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Why Does Modifying a Python List During Iteration Lead to Unexpected Results?

Barbara Streisand
Barbara StreisandOriginal
2024-12-27 18:36:111047browse

Why Does Modifying a Python List During Iteration Lead to Unexpected Results?

Iterative List Alteration in Python: Understanding the Consequences

In Python, modifying a list while iterating over it can lead to unexpected results. Consider the following code:

numbers = list(range(1, 50))

for i in numbers:
    if i < 20:
        numbers.remove(i)

print(numbers)

Instead of removing numbers below 20, as intended, this code prints a list where all numbers below 20 are missing, along with 20 itself.

The Problem: Iterator Position Shift

The issue stems from the fact that removing an item from a list shifts the position of subsequent items. As the loop progresses, the items being checked are no longer the expected ones, as the removed elements create "holes" in the list.

For instance, during the initial iteration, 1 is removed, but the next iteration does not check 2; instead, it checks 3 because the list has been shortened. This behavior continues, resulting in the incorrect output.

Proper List Alteration Techniques

To avoid this problem, use alternative methods for altering lists during iteration, such as:

  • List Comprehension:
numbers = [n for n in numbers if n >= 20]
  • In-place Alteration:
numbers[:] = (n for n in numbers if n >= 20)
  • Enumeration:
for i, n in enumerate(numbers):
    if n < 20:
        numbers[i] = None
numbers = [n for n in numbers if n is not None]

These techniques do not modify the list's length while iterating, ensuring correct item processing and the desired output.

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