Python的切片表示法是如何工作的?也就是说:当我编写[x:y:z]、a[:]、a]::2]等代码时,我如何理解哪些元素最终会出现在切片中?请在适当的地方附上参考资料。


另请参见:为什么切片和范围上限是互斥的?


当前回答

上面的答案不讨论切片分配。为了理解切片分配,可以在ASCII艺术中添加另一个概念:

                +---+---+---+---+---+---+
                | P | y | t | h | o | n |
                +---+---+---+---+---+---+
Slice position: 0   1   2   3   4   5   6
Index position:   0   1   2   3   4   5

>>> p = ['P','y','t','h','o','n']
# Why the two sets of numbers:
# indexing gives items, not lists
>>> p[0]
 'P'
>>> p[5]
 'n'

# Slicing gives lists
>>> p[0:1]
 ['P']
>>> p[0:2]
 ['P','y']

一种启发式方法是,对于从零到n的切片,思考:“零是开始,从开始开始,在列表中取n个项目”。

>>> p[5] # the last of six items, indexed from zero
 'n'
>>> p[0:5] # does NOT include the last item!
 ['P','y','t','h','o']
>>> p[0:6] # not p[0:5]!!!
 ['P','y','t','h','o','n']

另一种启发式方法是,“对于任何一个切片,用零替换开头,应用前面的启发式方法获得列表的结尾,然后将第一个数字向后计数,以从开头删除项目”

>>> p[0:4] # Start at the beginning and count out 4 items
 ['P','y','t','h']
>>> p[1:4] # Take one item off the front
 ['y','t','h']
>>> p[2:4] # Take two items off the front
 ['t','h']
# etc.

切片分配的第一个规则是,由于切片返回一个列表,所以切片分配需要一个列表(或其他可迭代的):

>>> p[2:3]
 ['t']
>>> p[2:3] = ['T']
>>> p
 ['P','y','T','h','o','n']
>>> p[2:3] = 't'
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
TypeError: can only assign an iterable

切片分配的第二个规则(您也可以在上面看到)是,无论切片索引返回列表的哪个部分,都是由切片分配更改的相同部分:

>>> p[2:4]
 ['T','h']
>>> p[2:4] = ['t','r']
>>> p
 ['P','y','t','r','o','n']

切片分配的第三条规则是,分配的列表(可迭代)不必具有相同的长度;索引切片被简单地切片,并被分配的任何内容整体替换:

>>> p = ['P','y','t','h','o','n'] # Start over
>>> p[2:4] = ['s','p','a','m']
>>> p
 ['P','y','s','p','a','m','o','n']

最难习惯的部分是分配给空切片。使用启发式1和2,很容易让你的头脑围绕空切片进行索引:

>>> p = ['P','y','t','h','o','n']
>>> p[0:4]
 ['P','y','t','h']
>>> p[1:4]
 ['y','t','h']
>>> p[2:4]
 ['t','h']
>>> p[3:4]
 ['h']
>>> p[4:4]
 []

然后,一旦您看到了这一点,将切片分配给空切片也是有意义的:

>>> p = ['P','y','t','h','o','n']
>>> p[2:4] = ['x','y'] # Assigned list is same length as slice
>>> p
 ['P','y','x','y','o','n'] # Result is same length
>>> p = ['P','y','t','h','o','n']
>>> p[3:4] = ['x','y'] # Assigned list is longer than slice
>>> p
 ['P','y','t','x','y','o','n'] # The result is longer
>>> p = ['P','y','t','h','o','n']
>>> p[4:4] = ['x','y']
>>> p
 ['P','y','t','h','x','y','o','n'] # The result is longer still

请注意,因为我们没有更改切片的第二个编号(4),所以插入的项目总是紧靠“o”堆叠,即使我们分配给空切片也是如此。因此,空切片分配的位置是非空切片分配位置的逻辑扩展。

稍微后退一点,当你继续进行我们的切片开始计数过程时会发生什么?

