python3：类中的singledispatch，如何调度self类型

Question

使用python3.4。 这里我想使用 singledispatch 在__mul__方法中调度不同类型。 像这样的代码：

class Vector(object):

    ## some code not paste  
    @functools.singledispatch
    def __mul__(self, other):
        raise NotImplementedError("can't mul these type")

    @__mul__.register(int)
    @__mul__.register(object)                # Becasue can't use Vector , I have to use object 
    def _(self, other):
        result = Vector(len(self))           # start with vector of zeros
        for j in range(len(self)):
            result[j] = self[j]*other
        return result

    @__mul__.register(Vector)                # how can I use the self't type
    @__mul__.register(object)                # 
    def _(self, other):
        pass # need impl 

正如你看到的代码，我想要支持Vector*Vertor ，这有 Name 错误

Traceback (most recent call last):
  File "p_algorithms\vector.py", line 6, in <module>
    class Vector(object):
  File "p_algorithms\vector.py", line 84, in Vector
    @__mul__.register(Vector)                   # how can I use the self't type
NameError: name 'Vector' is not defined

问题可能是如何在类的方法中使用类名 a 类型？ 我知道 C++ 有字体类声明。 python 如何解决我的问题？ 看到result = Vector(len(self))在方法体中可以使用Vector是很奇怪的。

---

看看http://lukasz.langa.pl/8/single-dispatch-generic-functions/我可以选择这种方式来实现：

import unittest
from functools import  singledispatch

class Vector(object):
    """Represent a vector in a multidimensional space."""

    def __init__(self, d):
        self._coords = [0 for i in range(0, d)]
        self.__init__mul__()


    def __init__mul__(self):
        __mul__registry = self.__mul__.registry
        self.__mul__ = singledispatch(__mul__registry[object])
        self.__mul__.register(int, self.mul_int)
        self.__mul__.register(Vector, self.mul_Vector)

    def __setitem__(self, key, value):
        self._coords[key] = value

    def __getitem__(self, item):
        return self._coords[item]

    def __len__(self):
        return len(self._coords)

    def __str__(self):
        return str(self._coords)

    @singledispatch
    def __mul__(self, other):
        print ("error type is ", type(other))
        print (type(other))
        raise NotImplementedError("can't mul these type")

    def mul_int(self,other):
         print ("other type is ", type(other))
         result = Vector(len(self))           # start with vector of zeros
         for j in range(len(self)):
             result[j] = self[j]*other
         return result

    def mul_Vector(self, other):
        print ("other type is ", type(other))
        #result = Vector(len(self))           # start with vector of zeros
        sum = 0
        for i in range(0,len(self)):
            sum += self._coords[i] * other._coords[i]
        return sum

class TestCase(unittest.TestCase):
    def test_singledispatch(self):
        # the following demonstrates usage of a few methods
        v = Vector(5)              # construct five-dimensional <0, 0, 0, 0, 0>
        for i in range(1,6):
            v[i-1] = i
        print(v.__mul__(3))
        print(v.__mul__(v))
        print(v*3)

if __name__ == "__main__":
    unittest.main()

答案很奇怪：

 other type is <class 'int'> [3, 6, 9, 12, 15] other type is <class '__main__.Vector'> 55 error type is <class 'int'> Traceback (most recent call last): File "p_algorithms\\vector.py", line 164, in <module> print(v*3) File "C:\\Python34\\lib\\functools.py", line 710, in wrapper return dispatch(args[0].__class__)(*args, **kw) File "p_algorithms\\vector.py", line 111, in __mul__ raise NotImplementedError("can't mul these type")

v.__mul__(3)可以工作但v*3不能工作。 这很奇怪从我的选项v*3与v.__mul__(3) 。

---

在@Martijn Pieters 发表评论后更新，我仍然想在课堂上实现v*3 。 所以我试试这个

import unittest
from functools import  singledispatch

class Vector(object):

    @staticmethod
    def static_mul_int(self,other):
         print ("other type is ", type(other))
         result = Vector(len(self))           # start with vector of zeros
         for j in range(len(self)):
             result[j] = self[j]*other
         return result

    @singledispatch
    @staticmethod
    def __static_mul__(cls, other):
        print ("error type is ", type(other))
        print (type(other))
        raise NotImplementedError("can't mul these type")


