Understanding Python Closure Late Binding and How to Fix It

The post discusses a common Python interview question that reveals the pitfalls of late binding in closures, where lambdas capture the loop variable by reference, leading to unexpected results.

Problematic code:

def testFun():
    temp = [lambda x : i*x for i in range(4)]
    return temp
for everyLambda in testFun():
    print(everyLambda(2))

Running this prints 6 four times because the loop finishes with i = 3 , and each lambda uses that final value when called.

Solution 1 – bind the current value using a default argument:

def testFun():
    temp = [lambda x, i=i: i * x for i in range(4)]
    return temp
for everyLambda in testFun():
    print(everyLambda(2))

Solution 2 – use functools.partial to fix the argument:

from functools import partial
from operator import mul

def testFun():
    return [partial(mul, i) for i in range(4)]
for everyLambda in testFun():
    print(everyLambda(2))

Solution 3 – employ a generator expression with the same default‑argument trick:

def testFun():
    return (lambda x, i=i: i * x for i in range(4))
for everyLambda in testFun():
    print(everyLambda(2))

Solution 4 – use a lazy‑evaluated generator with yield :

def testFun():
    for i in range(4):
        yield lambda x: i * x
for everyLambda in testFun():
    print(everyLambda(2))

All four approaches produce the expected output 0 2 4 6 (or printed line by line), demonstrating how to avoid the late‑binding trap in Python closures.