Python uses an algorithm called Timsort for its built-in `sort`

method for lists and the `sorted`

function. Timsort is derived from merge sort and insertion sort. It has an average case time complexity of O(n log n), which is the best you can achieve for comparison-based sorting algorithms.

While Timsort is highly efficient for a broad range of input datasets, it’s worth mentioning that “fastest” can be relative. Depending on the specific nature of the data you’re working with and the constraints of your problem, other sorting algorithms might be more efficient in certain cases.

However, for most general purposes, Timsort is a great choice because it’s adaptive, stable, and has good average-case performance.

Below is a tutorial that explains how to use Python’s built-in sorting methods.

## Fastest Sorting Algorithm in Python

### Using Python’s Built-in Sorting Functions

#### sorted()

The `sorted()`

function can be used to sort any iterable and returns a new sorted list from the elements of the given iterable.

```
# Example: Sorting a list of numbers
numbers = [2, 4, 1, 5, 3]
sorted_numbers = sorted(numbers)
print(sorted_numbers) # Output: [1, 2, 3, 4, 5]
# Example: Sorting a list of strings
words = ["apple", "banana", "cherry"]
sorted_words = sorted(words)
print(sorted_words) # Output: ['apple', 'banana', 'cherry']
```

You can see the output like below:

#### .sort()

The `sort()`

method sorts the elements of a list in-place and returns `None`

. This means that it modifies the original list and doesn’t create a new list.

```
# Example: Sorting a list of numbers in-place
numbers = [2, 4, 1, 5, 3]
numbers.sort()
print(numbers) # Output: [1, 2, 3, 4, 5]
```

Check out the output like below:

### Custom Sorting

Both `sort()`

and `sorted()`

can take two optional arguments: `key`

and `reverse`

.

`key`

: This takes a function as an argument, which would be used for custom sorting. For instance, if you want to sort based on the length of strings.`reverse`

: This can be set to`True`

if you want the sorting to be done in descending order.

```
# Example: Sorting a list of strings based on length
words = ["apple", "banana", "cherry", "date"]
sorted_words = sorted(words, key=len)
print(sorted_words) # Output: ['date', 'apple', 'banana', 'cherry']
# Example: Sorting a list of numbers in descending order
numbers = [2, 4, 1, 5, 3]
sorted_numbers = sorted(numbers, reverse=True)
print(sorted_numbers) # Output: [5, 4, 3, 2, 1]
```

You can see the output like below:

## Conclusion

For most cases, using Python’s built-in sorting functions `sorted()`

or the `.sort()`

method should be sufficient and is among the fastest options available due to the highly optimized Timsort algorithm. It’s generally a good idea to start with these and consider other options only if you find that they do not meet your specific needs.

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I am Bijay Kumar, a Microsoft MVP in SharePoint. Apart from SharePoint, I started working on Python, Machine learning, and artificial intelligence for the last 5 years. During this time I got expertise in various Python libraries also like Tkinter, Pandas, NumPy, Turtle, Django, Matplotlib, Tensorflow, Scipy, Scikit-Learn, etc… for various clients in the United States, Canada, the United Kingdom, Australia, New Zealand, etc. Check out my profile.