# Flatten list of lists Python

“Flatten a list of lists” in Python means the process of converting a nested list structure into a single, one-dimensional list. In other words, it involves taking a list that contains other lists as elements and creating a new list that contains all the individual elements from the nested lists in a linear sequence.

For example, given the following list of lists:

``````original_list = [[1, 2, 3], [4, 5], [6, 7, 8, 9]]
``````

The goal of flattening this list is to obtain a new list like this:

``````flattened_list = [1, 2, 3, 4, 5, 6, 7, 8, 9]
``````

This process can be useful in various situations where you want to work with a single flat list of elements rather than a nested structure. Python provides several methods to achieve this.

## Flatten list of lists Python example

To flatten a list of lists in Python, you can use various methods. Here are a few common approaches:

1. Using a nested list comprehension:

``````original_list = [[1, 2, 3], [4, 5], [6, 7, 8, 9]]
flattened_list = [item for sublist in original_list for item in sublist]
print(flattened_list)
``````

2. Using the `itertools.chain.from_iterable()` method:

``````from itertools import chain

original_list = [[1, 2, 3], [4, 5], [6, 7, 8, 9]]
flattened_list = list(chain.from_iterable(original_list))
print(flattened_list)
``````

3. Using the `sum()` function with a start value of an empty list:

``````original_list = [[1, 2, 3], [4, 5], [6, 7, 8, 9]]
flattened_list = sum(original_list, [])
print(flattened_list)
``````

Output:

Choose the method that you find most readable and suitable for your use case. The first two methods use a list comprehension or the `chain.from_iterable()` method, which are generally considered more Pythonic and efficient. The third method using `sum()` may not be as efficient for larger lists due to the overhead of concatenating lists.

Note: IDE: PyCharm 2021.3.3 (Community Edition)

Windows 10

Python 3.10.1

All Python Examples are in Python 3, so Maybe its different from python 2 or upgraded versions.