    __mul__registry2 = __static_mul__.registry
    __mul__ = singledispatch(__mul__registry2[object])
    __mul__.register(int, static_mul_int)

    def __init__(self, d):
        self._coords = [0 for i in range(0, d)]
        self.__init__mul__()


    def __init__mul__(self):
        __mul__registry = self.__mul__.registry
        print ("__mul__registry",__mul__registry,__mul__registry[object])
        self.__mul__ = singledispatch(__mul__registry[object])
        self.__mul__.register(int, self.mul_int)
        print ("at last __mul__registry",self.__mul__.registry)

    # @singledispatch
    # def __mul__(self, other):
    #     print ("error type is ", type(other))
    #     print (type(other))
    #     raise NotImplementedError("can't mul these type")


    def mul_int(self,other):
         print ("other type is ", type(other))
         result = Vector(len(self))           # start with vector of zeros
         for j in range(len(self)):
             result[j] = self[j]*other
         return result

    def __setitem__(self, key, value):
        self._coords[key] = value

    def __getitem__(self, item):
        return self._coords[item]

    def __len__(self):
        return len(self._coords)

    def __str__(self):
        return str(self._coords)


class TestCase(unittest.TestCase):
    def test_singledispatch(self):
        # the following demonstrates usage of a few methods
        v = Vector(5)              # construct five-dimensional <0, 0, 0, 0, 0>
        for i in range(1,6):
            v[i-1] = i
        print(v.__mul__(3))
        print("type(v).__mul__'s registry:",type(v).__mul__.registry)
        type(v).__mul__(v, 3)
        print(v*3)

if __name__ == "__main__":
    unittest.main() 

这次 。 v.__mul__(3)有错误：

 Traceback (most recent call last): File "test.py", line 73, in test_singledispatch type(v).__mul__(v, 3) File "/usr/lib/python3.4/functools.py", line 708, in wrapper return dispatch(args[0].__class__)(*args, **kw) TypeError: 'staticmethod' object is not callable

对我来说，静态方法应该像实例方法一样。

Answer 1

你根本不能在方法上使用functools.singledispatch ，至少不能作为装饰器。 Python 3.8 添加了一个新选项，仅用于方法： functools.singledispatchmethod() 。

这里还没有定义Vector并不重要； 任何方法的第一个参数始终是self ，而您在这里的第二个参数使用单分派。

因为装饰器在创建类对象之前应用于函数对象，所以您也可以在类主体之外将“方法”注册为函数，因此您可以访问Vector名称：

class Vector(object):

    @functools.singledispatch
    def __mul__(self, other):
        return NotImplemented

@Vector.__mul__.register(int)
@Vector.__mul__.register(Vector)                
def _(self, other):
    result = Vector(len(self))           # start with vector of zeros
    for j in range(len(self)):
        result[j] = self[j]*other
    return result

对于不受支持的类型，您需要返回NotImplemented单例，而不是引发异常。 这样 Python 也会尝试逆操作。

但是，由于无论如何调度都会在这里输入错误的参数（ self ），因此您必须想出自己的单一调度机制。

如果你真的想使用@functools.singledispatch你不得不委托给一个普通的功能，与参数反演：

@functools.singledispatch
def _vector_mul(other, self):
    return NotImplemented

class Vector(object):
    def __mul__(self, other):
        return _vector_mul(other, self)


@_vector_mul.register(int)
def _vector_int_mul(other, self):
    result = Vector(len(self))
    for j in range(len(self)):
        result[j] = self[j] * other
    return result

至于您使用__init__mul__的更新： v * 3不会转换为v.__mul__(3) 。 它被转换为type(v).__mul__(v, 3) ，请参阅 Python 数据模型参考中的特殊方法查找。 这总是绕过直接在实例上设置的任何方法。

这里type(v)是Vector ； Python 查找函数，这里不会使用绑定方法。 同样，因为functools.singledispatch在第一个参数上分派，所以你不能直接在Vector的方法上使用单分派，因为第一个参数总是一个Vector实例。

换句话说，Python不会使用你在__init__mul__ self设置的方法； 永远不会在实例上查找特殊方法，请参阅数据模型文档中的特殊方法查找。

Python 3.8 添加的functools.singledispatchmethod()选项使用一个类作为实现描述符协议的装饰器，就像方法一样。 这让它在绑定之前处理调度（因此在self将被添加到参数列表之前），然后绑定singledispatch调度调度器返回的注册函数。 此实现的源代码与较旧的 Python 版本完全兼容，因此您可以改用它：

from functools import singledispatch, update_wrapper

# Python 3.8 singledispatchmethod, backported
class singledispatchmethod:
    """Single-dispatch generic method descriptor.

