`>>> 和有什么不一样?some_object` 和 `>>>在 Python 解释器中打印 some_object`? [英] What is the difference between `>>> some_object` and `>>> print some_object` in the Python interpreter?

问题描述

在解释器中你可以只写一个对象的名字，例如一个列表 a = [1, 2, 3, u"hello"] 在解释器提示符下，如下所示:

<预><代码>>>>一个[1, 2, 3, 你见鬼xf6']

或者你可以这样做:

<预><代码>>>>打印一个[1, 2, 3, 你见鬼xf6']

这对于列表来说似乎是等价的.目前我正在使用 hdf5 来管理一些数据，我意识到上面提到的两种方法之间存在差异.鉴于:

 with tables.openFile("tutorial.h5", mode = "w", title = "Some Title") 作为 h5file:group = h5file.createGroup("/", '节点', '节点信息')table.table = h5file.createTable(group, 'readout', Node, "Readout example")

输出

打印 h5file

不同于

<预><代码>>>>h5文件

所以我想知道是否有人可以解释 Python 在这两种情况下的行为差异?

解决方案

在终端中键入一个对象会调用 __repr__()，它用于详细表示您正在打印的对象(无歧义).当你告诉打印"某些东西时，你正在调用 __str__() 并因此要求一些人类可读的东西.

Alex Martelli 这里.线程中的其他回复也可能说明差异.

例如，看看日期时间对象.

<预><代码>>>>导入日期时间>>>现在 = datetime.datetime.now()

比较...

<预><代码>>>>现在出: datetime.datetime(2011, 8, 18, 15, 10, 29, 827606)

到...

<预><代码>>>>现在打印出:2011-08-18 15:10:29.827606

希望能让它更清楚一点！

In the interpreter you can just write the name of an object e.g. a list a = [1, 2, 3, u"hellö"] at the interpreter prompt like this:

>>> a
[1, 2, 3, u'hellxf6']

or you can do:

>>> print a
[1, 2, 3, u'hellxf6']

which seems equivalent for lists. At the moment I am working with hdf5 to manage some data and I realized that there is a difference between the two methods mentioned above. Given:

with tables.openFile("tutorial.h5", mode = "w", title = "Some Title") as h5file:
    group = h5file.createGroup("/", 'node', 'Node information')
    tables.table = h5file.createTable(group, 'readout', Node, "Readout example")

The output of

print h5file

differs from

>>> h5file

So I was wondering if someone could explain Python's behavioral differences in these two cases?

解决方案

Typing an object into the terminal calls __repr__(), which is for a detailed representation of the object you are printing (unambiguous). When you tell something to 'print', you are calling __str__() and therefore asking for something human readable.

Alex Martelli gave a great explanation here. Other responses in the thread might also illuminate the difference.

For example, take a look at datetime objects.

>>> import datetime
>>> now = datetime.datetime.now()

Compare...

>>> now
Out: datetime.datetime(2011, 8, 18, 15, 10, 29, 827606)

to...

>>> print now
Out: 2011-08-18 15:10:29.827606

Hopefully that makes it a little more clear!

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