Python 有办法将任意值转为字符串：将它传入repr() 或str() 函数。

函数str() 用于将值转化为适于人阅读的形式，而repr() 转化为供解释器读取的形式。

在python的官方API中这样解释repr()函数：

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" 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" />

repr（）函数得到的字符串通常可以用来重新获得该对象，repr（）的输入对python比较友好。通常情况下obj==eval(repr(obj))这个等式是成立的。

>>> obj='I love Python'

>>> obj==eval(repr(obj))

True

而str()函数这没有这个功能

>>> obj==eval(str(obj))

Traceback (most recent call last):

  File "<stdin>", line 1, in <module>

  File "<string>", line 1

    I love Python

         ^

repr()函数：

>>>repr([0,1,2,3])

'[0,1,2,3]'

>>> repr('Hello')

"'Hello'"

>>> str(1.0/7.0)

'0.142857142857'

>>> repr(1.0/7.0)

'0.14285714285714285'

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