Understanding the Weird Behaviour of a Python Generator Function During List Conversion

Explore the peculiar behavior of Python generator functions, especially when yielding mutable objects like lists. Learn how to properly capture states and avoid surprising outcomes!
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The Weird Behaviour of a Python Generator Function When Converting to a List

Python's generator functions are a great way to handle iterations efficiently. However, when it comes to mutable objects like lists, their behavior can be surprisingly counterintuitive. In this guide, we'll explore a scenario where a generator function yields changing states of a list during a bubble sort, leading to unexpected results when converted to a list. Let's dive in!

The Problem: Generator Function and List Conversion

Imagine you want to observe every state of a list while sorting it using the bubble sort algorithm. You've cleverly implemented a generator function that yields the list's state at each step. However, when you convert that generator to a list using various methods, you only see the last sorted state repeated multiple times. Why does this happen?

Here's an outline of the generator function used in this scenario:

[[See Video to Reveal this Text or Code Snippet]]

The Unexpected Output

When running the generator, you get the desired output showing all intermediate steps during the sorting process. However, if you try to collect these outputs in a list, you will only see repeated entries of the last sorted state. Here's an example of the problematic code:

[[See Video to Reveal this Text or Code Snippet]]

The output looks something like this:

[[See Video to Reveal this Text or Code Snippet]]

Understanding the Behavior: Mutability and References

The core of the issue lies in how Python handles mutable objects like lists. The generator function only yields references to the same list object (arr). As a result, when arr is modified during successive iterations of the generator, all previous references in the list also reflect these changes.

Why the Repeats?

Single Reference: The list you create contains multiple references to the same list object (arr). When each state of arr is printed during sorting, you see the snapshot of that state. But once arr is fully sorted, every reference in the new list refers to the same final state of arr.

No Copies Made: Unless you specifically create a copy of the state of arr, you won't retain separate states—just the final sorted state repeated.

The Solution: Yielding Copies of the List

The solution is to make sure that each state you yield is a unique copy of the list. You can achieve this by using the copy() method or list() constructor when yielding the state. Here’s how you can modify the generator function:

[[See Video to Reveal this Text or Code Snippet]]

Testing the Modification

Now, if you attempt similar list conversions:

[[See Video to Reveal this Text or Code Snippet]]

You’ll see your desired output, showing all the intermediate states correctly captured without any repetitions. Each entry in your list reflects the actual state of the list during those points in time.

Conclusion

In summary, the behavior of the generator function revealed how Python handles mutable objects and the importance of making copies when necessary. To avoid encountering issues with references when working with generators, remember to yield copies of your mutable objects. This practice ensures that you capture the desired information without unexpected changes from later iterations.

Thanks for reading! Happy coding!