Скачать или смотреть Fixing the Jupyter Notebook Instance Overwrite Problem

Discover how to solve the issue of Jupyter Notebook overwriting class instances by understanding instance attributes vs class attributes. Perfect for beginners!
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This video is based on the question https://stackoverflow.com/q/62246114/ asked by the user 'S.A.A' ( https://stackoverflow.com/u/13700037/ ) and on the answer https://stackoverflow.com/a/62246165/ provided by the user 'Simon Notley' ( https://stackoverflow.com/u/9370816/ ) at 'Stack Overflow' website. Thanks to these great users and Stackexchange community for their contributions.

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Understanding the Class Instance Overwrite Problem in Jupyter Notebook

If you're new to programming with Jupyter Notebook, you might encounter some perplexing behaviors that don't appear when running regular .py files. One common issue is when the most recent instance of a class overwrites previous instances, leading to confusion and unexpected results. This guide will explore this problem in-depth and guide you to a proper solution.

The Problem: Overwriting Instances in Jupyter Notebook

Consider the code snippet below, where we create a simple class called testclass:

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

In this setup, after creating and printing two instances of testclass, it seems that the first instance’s values have been changed by the second.

Example Code

Creating the first instance:

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Output:

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Creating the second instance:

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Output:

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Reprinting the first instance:

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Expected Output:

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Actual Output:

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This behavior occurs because you're using the class name (testclass) to assign values. As a result, you inadvertently created class attributes instead of instance attributes.

The Solution: Switching to Instance Attributes

To fix this issue, you need to use self within the _init_ method. This approach allows each instance to maintain its own unique set of attributes. Here’s the corrected version of the _init_ method:

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Revised Class Implementation

With this adjustment, your complete code should look like this:

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Now, if you run the code again:

Creating the first instance:

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

Creating the second instance:

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

Reprinting the first instance:

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

This will give you the expected results where each instance maintains its unique attribute values.

Conclusion: Best Practices for Class Instances in Jupyter Notebook

By understanding and applying the difference between class attributes and instance attributes, you can avoid overwriting instances in Jupyter Notebook.

Additional Tips:

Consider implementing string representations for your classes by overloading the _str_ and _repr_ methods. This can help you print meaningful representations of your class objects.

Always remember to test your classes in various scenarios to ensure that they behave as intended.

With these adjustments, you should now have a clearer understanding of how to manage class instances in Jupyter Notebook effectively. Happy coding!