面向对象进阶
2019-04-11 10:35:45来源:博客园 阅读 ()
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isinstance和issubclass
isinstance(obj,cls)检查是否obj是否是类 cls 的对象
class Foo(object): pass obj = Foo() isinstance(obj, Foo)
issubclass(sub, super)检查sub类是否是 super 类的派生类
class Foo(object): pass class Bar(Foo): pass issubclass(Bar, Foo)
反射
1 什么是反射
反射的概念是由Smith在1982年首次提出的,主要是指程序可以访问、检测和修改它本身状态或行为的一种能力(自省)。这一概念的提出很快引发了计算机科学领域关于应用反射性的研究。它首先被程序语言的设计领域所采用,并在Lisp和面向对象方面取得了成绩。
2 python面向对象中的反射:通过字符串的形式操作对象相关的属性。python中的一切事物都是对象(都可以使用反射)
四个可以实现自省的函数
下列方法适用于类和对象(一切皆对象,类本身也是一个对象)
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def hasattr(*args, **kwargs): # real signature unknown """ Return whether the object has an attribute with the given name. This is done by calling getattr(obj, name) and catching AttributeError. """ pass
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def getattr(object, name, default=None): # known special case of getattr """ getattr(object, name[, default]) -> value Get a named attribute from an object; getattr(x, 'y') is equivalent to x.y. When a default argument is given, it is returned when the attribute doesn't exist; without it, an exception is raised in that case. """ pass getattr
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def setattr(x, y, v): # real signature unknown; restored from __doc__ """ Sets the named attribute on the given object to the specified value. setattr(x, 'y', v) is equivalent to ``x.y = v'' """ pass setattr
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def delattr(x, y): # real signature unknown; restored from __doc__ """ Deletes the named attribute from the given object. delattr(x, 'y') is equivalent to ``del x.y'' """ pass delattr
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class Func(object): def __init__(self, name): self.name = name def say_name(self): print("细脖大头鬼--%s" % self.name) func = Func("房书安") # 检查是否有属性 print(hasattr(func, 'name')) print(hasattr(func, 'say_name')) # 获取属性 name = getattr(func, 'name') print(name) say_name = getattr(func, 'say_name') say_name() print(getattr(func, 'age','不存在')) # 设置属性 setattr(func, 'age', 50) setattr(func, 'show_name', lambda self:self.name+'nb') print(func.__dict__) print(func.show_name(func)) # 删除属性 delattr(func, 'age') delattr(func, 'show_name') delattr(func, 'show_age') #不存在就报错
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class Foo(object): staticField = "徐良" def __init__(self): self.name = '房书安' def func(self): return 'func' @staticmethod def bar(): return 'bar' print(getattr(Foo, 'staticField')) print(getattr(Foo, 'func')) print(getattr(Foo, 'bar'))
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import sys def s1(): print('s1') def s2(): print('s2') this_module = sys.modules[__name__] hasattr(this_module, 's1') getattr(this_module, 's2')
导入其他模块,利用反射查找该模块是否存在某个方法
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def test(): print('from the test') # 文件名字 module_test.py
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import module_test as obj #obj.test() print(hasattr(obj,'test')) getattr(obj,'test')() # 当前文件:index.py
__str__和__repr__
改变对象的字符串显示__str__,__repr__
自定制格式化字符串__format__
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format_dict={ 'nat':'{obj.name}-{obj.addr}-{obj.type}',#学校名-学校地址-学校类型 'tna':'{obj.type}:{obj.name}:{obj.addr}',#学校类型:学校名:学校地址 'tan':'{obj.type}/{obj.addr}/{obj.name}',#学校类型/学校地址/学校名 } class School: def __init__(self,name,addr,type): self.name=name self.addr=addr self.type=type def __repr__(self): return 'School(%s,%s)' %(self.name,self.addr) def __str__(self): return '(%s,%s)' %(self.name,self.addr) def __format__(self, format_spec): # if format_spec if not format_spec or format_spec not in format_dict: format_spec='nat' fmt=format_dict[format_spec] return fmt.format(obj=self) s1=School('oldboy1','北京','私立') print('from repr: ',repr(s1)) print('from str: ',str(s1)) print(s1) ''' str函数或者print函数--->obj.__str__() repr或者交互式解释器--->obj.__repr__() 如果__str__没有被定义,那么就会使用__repr__来代替输出 注意:这俩方法的返回值必须是字符串,否则抛出异常 ''' print(format(s1,'nat')) print(format(s1,'tna')) print(format(s1,'tan')) print(format(s1,'asfdasdffd'))
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class B: def __str__(self): return 'str : class B' def __repr__(self): return 'repr : class B' b=B() print('%s'%b) print('%r'%b)
item系列
__getitem__ 、__setitem__ 、__delitem__
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class Foo: def __init__(self,name): self.name=name def __getitem__(self, item): print(self.__dict__[item]) def __setitem__(self, key, value): self.__dict__[key]=value def __delitem__(self, key): print('del obj[key]时,我执行') self.__dict__.pop(key) def __delattr__(self, item): print('del obj.key时,我执行') self.__dict__.pop(item) f1=Foo('nb') f1['age']=18 f1['age1']=19 del f1.age1 del f1['age'] f1['name']='朱亮' print(f1.__dict__)
