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Скачать или смотреть Finding Non-Overlapping 3-Element Sets in Python

  • vlogize
  • 2025-09-18
  • 0
Finding Non-Overlapping 3-Element Sets in Python
Find groups of 3-element sets that DO not share elements (no overlap whatsoever) in a listpythonsetoverlap
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Описание к видео Finding Non-Overlapping 3-Element Sets in Python

Discover how to find groups of 3-element sets in Python that do not share any elements. This guide provides a clear algorithm and example to solve the problem effectively.
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This video is based on the question https://stackoverflow.com/q/62240388/ asked by the user 'Travis Wells' ( https://stackoverflow.com/u/4967582/ ) and on the answer https://stackoverflow.com/a/62240492/ provided by the user 'Nick' ( https://stackoverflow.com/u/9473764/ ) 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: Find groups of 3-element sets that DO not share elements (no overlap whatsoever) in a list

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.
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How to Find Non-Overlapping 3-Element Sets in Python

Managing sets of data that do not share elements can be a challenging task, especially when dealing with larger datasets. For those working with lists of sets, you might find yourself needing to group these sets into collections that do not overlap at all. This guide will provide a step-by-step breakdown of how to achieve this efficiently in Python.

The Problem

In our scenario, we have lists containing 3-element sets, and our goal is to extract groups of these sets that do not share any elements. This means that each set in the output should be entirely unique with respect to the others, ensuring no values are repeated across the groups.

Example Input

Consider the following list of sets:

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

From this list, you might want an output that looks like:

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

In this case, you can see that 4 and 3 overlap with the first set; thus, they are excluded.

The Solution

Here's a straightforward approach to solve the problem using Python sets. The method will iterate through the list and check for overlaps using a set that keeps track of seen elements. This way, we ensure no duplicates across our selected sets.

Step-by-Step Breakdown

Initialize the input list and necessary variables:

Create an empty list for new sets.

Initialize a set to track unique elements.

Iterate through each list in the input:

For each sublist, check if any of its elements are already in the set of seen elements.

If not, add the sublist to the new list and update the seen set with its elements.

Print the output:

The result will be a new list of overlapping-free sets.

The Code

Here's the complete code that implements the above logic:

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

Expected Output

When you run the above code, the output will be:

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

This output confirms that the sets included are completely non-overlapping.

Conclusion

Finding non-overlapping 3-element sets in Python can be efficiently handled with sets for tracking unique elements. This method not only ensures correctness but is also effective for larger datasets. You can adapt and extend this approach to handle different types of datasets or to integrate it into larger algorithms as needed.

Feel free to implement this algorithm in your projects, and you'll find it invaluable for managing collections of data in Python!

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