在python语言里,__str__一般是格式是这样的。

class A:

def __str__(self):

return "this is in str"

事实上,__str__是被print函数调用的,一般都是return一个什么东西。这个东西应该是以字符串的形式表现的。如果不是要用str()函数转换。当你打印一个类的时候,那么print首先调用的就是类里面的定义的__str__,比如:str.py

如下脚本:

class  ybl():
name='yubenliu'
def __str__(self):
return self.name
t=ybl()
print t
print t.__str__() print type(t)

返回的结果是:

aaarticlea/png;base64,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" alt="" />

return 返回的只可以是字符串如果是其他的类型就会报错

在PYTHON中默认的类都__STR__这个属性如

aaarticlea/png;base64,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" alt="" />

用于print调用如:

>>> t={}

>>> t['1'] = "hello"

>>> t['2'] = "world"
>>> t   #等于 print t
{'1': 'hello', '2': 'world'}
>>> t.__str__()
"{'1': 'hello', '2': 'world'}"

大家可以看到一个字典,print t 和 t.__str__()是一样的。只不过__str__()将字典内容以字符串形式输出

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