__del__
析构方法,当对象在内存中被释放时,自动触发执行。
注:此方法一般无须定义,因为Python是一门高级语言,程序员在使用时无需关心内存的分配和释放,因为此工作都是交给Python解释器来执行,所以,析构函数的调用是由解释器在进行垃圾回收时自动触发执行的。
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class Foo: def __del__(self): print('执行我啦') f1=Foo() del f1 print('------->') #输出结果 执行我啦 ------->
__new__
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class A: def __init__(self): self.x = 1 print('in init function') def __new__(cls, *args, **kwargs): print('in new function') return object.__new__(A) a = A() print(a.x)
__call__
对象后面加括号,触发执行。
注:构造方法的执行是由创建对象触发的,即:对象 = 类名() ;而对于 __call__ 方法的执行是由对象后加括号触发的,即:对象() 或者 类()()
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class Foo: def __init__(self): pass def __call__(self, *args, **kwargs): print('__call__') obj = Foo() # 执行 __init__ obj() # 执行 __call__
with和__enter__, __exit__
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class A: def __enter__(self): print('before') def __exit__(self, exc_type, exc_val, exc_tb): print('after') with A() as a: print('123')
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class A: def __init__(self): print('init') def __enter__(self): print('before') def __exit__(self, exc_type, exc_val, exc_tb): print('after') with A() as a: print('123')
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class Myfile: def __init__(self,path,mode='r',encoding = 'utf-8'): self.path = path self.mode = mode self.encoding = encoding def __enter__(self): self.f = open(self.path, mode=self.mode, encoding=self.encoding) return self.f def __exit__(self, exc_type, exc_val, exc_tb): self.f.close() with Myfile('file',mode='w') as f: f.write('wahaha')
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import pickle class MyPickledump: def __init__(self,path): self.path = path def __enter__(self): self.f = open(self.path, mode='ab') return self def dump(self,content): pickle.dump(content,self.f) def __exit__(self, exc_type, exc_val, exc_tb): self.f.close() class Mypickleload: def __init__(self,path): self.path = path def __enter__(self): self.f = open(self.path, mode='rb') return self def __exit__(self, exc_type, exc_val, exc_tb): self.f.close() def load(self): return pickle.load(self.f) def loaditer(self): while True: try: yield self.load() except EOFError: break # with MyPickledump('file') as f: # f.dump({1,2,3,4}) with Mypickleload('file') as f: for item in f.loaditer(): print(item)
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import pickle class MyPickledump: def __init__(self,path): self.path = path def __enter__(self): self.f = open(self.path, mode='ab') return self def dump(self,content): pickle.dump(content,self.f) def __exit__(self, exc_type, exc_val, exc_tb): self.f.close() class Mypickleload: def __init__(self,path): self.path = path def __enter__(self): self.f = open(self.path, mode='rb') return self def __exit__(self, exc_type, exc_val, exc_tb): self.f.close() def __iter__(self): while True: try: yield pickle.load(self.f) except EOFError: break # with MyPickledump('file') as f: # f.dump({1,2,3,4}) with Mypickleload('file') as f: for item in f: print(item)
__len__
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class A: def __init__(self): self.a = 1 self.b = 2 def __len__(self): return len(self.__dict__) a = A() print(len(a))
__hash__
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class A: def __init__(self): self.a = 1 self.b = 2 def __hash__(self): return hash(str(self.a)+str(self.b)) a = A() print(hash(a))
__eq__
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class A: def __init__(self): self.a = 1 self.b = 2 def __eq__(self,obj): if self.a == obj.a and self.b == obj.b: return True a = A() b = A() print(a == b)
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class Person: def __init__(self,name,age,sex): self.name = name self.age = age self.sex = sex def __hash__(self): return hash(self.name+self.sex) def __eq__(self, other): if self.name == other.name and self.sex == other.sex:return True p_lst = [] for i in range(84): p_lst.append(Person('zorro',i,'man')) print(p_lst) print(set(p_lst))
深拷贝、浅拷贝
1. 浅拷贝
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浅拷贝是对于一个对象的顶层拷贝
通俗的理解是:拷贝了引用,并没有拷贝内容
2. 深拷贝
-
深拷贝是对于一个对象所有层次的拷贝(递归)
进一步理解深拷贝
3. 拷贝的其他方式
-
分片表达式可以赋值一个序列
-
字典的copy方法可以拷贝一个字典
4. 注意点
浅拷贝对不可变类型和可变类型的copy不同
-
copy.copy对于可变类型,会进行浅拷贝
-
copy.copy对于不可变类型,不会拷贝,仅仅是指向
copy.copy和copy.deepcopy的区别
copy.copy
copy.deepcopy
原文:http://www.cnblogs.com/Eva-J/articles/7351812.html
原文链接:https://www.cnblogs.com/ForT/p/10665272.html
如有疑问请与原作者联系
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