How to Fix Class Objects in numpy.array() that Don't Work Properly

Learn how to resolve the issue of class objects in numpy arrays displaying the same values. This blog covers a Python coding error and how to fix it.
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Understanding the Problem

Here's a brief overview of the problem. You are creating an array of objects for a class meant to store job-related data, namely job ID, deadline, and profit. However, when you run your code, all elements of the numpy array return identical values instead of individual ones for each instance. This is a frustrating issue, especially when you expect distinct outputs.

Let’s look at the code you provided:

Your Code

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Input Example

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Expected Output

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Actual Output

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Clearly, this isn't the output you were hoping for.

What’s Going Wrong?

The root of the issue lies in how you're creating instances of your class.

You initialize the value class once outside of the loop with val = value().

As you iterate through the loop and call initialize(), you are modifying the same instance every time.

Consequently, when you populate the numpy array, each position ends up referencing this single instance of the class that now contains only the last set of input values.

The Solution: Creating New Instances

The solution to your problem is straightforward: create a new instance of the value class for each entry in your array. Here’s how to modify your code accordingly:

Revised Code Implementation

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Key Changes

Instance Creation: Move val = value() inside the loop. This alteration ensures that a new instance is created for each input, storing values independently based on the user interaction.

Conclusion

Feel free to reach out if you have any questions or need further clarification on this topic. Happy coding!