What is :: (double colon) in Python when subscripting sequences?

PythonSyntaxSlice

Python Problem Overview


I know that I can use something like string[3:4] to get a substring in Python, but what does the 3 mean in somesequence[::3]?

Python Solutions


Solution 1 - Python

it means 'nothing for the first argument, nothing for the second, and jump by three'. It gets every third item of the sequence sliced. Extended slices is what you want. New in Python 2.3

Solution 2 - Python

Python sequence slice addresses can be written as a[start:end:step] and any of start, stop or end can be dropped. a[::3] is every third element of the sequence.

Solution 3 - Python

seq[::n] is a sequence of each n-th item in the entire sequence.

Example:

>>> range(10)[::2]
[0, 2, 4, 6, 8]

The syntax is:

seq[start:end:step]

So you can do (in Python 2):

>>> range(100)[5:18:2]
[5, 7, 9, 11, 13, 15, 17]

Solution 4 - Python

Explanation

s[i:j:k] is, according to the documentation, "slice of s from i to j with step k". When i and j are absent, the whole sequence is assumed and thus s[::k] means "every k-th item".

Examples

First, let's initialize a list:

>>> s = range(20)
>>> s
[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19]

Let's take every 3rd item from s:

>>> s[::3]
[0, 3, 6, 9, 12, 15, 18]

Let's take every 3rd item from s[2:]:

>>> s[2:]
[2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19]
>>> s[2::3]
[2, 5, 8, 11, 14, 17]

Let's take every 3rd item from s[5:12]:

>>> s[5:12]
[5, 6, 7, 8, 9, 10, 11]
>>> s[5:12:3]
[5, 8, 11]

Let's take every 3rd item from s[:10]:

>>> s[:10]
[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
>>> s[:10:3]
[0, 3, 6, 9]

Solution 5 - Python

TL;DR

This visual example will show you how to a neatly select elements in a NumPy Matrix (2 dimensional array) in a pretty entertaining way (I promise). Step 2 below illustrate the usage of that "double colons" :: in question.

(Caution: this is a NumPy array specific example with the aim of illustrating the a use case of "double colons" :: for jumping of elements in multiple axes. This example does not cover native Python data structures like List).

One concrete example to rule them all...

Say we have a NumPy matrix that looks like this:

In [1]: import numpy as np

In [2]: X = np.arange(100).reshape(10,10)

In [3]: X
Out[3]:
array([[ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9],
       [10, 11, 12, 13, 14, 15, 16, 17, 18, 19],
       [20, 21, 22, 23, 24, 25, 26, 27, 28, 29],
       [30, 31, 32, 33, 34, 35, 36, 37, 38, 39],
       [40, 41, 42, 43, 44, 45, 46, 47, 48, 49],
       [50, 51, 52, 53, 54, 55, 56, 57, 58, 59],
       [60, 61, 62, 63, 64, 65, 66, 67, 68, 69],
       [70, 71, 72, 73, 74, 75, 76, 77, 78, 79],
       [80, 81, 82, 83, 84, 85, 86, 87, 88, 89],
       [90, 91, 92, 93, 94, 95, 96, 97, 98, 99]])

Say for some reason, your boss wants you to select the following elements:

enter image description here

"But How???"... Read on! (We can do this in a 2-step approach)

Step 1 - Obtain subset

Specify the "start index" and "end index" in both row-wise and column-wise directions.

enter image description here

In code:

In [5]: X2 = X[2:9,3:8]

In [6]: X2
Out[6]:
array([[23, 24, 25, 26, 27],
       [33, 34, 35, 36, 37],
       [43, 44, 45, 46, 47],
       [53, 54, 55, 56, 57],
       [63, 64, 65, 66, 67],
       [73, 74, 75, 76, 77],
       [83, 84, 85, 86, 87]])

Notice now we've just obtained our subset, with the use of simple start and end indexing technique. Next up, how to do that "jumping"... (read on!)

Step 2 - Select elements (with the "jump step" argument)

We can now specify the "jump steps" in both row-wise and column-wise directions (to select elements in a "jumping" way) like this:

enter image description here

In code (note the double colons):

In [7]: X3 = X2[::3, ::2]

In [8]: X3
Out[8]:
array([[23, 25, 27],
       [53, 55, 57],
       [83, 85, 87]])

We have just selected all the elements as required! :)

 Consolidate Step 1 (start and end) and Step 2 ("jumping")

Now we know the concept, we can easily combine step 1 and step 2 into one consolidated step - for compactness:

In [9]: X4 = X[2:9,3:8][::3,::2]

    In [10]: X4
    Out[10]:
    array([[23, 25, 27],
           [53, 55, 57],
           [83, 85, 87]])

Done!

Solution 6 - Python

When slicing in Python the third parameter is the step. As others mentioned, see Extended Slices for a nice overview.

With this knowledge, [::3] just means that you have not specified any start or end indices for your slice. Since you have specified a step, 3, this will take every third entry of something starting at the first index. For example:

>>> '123123123'[::3]
'111'

Solution 7 - Python

You can also use this notation in your own custom classes to make it do whatever you want

class C(object):
    def __getitem__(self, k):
        return k

# Single argument is passed directly.
assert C()[0] == 0

# Multiple indices generate a tuple.
assert C()[0, 1] == (0, 1)

# Slice notation generates a slice object.
assert C()[1:2:3] == slice(1, 2, 3)

# If you omit any part of the slice notation, it becomes None.
assert C()[:] == slice(None, None, None)
assert C()[::] == slice(None, None, None)
assert C()[1::] == slice(1, None, None)
assert C()[:2:] == slice(None, 2, None)
assert C()[::3] == slice(None, None, 3)

# Tuple with a slice object:
assert C()[:, 1] == (slice(None, None, None), 1)

# Ellipsis class object.
assert C()[...] == Ellipsis

We can then open up slice objects as:

s = slice(1, 2, 3)
assert s.start == 1
assert s.stop == 2
assert s.step == 3

This is notably used in Numpy to slice multi-dimensional arrays in any direction.

Of course, any sane API should use ::3 with the usual "every 3" semantic.

The related Ellipsis is covered further at: https://stackoverflow.com/questions/772124/what-does-the-ellipsis-object-do/33087462#33087462

Solution 8 - Python

The third parameter is the step. So [::3] would return every 3rd element of the list/string.

Solution 9 - Python

remember that the foundations is what a[start:end:step] means. From there you can get a[1::2] get every odd index, a[::2] get every even, a[2::2] get every even starting at 2, a[2:4:2] get every even starting at 2 and ending at 4. Inspired by https://stackoverflow.com/a/3453102/1601580

Solution 10 - Python

Python uses the :: to separate the End, the Start, and the Step value.

Solution 11 - Python

Did I miss or nobody mentioned reversing with [::-1] here?

# Operating System List
systems = ['Windows', 'macOS', 'Linux']
print('Original List:', systems)

# Reversing a list	
#Syntax: reversed_list = systems[start:stop:step] 
reversed_list = systems[::-1]

# updated list
print('Updated List:', reversed_list)

source: https://www.programiz.com/python-programming/methods/list/reverse

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