PEP 3141 -- 数值类型的层次结构(A Type Hierarchy for Numbers)
英文原文:https://www.python.org/dev/peps/pep-3141
采集日期:2020-02-27
PEP: 3141
Title: A Type Hierarchy for Numbers
Author: Jeffrey Yasskin [email protected]
Status: Final
Type: Standards Track
Created: 23-Apr-2007
Post-History: 25-Apr-2007, 16-May-2007, 02-Aug-2007
目录
- 摘要(Abstract)
- 原由(Rationale)
- 规范(Specification)
- 数值类(Numeric Classses)
- 运算方法和魔法方法的改动(Changes to operations and magic methods)
- 实现类型时的注意事项(Notes for type implementors)
- 加入其他数值型抽象基类(Adding More Numeric ABCs)
- 算术运算的实现(Implementing the arithmetic operations)
- 未被接受的其他提案(Rejected Alternatives)
- Decimal 类型(The Decimal Type)
- 参考文献(References)
- 致谢(Acknowledgements)
- 版权(Copyright)
摘要(Abstract)
本提案定义了数值类抽象基类(ABC,Abstract Base Class,PEP 3119)的层次结构(hierarchy)。这里提出了
Number :> Complex :> Real :> Rational :> Integral
的层级,A :> B
意味着“A 是 B 的超类型”。这种层次结构的制定受到了 Scheme 数值类型塔的启发。
原由(Rationale)
用数值作参数的函数应能确定这些数值的属性,并且当语言中增加了基于类型的重载时,应能依据参数类型实现函数重载。比如,切片(slice)操作要求参数为整数类型(
Integral
),而 math
模块中的函数则要求参数为实数类型(Real
)。
规范(Specification)
本文定义了一组抽象基类,并给出一些方法的通常实现方式。这里用到了 PEP 3119 中的术语,但这种层次结构对于任何用于类定义的系统性解决方案都颇具意义。
标准库中的类型检查过程应该采用这些类,而不是采用具体(concrete)的内置类型。
数值类(Numeric Classses)
下面就从一个 Number 类开始吧,以便大家把数值的类型先模糊掉。该类只是为了便于重载,并不支持任何操作。
class Number(metaclass=ABCMeta): pass
复数的大多数实现类都是可散列(hashable)的,但如果要绝对可靠,则必须显式地进行检查,验证数值类型的层次结构是否支持可变(mutable)数值。
class Complex(Number):
"""Complex defines the operations that work on the builtin complex type.
In short, those are: conversion to complex, bool(), .real, .imag,
+, -, *, /, **, abs(), .conjugate(), ==, and !=.
If it is given heterogenous arguments, and doesn't have special
knowledge about them, it should fall back to the builtin complex
type as described below.
"""
@abstractmethod
def __complex__(self):
"""Return a builtin complex instance."""
def __bool__(self):
"""True if self != 0."""
return self != 0
@abstractproperty
def real(self):
"""Retrieve the real component of this number.
This should subclass Real.
"""
raise NotImplementedError
@abstractproperty
def imag(self):
"""Retrieve the real component of this number.
This should subclass Real.
"""
raise NotImplementedError
@abstractmethod
def __add__(self, other):
raise NotImplementedError
@abstractmethod
def __radd__(self, other):
raise NotImplementedError
@abstractmethod
def __neg__(self):
raise NotImplementedError
def __pos__(self):
"""Coerces self to whatever class defines the method."""
raise NotImplementedError
def __sub__(self, other):
return self + -other
def __rsub__(self, other):
return -self + other
@abstractmethod
def __mul__(self, other):
raise NotImplementedError
@abstractmethod
def __rmul__(self, other):
raise NotImplementedError
@abstractmethod
def __div__(self, other):
"""a/b; should promote to float or complex when necessary."""
raise NotImplementedError
@abstractmethod
def __rdiv__(self, other):
raise NotImplementedError
@abstractmethod
def __pow__(self, exponent):
"""a**b; should promote to float or complex when necessary."""
