Understanding when to use list comprehensions vs generator expressions

List Comprehensions

List comprehensions create new lists by transforming or filtering items from another iterable (such as a dictionary, tuple, or another list). They can be read as "do this operation for each item in this collection (and sometimes, only if this condition is true)".

The syntax looks like this:

[operation(item) for item in iterable if condition(item)]

List comprehensions are useful if you need to reuse and access these lists in your code.

List Comprehension with Simple Condition

Let's say I want a list representing books I haven't read yet in my personal library. I can use a list comprehension with a simple condition:

unread_books = [book for book in books if book.status == "to_read"]

Here, the list comprehension does not perform any operation on the individual book; it is only checking if the book's status is "to_read".

List Comprehension with Function Call

What if I want to ensure that my book titles are consistently capitalized? I can use a list comprehension that calls a function on each book title:

def fix_title(title):
    return title.strip().title()

book_titles = ['  war and peace', 'the HOBBIT ', '  dune']

cleaned_titles = [fix_title(t) for t in book_titles]
print(cleaned_titles)
# Output: ['War And Peace', 'The Hobbit', 'Dune']

List Comprehension with a more complex condition

Let's say I want all the titles of books that are longer than 300 pages AND I've already read:

finished_long_books = [
    book.title for book in books 
    if book.status == "finished" and book.page_count > 300
]

Generator Expressions

Generator expressions have a similar syntax as list comprehensions, but instead of creating a list, they produces items or values one at a time instead of storing a full list. This is useful if you're working with very large datasets and need to iterate over them only once.

Using generator expressions to sum values

Let's say I want to get a sum of all the pages I've read in my library:

total_pages_read = sum(book.page_count for book in books if book.status == "finished")

Note that the generator expression is passed to sum(), which adds each book's page count together if the book's status is "finished".

Using generator expressions to print values

Let's say I just want to print the names of the authors of the books I'm currently reading and don't need to store these as a separate list:

print(*(f"{book.author}" for book in books), sep="\n")

The generator expression is passed to print() as the first argument, which uses the unpacking operator * to print each author's name. The second argument is the separator that prints each name on a newline. This removes the need to use a for loop, iterating and printing over the authors in a single line.

Summary

List comprehensions create lists that can be reused and access in your code.

Generator expressions create generator objects that produce one value at a time, using less memory than a list.