Python slice() — A Simple Guide with Video

Python’s built-in slice() function returns a new slice object you can use to slice over sequences such as lists, strings, or tuples.

Read more about lists in our full tutorial about Python Slicing.

Example 1: Slice with Stop Argument

One of the best way to learn is by example! Here are some examples of how to use the slice() built-in function.

First, let’s create a list of 20 elements using the range() function:

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

The list consists of all elements from 0 to 19 (included). You can now access the first ten elements of this list by creating a new slice object with stop index 10, and pass the newly-created slice into the indexing scheme using the square bracket notation list[slice].

>>> s = slice(10)
>>> lst[s]
[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]

Example 2: Slice with Start and Stop Arguments

You can also give the start argument to start from any other position in the sequence to be sliced:

>>> lst =list(range(20))
>>> s = slice(5, 10)
>>> lst[s]
[5, 6, 7, 8, 9]

Example 3: Extended Slice with Start, Stop, and Step Arguments

The most advanced way is called extended slicing, where you define the start index, the stop index, and the step size:

>>> lst =list(range(20))
>>> s = slice(2, 10, 2)
>>> lst[s]
[2, 4, 6, 8]

Video Slicing

Syntax slice()

You can use the slice() method with up to three arguments:

Syntax: There are three ways of using the constructor:

# 1. Create new slice that goes from start index 0 (default) to stop using default step size 1. 
slice(stop) 

# 2. Create new slice that goes from start index to stop using default step size 1. 
slice(start, stop) 

 # 3. Create new slice that goes from start to stop using step as step size. 
slice(start, stop, step)

What’s the Purpose of slice() vs Python’s slicing notation?

Python also allows a more concise way of slicing sequences: the default slicing notation. Let’s quickly recap it:

Slicing is a concept to carve out a substring from a given string. Use slicing notation s[start:stop:step] to access every step-th element starting from index start (included) and ending in index stop (excluded). All three arguments are optional, so you can skip them to use the default values (start=0, stop=len(lst), step=1). For example, the expression s[2:4] from string 'hello' carves out the slice 'll' and the expression s[:3:2] carves out the slice 'hl'.

You can either create a slice object explicitly using slice() or you create it implicitly using the slice notation. Both variants are semantically identical:

>>> customers = ['Alice', 'Bob', 'Carl', 'Dave', 'Elena', 'Frank']
>>> customers[1:5:2]
['Bob', 'Dave']
>>> customers[slice(1, 5, 2)]
['Bob', 'Dave']

There’s only one difference: if you use slice() explicitly to create a slice object, you can reuse it for further slicing operations.

Performance Evaluation: Slicing vs slice()

This has some performance benefits, for example, when using the same slicing operation on different lists in a loop:

import time

lst = [list(range(10000)),
       list(range(20000)),
       list(range(30000))]


# Method 1: Slicing Notation
start = time.time()
for l in lst:
    print('Size of slice: ', len(l[5:-5:4]))
print(time.time() - start)

# Method 2: slice() Object
start = time.time()
s = slice(5, -5, 4)
for l in lst:
    print('Size of slice: ', len(l[s]))
print(time.time() - start)

Both methods have the same output:

Size of slice:  2498
Size of slice:  4998
Size of slice:  7498
0.03080606460571289
Size of slice:  2498
Size of slice:  4998
Size of slice:  7498
0.015621423721313477

However, the performance difference in this example is significant.

  • Method 1 takes 0.03 seconds to complete.
  • Method 2 takes 0.015 seconds to complete.

Using the function slice() to create a slice object once in advance results in a 50% runtime performance reduction compared to using standard slicing. The reason is that standard slicing will internally recreate the same slice object in each iteration which is inefficient.

Interactive Shell Exercise: Understanding slice()

Consider the following interactive code:

Exercise: Guess the output before running the code.


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Summary

Python’s built-in slice() function returns a new slice object you can use to slice over sequences such as lists, strings, or tuples.

  • slice(stop): create a new slice that goes from start index 0 (default) to stop using default step size 1.
  • slice(start, stop): create a new slice that goes from start index to stop using default step size 1.
  • slice(start, stop, step): create a new slice that goes from start to stop using step as step size.

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