• 『流畅的Python』第10章笔记_序列类型


    一、基础知识

    “__”前缀:私有属性、方法,在__dict__中存储时被改写为“_类名__”前缀

    “_”前缀:是约定俗成的保护属性、方法,不过编译器不会对之采取任何处理

    二、class特殊方法介绍

    在第9章的双元素基础上,我们扩展为任意元素长度的向量,并探讨了相关方法的使用:

    __getattr__(self, name):

    result = obj.name 会调用builtin函数getattr(obj,'name')查找对应属性,如果没有name属性则调用obj.__getattr__('name')方法,再无则报错

    __setattr__(self, name, value):

    obj.name = value 会调用builtin函数setattr(obj,'name',value)设置对应属性,如果设置了__setattr__('name',value)方法则优先调用此方法,而非直接将值存入__dict__并新建属性

    自己改写时一般添加一些预先处理,最后还是要用到继承super().__setattr__(name, value)

    __getitem__(self, item):

    在函数体内,会将self[index]的外部表达中的index转化为slice对象,方便处理

    __setitem__(self, key, value):

    没有用到,用于设置可以self[key]形式查询的数据,即支持序列索引和散列表两种形式

    实现程序如下:

    import math
    import reprlib
    from array import array
    import numbers  # 提供整数基类
    import functools
    import operator  # 亦或方法,虽然'^='功能一样
    import itertools
    
    
    class Vector:
        typecode = 'd'
        shortcut_names = 'xyzt'
    
        def __init__(self, components):
            self._components = array(self.typecode, components)
    
        def __iter__(self):
            return iter(self._components)
    
        def __repr__(self):
            components = reprlib.repr(self._components)
            components = components[components.find('['):-1]
            return 'Vector({})'.format(components)
    
        def __str__(self):
            return str(tuple(self))
    
        def __bytes__(self):
            return (bytes([ord(self.typecode)]) +
                    bytes(self._components))
    
        def __abs__(self):
            return math.sqrt(sum(x*x for x in self))
    
        def __bool__(self):
            return bool(abs(self))
    
        @classmethod
        def frombytes(cls, octets):
            typecode = chr(octets[0])
            memv = memoryview(octets[1:]).cast(typecode)
            return cls(memv)
    
        # ==========支持切片操作==========
        def __len__(self):
            return len(self._components)
    
        # def __getitem__(self, index):
        #     # 支持切片类似[1:2]
        #     # 但是Vector的切片是数组,而非Vector实例
        #     # 实际上在方法内部index被转化为了slice对象
        #     return self._components[index]
    
        # 和__setitem_对应(此处未实现)
        def __getitem__(self, index):  # 会将self[index]的index转化为slice对象
            cls = type(self)
            if isinstance(index, slice):
                return cls(self._components[index])
            elif isinstance(index, numbers.Integral):
                return self._components[index]
            else:
                raise TypeError('indices must be integers')
    
        # ==========动态存取属性==========
        # xyzt四个字母分别指代前四个分量,调用如'v.x',
        # 设置属性时保证不能使用小写字母a-z为实例添加属性
        def __getattr__(self, name):
            cls = type(self)
            if len(name) == 1:
                pos = cls.shortcut_names.find(name)
                if 0 <= pos < len(self._components):
                    return self._components[pos]
            raise AttributeError('object has no attribute')
    
        def __setattr__(self, name, value):
            cls = type(self)
            if len(name) == 1:
                if name in cls.shortcut_names:
                    error = 'readonly attribute {attr_name!r}'
                elif name.islower():
                    error = "can't set attributes 'a' to 'z' in {cls_name!r}"
                else:
                    error = ''  # bool('')=False
                if error:
                    raise AttributeError(error.format(cls_name=cls.__name__,
                                                      attr_name=name))
            super().__setattr__(name, value)
    
        # ==========哈希方法==========
        def __hash__(self):
            # hashes = map(hash, self._components)
            hashes = (hash(x) for x in self._components)
            return functools.reduce(operator.xor, hashes, initial=0)
        # reduce的initial表示初始值,如果序列为空则返回初始值,否则
        # 初始值加到序列首,对亦或运算初始值应该为0
    
        def __eq__(self, other):
            # ----------version1----------
            # 原版(注释句)在向量很长时消耗内存过巨,需要构建两个元组
            # return tuple(self) == tuple(other)
            # ----------version2----------
            # if len(self) != len(other):
            #     return False
            # for a, b in zip(self, other):
            #     if a != b:
            #         return False
            # return True
            # ----------version3----------
            return len(self) == len(other) and 
                   all(a == b for a, b in zip(self, other))
    
        # format规范化输出
        def angle(self, n):
            r = math.sqrt(sum(x * x for x in self._components))
            a = math.atan2(r, self[n-1])
            if (n == len(self) - 1) and (self[-1] < 0):
                return math.pi * 2 - a
            else:
                return a
    
        def angles(self):
            return (self.angle(n) for n in range(1, len(self)))
    
        def __format__(self, format_spec=''):
            if format_spec.endswith('h'):
                format_spec = format_spec[:-1]
                # r, angle1,angle2,……
                coords = itertools.chain([abs(self)], self.angles())
                out_fmt = '<{}>'
            else:
                coords = self
                out_fmt = '({})'
            components = (format(c, format_spec) for c in coords)
            return out_fmt.format(','.join(components))
    
    
    if __name__ == "__main__":
        print(Vector(range(10)))
        v = Vector(range(7))
        print(v)
        print(v[3])
        print(v.x)
    
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  • 原文地址:https://www.cnblogs.com/hellcat/p/9407631.html
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