Closures in Python Explained by Tracing Through the Code

Short summary

This tutorial explains Python closures by tracing through code examples step by step, showing how captured variables persist in cell objects after their enclosing scope is destroyed. It covers common interview pitfalls like the late-binding loop trap and demonstrates patterns for shared state and curried functions. The article ends with a pitch for PyCodeIt, an AI-powered Python dry-run practice platform.

• •Closures form when an inner function captures variables from an enclosing scope, stored in cell objects that persist after the outer scope is destroyed
• •The late-binding trap in loops causes all closures to reference the final loop value; using default arguments (i=i) captures the current value at definition time
• •Shared closure state enables class-free stateful objects, and nested closures support curried function patterns

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