Fixing Python dataclass Errors: Setting Default Lists with Values

Learn how to properly set default values for lists in Python dataclasses using `default_factory` instead of mutable defaults to avoid common errors.
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This video is based on the question stackoverflow.com/q/69564830/ asked by the user 'mark12345' ( stackoverflow.com/u/14951175/ ) and on the answer stackoverflow.com/a/69564866/ provided by the user 'Evan Summers' ( stackoverflow.com/u/16811479/ ) at 'Stack Overflow' website. Thanks to these great users and Stackexchange community for their contributions.

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Understanding the Issue with Default Lists in Python Dataclasses

When you start using Python's dataclass, you may encounter certain quirks that can lead to confusing errors—especially related to mutable default values. If you're trying to set default lists in a dataclass and you see an error like this:

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don't worry! You’re not alone, and we've got you covered on how to resolve this.

What Is the Problem?

The issue arises from how Python handles mutable objects, like lists. When you provide a mutable object as a default value in a function (or a dataclass), all instances of that dataclass end up sharing the same list instance. This leads to unexpected behaviors: changing the list in one instance modifies it for all instances.

Example of the Problematic Code

Here's the problematic code as described:

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When you try to access MyClass.my_list, you'll get the ValueError indicating a "mutable default." This is because you're trying to assign a list directly, which Python doesn't allow for dataclasses.

The Solution: Using default_factory

To resolve this, you should utilize the default_factory option provided by the dataclasses module. This allows you to create a new instance of a list (or any other mutable type) for every single instance of your dataclass. Here’s how you can modify your class definition:

Modified Class Implementation

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Breakdown of Changes:

Import field from dataclasses: This is necessary to use default_factory.

Use field(default_factory=...): This tells Python to call the provided function (in this case, a lambda function) to generate a new list for each instance.

With this structure, each instance of MyClass will have its own independent lists for my_list and my_list2, thus avoiding any mixed-up states due to shared data.

Summary

Don't use mutable objects like lists as default values in dataclasses.

Always prefer default_factory to ensure each instance has its own separate data.

Using a lambda function with default_factory makes your code cleaner and more predictable.

By following these guidelines, you should be able to avoid the common pitfalls associated with mutable defaults in Python dataclasses. Happy coding!