6 ways to flatten Python lists

Flattening lists in Python is a handy skill, especially when dealing with nested lists. Luckily, Python gives us plenty of tools to get the job done, from list comprehension to specialized libraries.

Here, we’ll explore six easy and effective ways to flatten lists, each with its own benefits. Let’s dive in and find the best method for your project.

1. List Comprehension

List comprehension is one of the quickest ways to flatten a list in Python. It’s simple, readable, and doesn’t require any extra libraries.

x = [[1, 2, 3], [4, 5]]
flat_list = [item for sublist in x for item in sublist]

Here, we’re looping through each sublist, then each item in that sublist, gathering all items into a single, flat list.

2. itertools.chain.from_iterable()

If you need a more efficient approach, especially with larger lists, itertools.chain.from_iterable() is a solid choice. It’s known for handling large data efficiently:

from itertools import chain
x = [[1, 2, 3], [4, 5]]
flat_list = list(chain.from_iterable(x))

Using chain.from_iterable() simplifies flattening by treating each sublist as a sequence to merge together.

3. The sum() Trick to Flatten Lists

Here’s a lesser-known trick for flattening lists: the built-in sum() function. While unconventional, it’s quick for smaller lists:

x = [[1, 2, 3], [4, 5]]
flat_list = sum(x, [])

The sum() function takes two arguments: the iterable (our list) and a starting value, which here is []. sum() then “adds” each sublist to the starting list, resulting in a flattened list.

However, it’s worth noting that sum() can be slower than other methods for larger lists, and it only works if every item is a list.

4. numpy.flatten() for Flattening Lists

If you’re working with arrays or multi-dimensional data, numpy offers a convenient way to flatten lists, especially if they’re in an array format. This method is ideal for numerical data.

import numpy as np
x = np.array([[1, 2, 3], [4, 5]])
flat_list = x.flatten().tolist()

Using numpy.flatten() will give you a one-dimensional array, which we convert back to a standard Python list with .flatten().

5. functools.reduce()

If you prefer functional programming, functools.reduce() offers another way to flatten lists in Python. Although it’s less common, it’s useful if you’re comfortable with lambda functions.

from functools import reduce
x = [[1, 2, 3], [4, 5]]
flat_list = reduce(lambda a, b: a + b, x)

With reduce(), each sublist is added to the next, creating a single flattened list in the end.

6. Using a Nested Loop to Flatten Lists

Finally, a classic nested loop is always a reliable choice. This approach requires a bit more code, but it’s flexible and doesn’t need any imports.

x = [[1, 2, 3], [4, 5]]
flat_list = []
for sublist in x:
    for item in sublist:
        flat_list.append(item)

The nested loop gives you more control, making it ideal if you need custom handling for each element in the sublists.

Choosing the Best Way to Flatten a List in Python

Each method has its strengths. For quick, readable solutions, list comprehension or itertools.chain works well.

If you’re dealing with larger or multi-dimensional data, consider using numpy.flatten().

Meanwhile, sum() offers a fun alternative but is best suited for smaller lists due to its performance limitations.

With these options, you’re ready to flatten lists efficiently in Python. Whether you’re going for simplicity or speed, there’s a solution here that’ll fit your needs.

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