>>> p = ['P','y','t','h','o','n']
>>> p[0:4]
 ['P','y','t','h']
>>> p[1:4]
 ['y','t','h']
>>> p[2:4]
 ['t','h']
>>> p[3:4]
 ['h']
>>> p[4:4]
 []
>>> p[5:4]
 []
>>> p[6:4]
 []

通过切片,一旦你完成,你就完成了;它不会开始向后倾斜。在Python中,除非使用负数明确要求,否则不会获得负的步幅。

>>> p[5:3:-1]
 ['n','o']

“一旦你完成了,你就完成了”规则会产生一些奇怪的后果:

>>> p[4:4]
 []
>>> p[5:4]
 []
>>> p[6:4]
 []
>>> p[6]
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
IndexError: list index out of range

事实上,与索引相比,Python切片具有奇怪的防错误性:

>>> p[100:200]
 []
>>> p[int(2e99):int(1e99)]
 []

这有时会派上用场,但也会导致一些奇怪的行为:

>>> p
 ['P', 'y', 't', 'h', 'o', 'n']
>>> p[int(2e99):int(1e99)] = ['p','o','w','e','r']
>>> p
 ['P', 'y', 't', 'h', 'o', 'n', 'p', 'o', 'w', 'e', 'r']

根据您的应用程序,这可能。。。或者可能不。。。成为你在那里所希望的!


以下是我的原始答案。它对很多人都很有用,所以我不想删除它。

>>> r=[1,2,3,4]
>>> r[1:1]
[]
>>> r[1:1]=[9,8]
>>> r
[1, 9, 8, 2, 3, 4]
>>> r[1:1]=['blah']
>>> r
[1, 'blah', 9, 8, 2, 3, 4]

这也可以澄清切片和索引之间的区别。

其他回答

我不认为Python教程图(在各种其他答案中引用)是好的,因为这个建议适用于积极的步幅,但不适用于消极的步幅。

这是一个图表:

 +---+---+---+---+---+---+
 | P | y | t | h | o | n |
 +---+---+---+---+---+---+
 0   1   2   3   4   5   6
-6  -5  -4  -3  -2  -1

从图中,我希望[-4,-6,-1]是yP,但它是ty。

>>> a = "Python"
>>> a[2:4:1] # as expected
'th'
>>> a[-4:-6:-1] # off by 1
'ty'

始终有效的方法是在字符或槽中思考,并将索引用作半开区间——如果是正步幅,则右开,如果是负步幅,那么左开。

这样,我可以将[-4:-6:-1]看作是区间术语中的(-6,-4])。

 +---+---+---+---+---+---+
 | P | y | t | h | o | n |
 +---+---+---+---+---+---+
   0   1   2   3   4   5  
  -6  -5  -4  -3  -2  -1

 +---+---+---+---+---+---+---+---+---+---+---+---+
 | P | y | t | h | o | n | P | y | t | h | o | n |
 +---+---+---+---+---+---+---+---+---+---+---+---+
  -6  -5  -4  -3  -2  -1   0   1   2   3   4   5  

在找到这张很棒的桌子http://wiki.python.org/moin/MovingToPythonFromOtherLanguages

Python indexes and slices for a six-element list.
Indexes enumerate the elements, slices enumerate the spaces between the elements.

Index from rear:    -6  -5  -4  -3  -2  -1      a=[0,1,2,3,4,5]    a[1:]==[1,2,3,4,5]
Index from front:    0   1   2   3   4   5      len(a)==6          a[:5]==[0,1,2,3,4]
                   +---+---+---+---+---+---+    a[0]==0            a[:-2]==[0,1,2,3]
                   | a | b | c | d | e | f |    a[5]==5            a[1:2]==[1]
                   +---+---+---+---+---+---+    a[-1]==5           a[1:-1]==[1,2,3,4]
Slice from front:  :   1   2   3   4   5   :    a[-2]==4
Slice from rear:   :  -5  -4  -3  -2  -1   :
                                                b=a[:]
                                                b==[0,1,2,3,4,5] (shallow copy of a)

