A part of learning python is understanding the use of list comprehensions and how or when to use them, this post aims to tackle the basics of applying list comprehensions and explaining what it is.
What are List Comprehensions?
List comprehensions provide a concise way to create lists and transform data. It's essentially a syntactic construct which lets you create a list by performing an operation on each item of a sequence (like a list or a range), filtering the items based on a condition. Think of it as a concise way to map and filter elements from one list (or iterable) to another list.
variable = [expression for item in iterable if condition]
- expression: The current item in the iteration, but it could be modified or operated upon.
- item: The variable that takes the value of each item in the iterable.
- iterable: A sequence of values to iterate over. (e.g a list)
- condition: An optional filter to include only items that evaluate as True.
1. Transforming items (mapping)
Both methods come to the same result but do it different ways, for example using a for loop requires prior declaration of the list variable (named
numbers) and requires using the append method. In this example we loop through a range of 10 integers (0 to 9), multiply the value by two and append it to the list.
# For loop numbers =  for i in range(10): numbers.append(i * 2) # List comprehension numbers = [i * 2 for i in range(10)]
[0, 2, 4, 6, 8, 10, 12, 14, 16, 18].
2. With a Condition (filtering)
To filter only values greater than four we can use a simple if condition to evaluate the variable i (the item in the list), if the condition result is True then the item is included in the list.
values = [i for i in range(10) if i > 4]
[5, 6, 7, 8, 9]
3. Nested List Comprehensions
Flattening a nested list (e.g a 2D list) can also be done:
nested_list = [[1, 2, 3], [4, 5, 6], [7, 8, 9]] flattened = [num for sublist in nested_list for num in sublist]
[1, 2, 3, 4, 5, 6, 7, 8, 9]
Why Use List Comprehensions?
- Conciseness: Often, you can replace multiple lines of code with a single, readable line.
- Performance: In many cases, using a list comprehension is faster than the equivalent for-loop (sometimes up to 50%!).
When to Avoid?
- Readability: If the comprehension becomes complex, it might be better to use a traditional loop for the sake of clarity unless the performance difference is required. If performance difference is to impactful then comments should be added.
- Output: If you're not aiming to build a list, comprehension is most likely not the right tool and may cause your code to be more difficult to understand which can impact bug fixing and general code maintenance.
While list comprehensions offer a compact way to write loops, it's essential to ensure the resulting code remains readable. If a comprehension gets too complex, it might be more maintainable to use a traditional for-loop. Code clarity should always be a priority, especially when in a setting where other people are going to be working with your code. Even if you are working on a home project or learning, you should still focus on making code readable as it's easier to do once it becomes a habit and not a chore.
By understanding the components of list comprehensions and practicing with different scenarios, you'll soon find them to be a valuable tool in your Python coding toolkit.