Learn how to resolve the `NotImplementedError` when calling overloaded functions in Python by providing the necessary implementation in a clear and concise manner.
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Understanding the NotImplementedError: Handling Overloaded Functions in Python

When you’re working with Python, you may encounter the NotImplementedError, especially when dealing with function overloading. This error can be quite confusing if you’re not familiar with how overloaded functions work in Python. In this post, we will delve into what causes this error and provide a straightforward solution to fix it.

The Problem

Consider the following code snippet that employs function overloading with the @overload decorator:

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

While calling this function with var.setSize((500,500)), you may be surprised to see the following error message:

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

So, what does this mean?

Why Does This Error Occur?

This error occurs due to a misunderstanding of how the @overload decorator works in Python:

Purpose of @overload: The @overload decorator is used to specify multiple signatures for a function in a way that helps static type checkers understand the function’s usage. However, @overload does not provide an implementation of the function itself. It merely serves as documentation for developers and static type checkers.

Missing Implementation: With overloaded functions, after defining the signatures using @overload, you must provide a concrete implementation that is not decorated with @overload. This implementation is where the actual logic of the function resides.

How to Fix the Issue

To address the NotImplementedError, follow these steps to ensure that you have a concrete implementation of your overloaded function:

Step 1: Add the Implementation Method

At the end of your overloaded functions, add a final implementation method that combines the signatures. It could look something like this:

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

Step 2: Test Your Code

After adding your implementation method, try calling your function again:

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

Key Takeaways

Always remember that the @overload decorator only defines the expected function signatures and does not contain any executable code.

Ensure to include a concrete implementation after defining overloaded methods to avoid NotImplementedError.

By following these guidelines, you ensure your overloaded functions in Python are both meaningful and functional, providing the flexibility you need without running into confusing errors. Happy coding!

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