枚举序列x语法允许的可能性:

>>> x[:]                # [x[0],   x[1],          ..., x[-1]    ]
>>> x[low:]             # [x[low], x[low+1],      ..., x[-1]    ]
>>> x[:high]            # [x[0],   x[1],          ..., x[high-1]]
>>> x[low:high]         # [x[low], x[low+1],      ..., x[high-1]]
>>> x[::stride]         # [x[0],   x[stride],     ..., x[-1]    ]
>>> x[low::stride]      # [x[low], x[low+stride], ..., x[-1]    ]
>>> x[:high:stride]     # [x[0],   x[stride],     ..., x[high-1]]
>>> x[low:high:stride]  # [x[low], x[low+stride], ..., x[high-1]]

当然,如果(高低)%步幅!=0,则终点将略低于高1。

如果步幅为负,则由于我们正在倒计时,顺序会有点改变:

>>> x[::-stride]        # [x[-1],   x[-1-stride],   ..., x[0]    ]
>>> x[high::-stride]    # [x[high], x[high-stride], ..., x[0]    ]
>>> x[:low:-stride]     # [x[-1],   x[-1-stride],   ..., x[low+1]]
>>> x[high:low:-stride] # [x[high], x[high-stride], ..., x[low+1]]

扩展切片(带逗号和省略号)通常仅用于特殊数据结构(如NumPy);基本序列不支持它们。

>>> class slicee:
...     def __getitem__(self, item):
...         return repr(item)
...
>>> slicee()[0, 1:2, ::5, ...]
'(0, slice(1, 2, None), slice(None, None, 5), Ellipsis)'

已经有很多答案了,但我想添加一个性能比较

~$ python3.8 -m timeit -s 'fun = "this is fun;slicer = slice(0, 3)"' "fun_slice = fun[slicer]" 
10000000 loops, best of 5: 29.8 nsec per loop
~$ python3.8 -m timeit -s 'fun = "this is fun"' "fun_slice = fun[0:3]" 
10000000 loops, best of 5: 37.9 nsec per loop
~$ python3.8 -m timeit -s 'fun = "this is fun"' "fun_slice = fun[slice(0, 3)]" 
5000000 loops, best of 5: 68.7 nsec per loop
~$ python3.8 -m timeit -s 'fun = "this is fun"' "slicer = slice(0, 3)" 
5000000 loops, best of 5: 42.8 nsec per loop

因此,如果您重复使用同一个切片,使用切片对象将有益并提高可读性。然而,如果您只进行了几次切片,则应首选[:]表示法。

上面的答案不讨论切片分配。为了理解切片分配,可以在ASCII艺术中添加另一个概念:

                +---+---+---+---+---+---+
                | P | y | t | h | o | n |
                +---+---+---+---+---+---+
Slice position: 0   1   2   3   4   5   6
Index position:   0   1   2   3   4   5

>>> p = ['P','y','t','h','o','n']
# Why the two sets of numbers:
# indexing gives items, not lists
>>> p[0]
 'P'
>>> p[5]
 'n'

# Slicing gives lists
>>> p[0:1]
 ['P']
>>> p[0:2]
 ['P','y']

一种启发式方法是,对于从零到n的切片,思考:“零是开始,从开始开始,在列表中取n个项目”。

>>> p[5] # the last of six items, indexed from zero
 'n'
>>> p[0:5] # does NOT include the last item!
 ['P','y','t','h','o']
>>> p[0:6] # not p[0:5]!!!
 ['P','y','t','h','o','n']

另一种启发式方法是,“对于任何一个切片,用零替换开头,应用前面的启发式方法获得列表的结尾,然后将第一个数字向后计数,以从开头删除项目”

>>> p[0:4] # Start at the beginning and count out 4 items
 ['P','y','t','h']
>>> p[1:4] # Take one item off the front
 ['y','t','h']
>>> p[2:4] # Take two items off the front
 ['t','h']
# etc.

