Скачать или смотреть Merging Two Lists of Dictionaries in Python

Learn how to effectively merge two lists of dictionaries in Python using a simple function that combines paths by their positional keys.
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Merging Two Lists of Dictionaries in Python: A Step-by-Step Guide

In Python, merging data can sometimes become a complicated task, especially when you're dealing with lists of dictionaries. If you've ever found yourself needing to combine two lists of dictionaries based on a common key, you’re in the right place. This guide will walk you through a specific scenario where you need to merge paths from two lists of dictionaries based on their positional values (pos).

The Problem: Understanding the Data Structures

You may be working with two lists of dictionaries that look like this:

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Here’s the structure we see:

data_1 contains dictionaries with paths as a list of lists and a pos key to identify each entry.

data_2 has a similar structure, and you need to merge these lists such that each unique pos combines the corresponding paths from both lists.

Desired Outcome

The goal is to produce an output that combines these paths into a single list, resulting in something like this:

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The Solution: Implementing the Merge Function

To achieve this, you can define a function called join_data. Let’s break down the implementation step-by-step.

Step 1: Initialize the Merge Logic

We'll use an intermediate dictionary to keep track of the pos as keys and merge the paths as values.

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merged.setdefault(d['pos'], []): This will initialize an empty list for a new position, if it doesn't already exist.

.extend(d['paths']): This merges the paths from both lists into the corresponding position.

Step 3: Reformat the Merged Data

After merging, we need to convert our intermediate dictionary back into the list of dictionaries format.

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Step 4: Putting It All Together

Now we can put everything together and see the function in action:

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Final Output

Running this code will yield the desired output:

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Conclusion

Merging two lists of dictionaries by their positional values can be achieved effectively in Python through the use of a dictionary for intermediate storage. This approach allows for clean handling of data without losing any entries or paths. By following the steps outlined in this guide, you can confidently adapt the logic to fit your data needs.

Make sure to test the function with various data sets to see how it performs across different scenarios. Happy coding!