Performance Basics

Before optimizing anything, measure — Python's built-in timeit module times a piece of code precisely.

import timeit

def using_loop():
    result = []
    for n in range(1000):
        result.append(n * 2)
    return result

def using_comprehension():
    return [n * 2 for n in range(1000)]

print(timeit.timeit(using_loop, number=1000))
print(timeit.timeit(using_comprehension, number=1000))

A list comprehension is typically faster than an equivalent explicit loop with .append(), since it's optimized internally by Python. The general rule: optimize the specific part measured to be slow, not whatever feels slow.