切片分配的第一个规则是,由于切片返回一个列表,所以切片分配需要一个列表(或其他可迭代的):

>>> p[2:3]
 ['t']
>>> p[2:3] = ['T']
>>> p
 ['P','y','T','h','o','n']
>>> p[2:3] = 't'
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
TypeError: can only assign an iterable

切片分配的第二个规则(您也可以在上面看到)是,无论切片索引返回列表的哪个部分,都是由切片分配更改的相同部分:

>>> p[2:4]
 ['T','h']
>>> p[2:4] = ['t','r']
>>> p
 ['P','y','t','r','o','n']

切片分配的第三条规则是,分配的列表(可迭代)不必具有相同的长度;索引切片被简单地切片,并被分配的任何内容整体替换:

>>> p = ['P','y','t','h','o','n'] # Start over
>>> p[2:4] = ['s','p','a','m']
>>> p
 ['P','y','s','p','a','m','o','n']

最难习惯的部分是分配给空切片。使用启发式1和2,很容易让你的头脑围绕空切片进行索引:

>>> p = ['P','y','t','h','o','n']
>>> p[0:4]
 ['P','y','t','h']
>>> p[1:4]
 ['y','t','h']
>>> p[2:4]
 ['t','h']
>>> p[3:4]
 ['h']
>>> p[4:4]
 []

然后,一旦您看到了这一点,将切片分配给空切片也是有意义的:

>>> p = ['P','y','t','h','o','n']
>>> p[2:4] = ['x','y'] # Assigned list is same length as slice
>>> p
 ['P','y','x','y','o','n'] # Result is same length
>>> p = ['P','y','t','h','o','n']
>>> p[3:4] = ['x','y'] # Assigned list is longer than slice
>>> p
 ['P','y','t','x','y','o','n'] # The result is longer
>>> p = ['P','y','t','h','o','n']
>>> p[4:4] = ['x','y']
>>> p
 ['P','y','t','h','x','y','o','n'] # The result is longer still

请注意,因为我们没有更改切片的第二个编号(4),所以插入的项目总是紧靠“o”堆叠,即使我们分配给空切片也是如此。因此,空切片分配的位置是非空切片分配位置的逻辑扩展。

稍微后退一点,当你继续进行我们的切片开始计数过程时会发生什么?

>>> p = ['P','y','t','h','o','n']
>>> p[0:4]
 ['P','y','t','h']
>>> p[1:4]
 ['y','t','h']
>>> p[2:4]
 ['t','h']
>>> p[3:4]
 ['h']
>>> p[4:4]
 []
>>> p[5:4]
 []
>>> p[6:4]
 []

通过切片,一旦你完成,你就完成了;它不会开始向后倾斜。在Python中,除非使用负数明确要求,否则不会获得负的步幅。

>>> p[5:3:-1]
 ['n','o']

“一旦你完成了,你就完成了”规则会产生一些奇怪的后果:

>>> p[4:4]
 []
>>> p[5:4]
 []
>>> p[6:4]
 []
>>> p[6]
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
IndexError: list index out of range

事实上,与索引相比,Python切片具有奇怪的防错误性:

>>> p[100:200]
 []
>>> p[int(2e99):int(1e99)]
 []

这有时会派上用场,但也会导致一些奇怪的行为:

>>> p
 ['P', 'y', 't', 'h', 'o', 'n']
>>> p[int(2e99):int(1e99)] = ['p','o','w','e','r']
>>> p
 ['P', 'y', 't', 'h', 'o', 'n', 'p', 'o', 'w', 'e', 'r']

根据您的应用程序,这可能。。。或者可能不。。。成为你在那里所希望的!


以下是我的原始答案。它对很多人都很有用,所以我不想删除它。

>>> r=[1,2,3,4]
>>> r[1:1]
[]
>>> r[1:1]=[9,8]
>>> r
[1, 9, 8, 2, 3, 4]
>>> r[1:1]=['blah']
>>> r
[1, 'blah', 9, 8, 2, 3, 4]

这也可以澄清切片和索引之间的区别。