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Скачать или смотреть Finding Unique Combinations of Two Sets of Identical Lists in Python

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  • 2025-05-28
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Finding Unique Combinations of Two Sets of Identical Lists in Python
Finding all unique combinations of two sets of identical lists?pythonpython 3.xcombinations
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Описание к видео Finding Unique Combinations of Two Sets of Identical Lists in Python

Discover how to find all unique combinations of items from identical lists in Python without repetition, utilizing itertools library for clean and efficient code.
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This video is based on the question https://stackoverflow.com/q/67327461/ asked by the user 'mcfadX' ( https://stackoverflow.com/u/15224404/ ) and on the answer https://stackoverflow.com/a/67327649/ provided by the user 'wjandrea' ( https://stackoverflow.com/u/4518341/ ) at 'Stack Overflow' website. Thanks to these great users and Stackexchange community for their contributions.

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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.

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Finding Unique Combinations of Two Sets of Identical Lists in Python

When dealing with two sets of identical lists in Python, one common problem that arises is how to generate all unique combinations of items without repeating any items in the same combination. For example, if you have lists of crusts, toppings, and sauces for a pizza, you might want to explore all possible combinations while ensuring that two identical toppings or sauces do not appear together. This guide will walk you through an effective solution to this problem using Python's itertools library.

The Problem

Let's say we have the following lists:

Crust types: ['Thin Crust', 'Hand Tossed']

Topping options: ['Bacon', 'Pepperoni', 'Steak']

Sauce options: ['Tomato', 'BBQ', 'Ranch']

Your goal is to generate a list of combinations structured in a specific format:

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

For example:

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

However, you want to prevent duplicates like Bacon, Bacon from appearing in the same combination.

The Solution

Step 1: Set Up Your Lists

To start with, it’s essential to define our lists as follows:

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

By merging the lists into a single topping list and a single sauce list, we streamline our combination generation.

Step 2: Use itertools.combinations

The core of our solution lies in the use of itertools.combinations, which allows us to create combinations of items without repetition. Here's how you can generate the required combinations:

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

With this approach, topping_combs will contain pairs of toppings without duplicates.

Step 3: Create All Combinations Using itertools.product

Next, we can combine crusts, toppings, and sauces using the product function:

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

This creates a Cartesian product of all the specified elements, allowing us to explore every combination.

Step 4: Print the Results

Finally, you can output the results in the desired format:

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

This will iterate over all the combinations and print them nicely formatted.

Example Output

After running the complete code, you would get an output like:

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

Each line represents a unique combination of crust, toppings, and sauces, without any identical toppings or sauces appearing together.

Complete Code

Here's the complete code to achieve this:

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

Conclusion

In this guide, we have successfully tackled the problem of finding all unique combinations of two sets of identical lists in Python while preventing duplicates in the output. Utilizing the combinations and product functions from the itertools library allowed us to generate the desired results efficiently. By following this structured approach, you can apply similar techniques to other data configuration scenarios in Python.

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