Скачать или смотреть How to Remove Duplicate Dictionaries Based on Key-Value Pairs in Python

Learn how to effectively remove duplicate dictionaries in Python by combining keys and avoiding duplicates, ensuring a clean data structure for your applications.
---
This video is based on the question https://stackoverflow.com/q/62650520/ asked by the user 'Toan Nguyen Phuoc' ( https://stackoverflow.com/u/11118581/ ) and on the answer https://stackoverflow.com/a/62650685/ provided by the user 'Ronie Martinez' ( https://stackoverflow.com/u/1279157/ ) 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: Remove duplicate dict based on key and value in dict

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 Remove Duplicate Dictionaries Based on Key-Value Pairs in Python

When working with structured data in Python, such as dictionaries, you may encounter scenarios where duplicate entries can lead to inefficiencies or errors in your application. In this guide, we’ll explore a common problem: how to remove duplicate dictionaries based on their key-value pairs, combining the values when necessary to create a streamlined data structure.

Understanding the Problem

Imagine you have a list of dictionaries where each dictionary contains a key associated with a list of values. In many cases, you might find multiple entries sharing the same key but with different values. For instance, consider the following data structure:

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

You want to achieve the following result, where duplicates are removed, and values for the same key are combined:

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

Let’s dive into the solution.

The Solution

The solution involves iterating over the list of dictionaries and using Python's defaultdict to effortlessly collect and combine values. Below are the steps to implement this.

1. Importing Required Module

First, you need to import the defaultdict from the collections module, which allows for easier management of lists associated with dictionary keys.

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

2. Collecting Values

Next, we will create a defaultdict to store our combined results:

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

3. Iterating through the Matches

Now, we’ll iterate through each dictionary in the matches list, adding values to our result dictionary:

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

4. Converting the Result Back to a List of Dictionaries

Finally, convert the result into a list of dictionaries before displaying or returning it:

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

Making Values Unique

After running the above code, you may notice that duplicate values within lists are not filtered out. To address this, you can convert the lists to sets, ensuring all values are unique:

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

Complete Code Example

Here’s the complete code for reference:

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

Conclusion

In summary, we successfully removed duplicate dictionaries and combined values based on keys using a simple yet effective approach in Python. By utilizing defaultdict, we can manage more complex structures and clean up our data effortlessly. This technique is particularly valuable when handling large datasets with potential redundancy.

With the steps and code provided above, you’re well-equipped to tackle similar challenges in your existing or upcoming projects. Happy coding!