Скачать или смотреть How to Define a Shared List in a Recursive Function in Python

Discover how to encapsulate a function in Python by using a shared list. Learn how to pass lists as function arguments in recursion.
---
This video is based on the question https://stackoverflow.com/q/62679295/ asked by the user 'zahra honarvar' ( https://stackoverflow.com/u/13346054/ ) and on the answer https://stackoverflow.com/a/62679319/ provided by the user 'Kasra Najafi' ( https://stackoverflow.com/u/13151077/ ) at 'Stack Overflow' website. Thanks to these great users and Stackexchange community for their contributions.

Visit these links for original content and any more details, such as alternate solutions, latest updates/developments on topic, comments, revision history etc. For example, the original title of the Question was: How can i define a shared list in the recursive function in python?

Also, Content (except music) licensed under CC BY-SA https://meta.stackexchange.com/help/l...
The original Question post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license, and the original Answer post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license.

If anything seems off to you, please feel free to write me at vlogize [AT] gmail [DOT] com.
---
How to Define a Shared List in a Recursive Function in Python

When working with recursion in Python, it’s common to encounter the need for shared state, particularly when dealing with lists. If you’ve tried defining a list inside your recursive function, you may have noticed that this creates a local variable that doesn't retain its values across function calls. This raises an interesting question: How can you define a shared list within a recursive function without making it a global variable?

In this guide, we'll explore how to properly encapsulate your function while still using a shared list in your recursion.

The Problem

Consider the following code where a list is defined outside of a recursive function. The function appends numbers to this list as it recursively decrements a value:

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

In this example, the list s is shared correctly across the recursion because it is defined outside the function. However, you might want the list to be encapsulated within the function instead without relying on global variables.

The challenge is that defining the list inside the function will make it a local variable. Local variables do not retain values between recursive calls, which defeats the purpose of maintaining a shared state.

The Solution: Use Function Arguments

To overcome this issue, we can modify our approach by passing the list as an argument to the recursive function. Here’s how you can do that:

Step-by-step Breakdown

Initialize the List as a Function Argument: You can provide a default value for the list parameter in your recursive function. This allows the list to retain its state across recursive calls.

Check the Base Case: Similar to the original function, you need a base case. If your variable n reaches 0, it should return the list.

Append and Call Recursion: Append the current value of n to the list. Then, call the recursion with the decremented value of n and the list itself.

Here's how you can implement this solution:

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

Explanation of the Code

def rec(n, s=[]): The function rec takes two arguments, n and s, where s has a default empty list.

if n == 0: return s: This checks if the base case is met. If n is 0, the function returns the accumulated list.

s.append(n): This adds the current value of n to the list.

return rec(n-1, s): This makes the recursive call, passing the list s so that its state is preserved through the recursive calls.

Conclusion

Using a function argument for a shared list allows you to maintain encapsulation while still sharing the list across recursive calls. By following the approach demonstrated above, you prevent the need to resort to global variables and allow for cleaner, more organized code.

Next time you face a similar challenge, remember this method to effectively manage shared state within your recursive functions in Python!