How to Address Closure Scoping Issues in Python Lambda Functions?

Understanding Python Lambda Closure Scoping

When using closures in Python, it's crucial to comprehend their scoping behavior. In this context, closures refer not only to lambda functions but also to any function that accesses variables from its enclosing scope.

In the given example:

<code class="python">names = ['a', 'b', 'c']

funcs1 = [gen_clousure(n) for n in names]
funcs2 = [lambda x: test_fun(n, x) for n in names]</code>

The reason funcs2 returns the last name for all cases is due to closure scoping. When defining lambda x: test_fun(n, x), the value of n is not evaluated and stored within the function during definition but only at the time of invocation. Therefore, by the time the function is called, n contains the final value from the loop, resulting in the last name being repeatedly printed.

To address this issue, you must ensure that the closure captures the intended value by providing it as an argument to the function. In this case, you would need to pass n as an argument to the lambda function, such as:

<code class="python">funcs2 = [lambda x, n=n: test_fun(n, x) for n in names]</code>

Alternatively, you can encapsulate the lambda function within another function:

<code class="python">def makeFunc(n):
    return lambda x: x+n
stuff = [makeFunc(n) for n in [1, 2, 3]]</code>

In this case, the inner lambda references the local variable n within the enclosing function makeFunc, resulting in each function capturing the correct value of n.

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