Скачать или смотреть Creating a Single JSON Record from Multiple JSON Records: A Performance Efficient Approach

Learn how to merge multiple JSON records into a single efficient JSON structure using Python. This guide provides concise coding strategies to optimize your JSON manipulation process.
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Creating a Single JSON Record from Multiple JSON Records: A Performance Efficient Approach

In today's data-driven world, JSON (JavaScript Object Notation) is a widely used format for data interchange. As a programmer, you may encounter situations where you need to convert multiple JSON records into a single JSON record efficiently. In this guide, we'll explore a practical solution to combine these records and how to optimize the code for performance.

The Problem Scenario

Imagine you have a dictionary containing multiple JSON lines, where each line has some common keys and some additional unique ones. Here's a sample structure:

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

The Key Objective

The goal is to write a function that combines these multiple JSON records into one single JSON object, with the following requirements:

Function Arguments:

A list of common keys (e.g., ["processId", "userId", "reportName"]).

The list of dictionaries (the multiple JSON records).

Expected Output:
You want a unified JSON record like this:

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

The Solution

Optimizing the Code

Here’s an optimized method to achieve this goal with fewer lines of code and better readability:

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

How This Works

Extract Common Keys:
We first create a dictionary rec0 that holds only the common keys (the ones that are the same in all JSON records).

Copy the Common Keys:
We then make a copy of rec0 into res so we can build upon it.

Loop Through the Records:
For each record (dct), we enumerate through its items. If a key is not part of the common keys, we append an index to its name to ensure uniqueness. This prevents overwriting any data.

Final Output:
The resulting JSON record contains all common and unique keys, indexed where necessary.

Conclusion

By using this simple yet efficient approach, you not only simplify the code but also enhance its performance. This technique is ideal for any scenario involving JSON manipulation, ensuring a cleaner, more readable, and performance-driven solution.

Feel free to adapt this solution for your own projects and streamline your JSON data handling processes!