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Learn how to easily convert UNIX timestamps to readable datetime formats in a JSON object with Python. This guide walks you through the process step-by-step.
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Converting UNIX Timestamps to Readable Datetime in a JSON Object

When working with APIs, you often encounter JSON objects that contain UNIX timestamps. These timestamps represent the specific moment in time when an event occurred, but they are not very user-friendly and difficult to interpret at a glance. The challenge arises when you need to convert these timestamps into a human-readable format, especially if you are dealing with a large dataset. In this post, we will explore how to effectively convert UNIX timestamps in a JSON object to a more understandable datetime format using Python.

Understanding the JSON Structure

Consider a JSON object that has various keys representing different data points. For instance, you may have the following structure containing pricing data over a year:

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Here, each entry in the prices list consists of two elements:

A UNIX timestamp (in milliseconds)

A corresponding price value

In this particular example, the timestamp indicates the date and time in milliseconds since January 1, 1970. Our goal is to convert these timestamps into a readable datetime format.

Step-by-Step Guide to Convert Timestamps

Step 1: Import Required Modules

You will need to import the datetime module, which allows us to work with date and time in Python.

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Step 2: Define Your JSON Object

For the purpose of this example, we will create a simplified version of the JSON object we used earlier. You can adjust the object as needed to include more data or keys.

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Step 3: Loop Through the Timestamps

The next step is to iterate through each item in the prices array, convert the first element (the timestamp) to a readable datetime format, and update the respective value.

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In this code block:

We first convert the timestamp from milliseconds to seconds by dividing by 1000.

Then we use datetime.utcfromtimestamp(ts) to get the date and time in UTC.

We format it to a string representation with a readable format '%Y-%m-%d %H:%M:%S'.

Step 4: Output the Result

Finally, after updating the prices list, we can print the modified JSON object to see the result.

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Resulting Output

After running the entire code, the updated version of the JSON object will look like this:

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Conclusion

Converting UNIX timestamps to a more user-friendly datetime format in JSON objects is straightforward with Python. By following these simple steps, you can easily enhance the readability of your data, making it more accessible for analysis and reporting. Whether you're working on financial applications, data analytics, or any other field where time-stamped data is crucial, mastering this conversion will undoubtedly improve your workflows.

Now you can use this knowledge to work with large datasets and present the information in a way that is easier for others (and yourself) to understand!