alternative ways of specifying overloaded versions. Defining __repr__ is simply there to make the printed output meaningful (you don't need it in general). Notice that multidispatch is able to handle three additional input combinations that don't have any positional parameters.

使用num_holes=None作为默认值。然后检查num_holes是否为None，如果是，则随机化。这就是我通常看到的情况。

更完全不同的构造方法可能需要一个返回cls实例的类方法。

为什么你认为你的解决方案“笨拙”?就我个人而言，在你这样的情况下，我更喜欢一个具有默认值的构造函数，而不是多个重载构造函数(Python不支持方法重载):

def __init__(self, num_holes=None):
    if num_holes is None:
        # Construct a gouda
    else:
        # custom cheese
    # common initialization

对于有很多不同构造函数的非常复杂的情况，使用不同的工厂函数可能会更干净:

@classmethod
def create_gouda(cls):
    c = Cheese()
    # ...
    return c

@classmethod
def create_cheddar(cls):
    # ...

在你的奶酪的例子中，你可能想要使用奶酪的一个Gouda子类…

这就是我如何解决一个我必须创建的YearQuarter类。我创建了一个__init__，它对各种各样的输入非常宽容。

你可以这样使用它:

>>> from datetime import date
>>> temp1 = YearQuarter(year=2017, month=12)
>>> print temp1
2017-Q4
>>> temp2 = YearQuarter(temp1)
>>> print temp2
2017-Q4
>>> temp3 = YearQuarter((2017, 6))
>>> print temp3
2017-Q2 
>>> temp4 = YearQuarter(date(2017, 1, 18))
>>> print temp4
2017-Q1
>>> temp5 = YearQuarter(year=2017, quarter = 3)
>>> print temp5
2017-Q3

这就是__init__和类的其余部分的样子:

import datetime


class YearQuarter:

    def __init__(self, *args, **kwargs):
        if len(args) == 1:
            [x]     = args

            if isinstance(x, datetime.date):
                self._year      = int(x.year)
                self._quarter   = (int(x.month) + 2) / 3
            elif isinstance(x, tuple):
                year, month     = x

                self._year      = int(year)

                month           = int(month)

                if 1 <= month <= 12:
                    self._quarter   = (month + 2) / 3
                else:
                    raise ValueError

            elif isinstance(x, YearQuarter):
                self._year      = x._year
                self._quarter   = x._quarter

        elif len(args) == 2:
            year, month     = args

            self._year      = int(year)

            month           = int(month)

            if 1 <= month <= 12:
                self._quarter   = (month + 2) / 3
            else:
                raise ValueError

        elif kwargs:

            self._year      = int(kwargs["year"])

            if "quarter" in kwargs:
                quarter     = int(kwargs["quarter"])

                if 1 <= quarter <= 4:
                    self._quarter     = quarter
                else:
                    raise ValueError
            elif "month" in kwargs:
                month   = int(kwargs["month"])

                if 1 <= month <= 12:
                    self._quarter     = (month + 2) / 3
                else:
                    raise ValueError

    def __str__(self):
        return '{0}-Q{1}'.format(self._year, self._quarter)