raise NotImplementedError
@abstractmethod
def __rpow__(self, base):
raise NotImplementedError
@abstractmethod
def __abs__(self):
"""Returns the Real distance from 0."""
raise NotImplementedError
@abstractmethod
def conjugate(self):
"""(x+y*i).conjugate() returns (x-y*i)."""
raise NotImplementedError
@abstractmethod
def __eq__(self, other):
raise NotImplementedError
# __ne__ is inherited from object and negates whatever __eq__ does.
实数 Real
的抽象基类表明,数值在层次结构中处于实数的位置,并且支持内置 float
类型的全部操作。除了 NaN(本文基本忽略)之外,实数是完全有序的。
class Real(Complex):
"""To Complex, Real adds the operations that work on real numbers.
In short, those are: conversion to float, trunc(), math.floor(),
math.ceil(), round(), divmod(), //, %, <, <=, >, and >=.
Real also provides defaults for some of the derived operations.
"""
# XXX What to do about the __int__ implementation that's
# currently present on float? Get rid of it?
@abstractmethod
def __float__(self):
"""Any Real can be converted to a native float object."""
raise NotImplementedError
@abstractmethod
def __trunc__(self):
"""Truncates self to an Integral.
Returns an Integral i such that:
* i>=0 iff self>0;
* abs(i) <= abs(self);
* for any Integral j satisfying the first two conditions,
abs(i) >= abs(j) [i.e. i has "maximal" abs among those].
i.e. "truncate towards 0".
"""
raise NotImplementedError
@abstractmethod
def __floor__(self):
"""Finds the greatest Integral <= self."""
raise NotImplementedError
@abstractmethod
def __ceil__(self):
"""Finds the least Integral >= self."""
raise NotImplementedError
@abstractmethod
def __round__(self, ndigits:Integral=None):
"""Rounds self to ndigits decimal places, defaulting to 0.
If ndigits is omitted or None, returns an Integral,
otherwise returns a Real, preferably of the same type as
self. Types may choose which direction to round half. For
example, float rounds half toward even.
"""
raise NotImplementedError
def __divmod__(self, other):
"""The pair (self // other, self % other).
Sometimes this can be computed faster than the pair of
operations.
"""
return (self // other, self % other)
def __rdivmod__(self, other):
"""The pair (self // other, self % other).
Sometimes this can be computed faster than the pair of
operations.
"""
return (other // self, other % self)
@abstractmethod
def __floordiv__(self, other):
"""The floor() of self/other. Integral."""
raise NotImplementedError
@abstractmethod
def __rfloordiv__(self, other):
"""The floor() of other/self."""
raise NotImplementedError
@abstractmethod
def __mod__(self, other):
"""self % other
See
https://mail.python.org/pipermail/python-3000/2006-May/001735.html
and consider using "self/other - trunc(self/other)"
instead if you're worried about round-off errors.
"""
raise NotImplementedError
@abstractmethod
def __rmod__(self, other):
"""other % self"""
raise NotImplementedError
@abstractmethod
def __lt__(self, other):
"""< on Reals defines a total ordering, except perhaps for NaN."""
raise NotImplementedError
@abstractmethod
def __le__(self, other):
raise NotImplementedError
# __gt__ and __ge__ are automatically done by reversing the arguments.
# (But __le__ is not computed as the opposite of __gt__!)
# Concrete implementations of Complex abstract methods.
# Subclasses may override these, but don't have to.
def __complex__(self):
return complex(float(self))
@property
def real(self):
return +self
@property
def imag(self):
return 0
def conjugate(self):
"""Conjugate is a no-op for Reals."""
return +self
应把 Demo/classes/Rat.py 清除掉,将其升级为标准库中的 rational.py。这样就能实现有理数的抽象基类 Rational 了。
class Rational(Real, Exact):
""".numerator and .denominator should be in lowest terms."""