    Supports wrapping existing descriptors and handles non-descriptor
    callables as instance methods.
    """

    def __init__(self, func):
        if not callable(func) and not hasattr(func, "__get__"):
            raise TypeError(f"{func!r} is not callable or a descriptor")

        self.dispatcher = singledispatch(func)
        self.func = func

    def register(self, cls, method=None):
        """generic_method.register(cls, func) -> func

        Registers a new implementation for the given *cls* on a *generic_method*.
        """
        return self.dispatcher.register(cls, func=method)

    def __get__(self, obj, cls):
        def _method(*args, **kwargs):
            method = self.dispatcher.dispatch(args[0].__class__)
            return method.__get__(obj, cls)(*args, **kwargs)

        _method.__isabstractmethod__ = self.__isabstractmethod__
        _method.register = self.register
        update_wrapper(_method, self.func)
        return _method

    @property
    def __isabstractmethod__(self):
        return getattr(self.func, '__isabstractmethod__', False)

并将其应用于您的Vector()类。 在创建类之后，您仍然必须为单个调度注册Vector实现，因为只有这样您才能为该类注册一个调度：

class Vector(object):
    def __init__(self, d):
        self._coords = [0] * d

    def __setitem__(self, key, value):
        self._coords[key] = value

    def __getitem__(self, item):
        return self._coords[item]

    def __len__(self):
        return len(self._coords)

    def __repr__(self):
        return f"Vector({self._coords!r})"

    def __str__(self):
        return str(self._coords)

    @singledispatchmethod
    def __mul__(self, other):
        return NotImplemented

    @__mul__.register
    def _int_mul(self, other: int):
        result = Vector(len(self))
        for j in range(len(self)):
            result[j] = self[j] * other
        return result

@Vector.__mul__.register
def _vector_mul(self, other: Vector):
    return sum(sc * oc for sc, oc in zip(self._coords, other._coords))

您当然也可以首先创建一个子类并基于它进行调度，因为调度也适用于子类：

class _Vector(object):
    def __init__(self, d):
        self._coords = [0] * d

class Vector(_Vector):
    def __setitem__(self, key, value):
        self._coords[key] = value

    def __getitem__(self, item):
        return self._coords[item]

    def __len__(self):
        return len(self._coords)

    def __repr__(self):
        return f"{type(self).__name__}({self._coords!r})"

    def __str__(self):
        return str(self._coords)

    @singledispatchmethod
    def __mul__(self, other):
        return NotImplemented

    @__mul__.register
    def _int_mul(self, other: int):
        result = Vector(len(self))
        for j in range(len(self)):
            result[j] = self[j] * other
        return result

    @__mul__.register
    def _vector_mul(self, other: _Vector):
        return sum(sc * oc for sc, oc in zip(self._coords, other._coords))

Answer 2

这是一个有点难看，因为你需要推迟结合执行Vector / Vector乘法后才Vector实际上定义。 但是这个想法是单分派函数需要第一个参数是任意类型的，所以Vector.__mul__将调用该函数并将self作为第二个参数。

import functools

class Vector:

    def __mul__(self, other):
        # Python has already dispatched Vector() * object() here, so
        # swap the arguments so that our single-dispatch works. Note
        # that in general if a*b != b*a, then the _mul_by_other
        # implementations need to compensate.
        return Vector._mul_by_other(other, self)

    @functools.singledispatch
    def _mul_by_other(x, y):
        raise NotImplementedError("Can't multiply vector by {}".format(type(x)))

    @_mul_by_other.register(int)
    def _(x, y):
        print("Multiply vector by int")

@Vector._mul_by_other.register(Vector)
def _(x, y):
    print("Multiply vector by another vector")

x = Vector()
y = Vector()
x * 3
x * y
try:
    x * "foo"
except NotImplementedError:
    print("Caught attempt to multiply by string")