Here are a few title options, keeping in mind the question format and the article\'s focus: Option 1 (Direct and Concise): * Why are List Comprehensions Faster than Appending to Lists? Option 2 (Fo

Why is list comprehension significantly faster than appending to a list?

List comprehension is a concise syntax for performing a series of operations on a collection of items and creating a new list from the results. While it may appear to be merely a different way of writing a for loop, the performance difference is undeniable. List comprehensions often execute significantly faster than their traditional counterparts.

The key distinction lies in how list comprehensions and appending to lists handle function calls. In the case of appending, for each iteration of the loop, the append attribute of the list must be loaded and called as a function. This process adds overhead and slows down the execution.

Consider the following code snippet:

<code class="python">t = []
for i in range(10000):
    t.append(i)

# Using list comprehension
t = [i for i in range(10000)]</code>

As illustrated in the provided example, the list comprehension version executes 50% faster than the appending method. This difference becomes more apparent as the size of the list grows.

Furthermore, let's examine the bytecode disassembly of these functions:

<code class="python"># Appending to a list
dis.dis(appending_function)

# List comprehension
dis.dis(list_comprehension_function)</code>

By comparing the bytecode, we can observe that the function using list comprehension does not require the loading and calling of the append attribute, resulting in a reduction in overhead and improved performance.

Therefore, when creating a new list by applying operations to a collection of items, list comprehensions emerge as the superior choice due to their speed advantage and syntactic elegance.

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