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Why Does My Python List Comprehension Change My Variable\'s Value?

Susan Sarandon
Release: 2024-11-29 12:08:11
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Why Does My Python List Comprehension Change My Variable's Value?

Unexpected Behavior: List Comprehensions Altering Variable Scope

Python list comprehensions are powerful tools for data manipulation, but they come with a hidden quirk that can lead to unexpected behavior.

The Issue

In Python 2 (and earlier), list comprehensions can "rebind" the loop control variable to the last value of the loop, even after the scope of the comprehension has ended. This can result in surprising behavior:

x = "original value"
squares = [x**2 for x in range(5)]
print(x)  # Prints 4 in Python 2!
Copy after login

In this example, the loop control variable x is reassigned to the last value of the loop (4) within the list comprehension. This means that when print(x) is called outside the comprehension, it prints 4 instead of "original value."

Explanation

The behavior described above is a result of the way list comprehensions were initially implemented in Python 2. To make list comprehensions as efficient as possible, the loop control variable was leaked into the surrounding scope.

Python 3 Correction

In Python 3, this behavior was changed. List comprehensions no longer rebind the loop control variable outside the comprehension. This was done to improve the consistency between list comprehensions and generator expressions, which never rebind the loop control variable.

Guido van Rossum's Explanation

Guido van Rossum, the creator of Python, explained the reasoning behind this change in Python 3:

"We decided to fix the "dirty little secret" of list comprehensions by using the same implementation strategy as for generator expressions. Thus, in Python 3, the above example... will print 'before', proving that the 'x' in the list comprehension temporarily shadows but does not override the 'x' in the surrounding scope."

Conclusion

While the behavior of list comprehensions may seem counterintuitive at first, it is important to understand how they work in both Python 2 and Python 3. This knowledge will help you avoid potential bugs and write more robust code.

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