@abstractproperty
def numerator(self):
raise NotImplementedError
@abstractproperty
def denominator(self):
raise NotImplementedError
# Concrete implementation of Real's conversion to float.
# (This invokes Integer.__div__().)
def __float__(self):
return self.numerator / self.denominator
最后是整数类型:
class Integral(Rational):
"""Integral adds a conversion to int and the bit-string operations."""
@abstractmethod
def __int__(self):
raise NotImplementedError
def __index__(self):
"""__index__() exists because float has __int__()."""
return int(self)
def __lshift__(self, other):
return int(self) << int(other)
def __rlshift__(self, other):
return int(other) << int(self)
def __rshift__(self, other):
return int(self) >> int(other)
def __rrshift__(self, other):
return int(other) >> int(self)
def __and__(self, other):
return int(self) & int(other)
def __rand__(self, other):
return int(other) & int(self)
def __xor__(self, other):
return int(self) ^ int(other)
def __rxor__(self, other):
return int(other) ^ int(self)
def __or__(self, other):
return int(self) | int(other)
def __ror__(self, other):
return int(other) | int(self)
def __invert__(self):
return ~int(self)
# Concrete implementations of Rational and Real abstract methods.
def __float__(self):
"""float(self) == float(int(self))"""
return float(int(self))
@property
def numerator(self):
"""Integers are their own numerators."""
return +self
@property
def denominator(self):
"""Integers have a denominator of 1."""
return 1
运算方法和魔法方法的改动(Changes to operations and magic methods)
为了支持 float 和 int (Real 和 Integral)之间更细微的差别,下面给出一些新的魔法方法,以供相应的库函数调用。这些方法都会返回 Integral 而非 Real。
__trunc__(self)
,由新的内置方法trunc(x)
调用,返回 0 和x
之间离x
最近的整数。__floor__(self)
,由math.floor(x)
调用,返回<= x
的最大整数。__ceil__(self)
,由math.ceil(x)
调用,返回>= x
的最大整数。__round__(self)
,由round(x)
调用,返回离x
最近的整数,半数取整将依数据类型而定。在 3.0 版中float
将会修改为半数向偶数取整。这还有一个带两个参数的版本__round__(self, ndigits)
,由round(x, ndigits)
调用,将会返回实数。
在 2.6 版中,math.floor
、math.ceil
和 round
将仍旧返回浮点数。
float
实现的 int()
转换等效于 trunc()
。通常 int()
转换应该先尝试 __int__()
,若不存在再尝试 __trunc__()
。
complex.__{divmod,mod,floordiv,int,float}__
也消失了。若是能提供一个好的错误信息就完美了,但更重要的是别再出现在 help(complex)
里了。
实现类型时的注意事项(Notes for type implementors)
实现时应注意让相等的数值确实相等,并将他们散列为相同值。如果实数有两种不同的扩展实现,就可能有些微妙了。比如,复数类型如下实现 hash() 就较为合理:
def __hash__(self):
return hash(complex(self))
但对那些超出内置复数范围或精度的值应该多加小心。
加入其他数值型抽象基类(Adding More Numeric ABCs)
当然,数值型还可能会有更多的抽象基类,如果不考虑添加这些类的能力,数值类型的层次结构会很差劲。比如可以在
Complex
和 Real
之间加入以下 MyFoo
:
class MyFoo(Complex): ...
