List comprehensions are a powerful feature in Python that allows you to create new lists from existing ones in a concise and readable way. They are a shorthand way to create a new list by applying a transformation function to each item in the original list.
Before We Begin: A Common Loop-and-Append Pattern
Let's consider a common use case where we want to create a new list of squares of numbers from 0 to 10. We might write the following code:
result = []
for i in range(11):
result.append(i**2)
This code works, but it's not very efficient, especially for large lists, as it involves creating an empty list and repeatedly appending to it.
Using List Comprehensions
We can rewrite the above code using a list comprehension as follows:
result = [i**2 for i in range(11)]
This code produces the same output as the original, but with a significant reduction in code size and a performance improvement.
Quick Patterns for List Comprehensions
Here are some common patterns to keep in mind when writing list comprehensions:
- element transformation:
[expression for element in iterable] - conditional filtering:
[expression for element in iterable if condition] - multiple iterables:
[expression for element in iterable1 for element2 in iterable2]
Example Use Cases
- Creating a list of squares of numbers:
[i**2 for i in range(11)] - Filtering a list of numbers to keep only the even ones:
[x for x in [1, 2, 3, 4, 5] if x % 2 == 0] - Creating a list of pairs of numbers:
[(x, y) for x in [1, 2] for y in [3, 4]]
Remember, list comprehensions are not only more concise, but they are also more readable and faster than traditional loop-and-append code. Use them to streamline your Python code and improve performance!