Python List Comprehension vs For [closed]

Question

Why does list comprehension have better performance than a for loop, in Python?

list comprehension:

new_items = [a for a in items if a > 10]

for loop:

new_items = []
for a in items:
    if a > 10: new_items.append(a)

Are there other examples (not loops), where one Python structure has worse performance than another Python structure?

Answer 1

Essentially, list comprehension and for loops does pretty similar things, with list comprehension doing away some overheads and making it look pretty. To understand why this is faster, you should look in Efficiency of list comprehensions and to quote the relevant part for your problem:

List comprehensions perform better here because you don’t need to load the append attribute off of the list (loop program, bytecode 28) and call it as a function (loop program, bytecode 38). Instead, in a comprehension, a specialized LIST_APPEND bytecode is generated for a fast append onto the result list (comprehension program, bytecode 33).

In the loop_faster program, you avoid the overhead of the append attribute lookup by hoisting it out of the loop and placing the result in a fastlocal (bytecode 9-12), so it loops more quickly; however, the comprehension uses a specialized LIST_APPEND bytecode instead of incurring the overhead of a function call, so it still trumps.

The link also details some of the possible pitfalls associated with lc and I would recommend you to go through it once.