What do Python closures get wrong when they capture loop variables in lambdas?

Why Python Closures Capture the Loop Variable, Not the Per-Iteration Value

A lambda closes over the variable binding, not a frozen snapshot of the value at the moment the lambda is created. In a loop, that means each function shares the same loop variable name, and when the loop finishes, they all read whatever value it holds then. The behaviour is a scoping and binding issue, not a lambda-specific bug.

This is why the result often surprises people who expect each function to “remember” its own iteration. The closure is evaluated later, when the function is called, so it follows the current state of the surrounding scope. If the loop variable changes after the closure is created, the later call sees the changed value.

Why the Last Loop Value Shows Up in Every Lambda

Inside a loop, each lambda usually refers to the same variable object from the enclosing scope. The loop updates that object on every iteration, but it does not create a new binding for each lambda. When the functions are finally invoked, they all look up the variable at call time, which is why the final iteration value can appear everywhere.

This late binding model is useful in many closure patterns, but it becomes a trap when you intend per-iteration capture. The underlying issue is that the loop variable survives beyond the body of the loop, so the closure reads a shared reference instead of an isolated value. That distinction matters whenever the callback is stored and executed later.

How to Preserve Each Iteration’s Value

The standard fix is to bind the current value as a default argument, such as lambda x=i: x, so the lambda stores its own parameter default at creation time. Another common option is to move the lambda creation into a helper function that receives the loop value as an argument. Both approaches force an early binding point and avoid shared late lookup.

Choose the approach that makes the code easiest to read in context. Default arguments are concise and work well for small callback factories, while a helper function can be clearer when the captured state is more complex than a single scalar. The key requirement is that the closure must receive a distinct value per iteration, not a shared outer variable.

Practitioner Guidance

What to verify: When a loop creates callbacks, inspect whether the callback is meant to preserve state from creation time or read the latest state at execution time. If the callback is delayed, assume late binding will matter unless you explicitly isolate the value.

Common mistake: Developers often test only the first callback or print the functions immediately after creation, which hides the bug. The failure usually appears later, when the queued or stored functions all resolve to the same final value.

Practitioner takeaway: Treat loop-captured lambdas as shared-variable readers by default, and make the binding explicit whenever each callback must retain its own iteration-specific value.

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