MyFoo.register(Real)
算术运算的实现(Implementing the arithmetic operations)
在混合运算时,要么调用两个参数类型已知的实现,要么先把两个参数都转换为最接近的内置类型再执行运算,这便是应该实现的算术运算。对于整型的子类型,这意味着 add 和 radd 应该定义如下:
class MyIntegral(Integral):
def __add__(self, other):
if isinstance(other, MyIntegral):
return do_my_adding_stuff(self, other)
elif isinstance(other, OtherTypeIKnowAbout):
return do_my_other_adding_stuff(self, other)
else:
return NotImplemented
def __radd__(self, other):
if isinstance(other, MyIntegral):
return do_my_adding_stuff(other, self)
elif isinstance(other, OtherTypeIKnowAbout):
return do_my_other_adding_stuff(other, self)
elif isinstance(other, Integral):
return int(other) + int(self)
elif isinstance(other, Real):
return float(other) + float(self)
elif isinstance(other, Complex):
return complex(other) + complex(self)
else:
return NotImplemented
对于复数类的子类,混合运算有五种不同的情况。这里将把上述所有未引用 MyIntegral 和 OtherTypeIKnowAbout 的代码作为“样板”(boilerplate)。a
将会是 A
的实例,而 A
是 Complex
的子类型(a : A <: Complex
),同样 b : B <: Complex
。于是 a + b
将会被如下处理:
- 如果 A 定义了可以接受 b 的 add 方法,万事大吉。
- 如果 A 降级(fall back)到采用样板代码,并要由 add 返回结果值,那么就算 B 定义了更明智的 radd 也会被忽略,于是样板代码应该返回 add 得出的 NotImplemented。(或者 A 可能压根儿就不去实现 add。
- 然后就轮到 B 的 radd。如果能接受 a 则万事大吉。
- 如果 B 降级到采用样板代码,因为没有其他方法可供尝试,所以这时会采用默认的实现代码。
- 如果 B <: A,Python 会在
A.__add__
之前先尝试调用B.__radd__
。这种做法没有问题,因为 B 的方法是在了解 A 的情况下实现的,因此它能够在传递给 Complex 之前处理这些实例。
如果 A<:Complex
和 B<:Real
不再共用其他信息,那么共用内置 Complex 类型的相关运算方法就是合理的,两者的 radd 都会落到 Complex 中,因此 a+b == b+a
。
未被接受的其他提案(Rejected Alternatives)
在 Number 形成之前,本 PEP 的最初版本曾经定义了一种受 Haskell Numeric Prelude 启发而得的数值类型层次结构,其中包括 MonoidUnderPlus、AdditiveGroup、Ring、Field,以及之前提及的其他几种数值类型。原本是希望这些对使用向量和矩阵的人有用,但是 NumPy 社区确实对此不感兴趣,同时还遇到了一个问题,即便
x
是 X <: MonoidUnderPlus
的实例,y
也是 Y <: MonoidUnderPlus
的实例,但 x + y
仍有可能没有意义。
于是后来 Number 又增加了更多分支,将高斯整数(Gaussian Integer)和 Z/nZ 之类的数值包含了进去,他们可能属于 Complex 但不一定要支持除法之类的运算。社区认为对于 Python 而言这种做法太复杂了,因此本提案现在缩小了规模,更接近于 Scheme 数值类型塔。
Decimal 类型(The Decimal Type)
经与作者协商,决定目前不应将 Decimal 类型加入数值类型塔中。
参考文献(References)
抽象基类介绍(http://www.python.org/dev/peps/pep-3119/)
可能的 Python 3K 类树?Bill Janssen 写的 Wiki(http://wiki.python.org/moin/AbstractBaseClasses)
NumericPrelude:数值类层级关系的实验性替代方案(http://darcs.haskell.org/numericprelude/docs/html/index.html)
Scheme 数值类型塔(https://groups.csail.mit.edu/mac/ftpdir/scheme-reports/r5rs-html/r5rs_8.html#SEC50)
致谢(Acknowledgements)
感谢 Neal Norwitz 第一时间鼓励我写下本 PEP,感谢 Travis Oliphant 指出 Numpy 用户对数(algebraic)的概念真不太在意,感谢 Alan Isaac 提醒我 Scheme 已经完成了本文相关体系的构建,感谢 Guido van Rossum 和邮件列表中的很多人帮我完善了概念。
版权(Copyright)
本文已在公共领域发布。
原文地址:https://www.cnblogs.com/popapa/p/PEP3141.html