How to Avoid 'RuntimeError: dictionary changed size during iteration' Error

Summary: Learn how to prevent the "RuntimeError: dictionary changed size during iteration" error in Python by understanding its causes and implementing effective solutions.
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When working with dictionaries in Python, you might encounter the "RuntimeError: dictionary changed size during iteration" error. This error occurs when you attempt to modify a dictionary (e.g., adding or removing keys) while iterating over it. Understanding why this happens and how to avoid it can save you from unexpected crashes and make your code more robust. In this post, we'll explore the causes of this error and provide practical solutions to avoid it.

Understanding the Error

Dictionaries in Python are dynamic structures that can grow and shrink. However, when you iterate over a dictionary, Python expects the dictionary to remain the same size throughout the iteration. Modifying the dictionary during this process disrupts the internal state, leading to the "RuntimeError: dictionary changed size during iteration."

Causes of the Error

This error typically occurs in the following scenarios:

Adding keys during iteration:

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Removing keys during iteration:

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Solutions to Avoid the Error

Iterate Over a Copy of the Dictionary
One straightforward solution is to iterate over a copy of the dictionary's keys or items, allowing you to modify the original dictionary without issues.

Using .copy() Method:

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Using list() Function:

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Collect Changes and Apply Them After Iteration
Another approach is to collect changes in a separate list or dictionary and apply them after the iteration is complete.

Example:

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Use Dictionary Comprehensions
If the goal is to filter the dictionary, dictionary comprehensions can be a clean and concise way to create a new dictionary without modifying the original during iteration.

Example:

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Conclusion

The "RuntimeError: dictionary changed size during iteration" error can be frustrating, but with the right approach, it is easily avoidable. By iterating over a copy of the dictionary, collecting changes for later application, or using dictionary comprehensions, you can safely modify dictionaries without encountering this error. Implement these strategies to ensure your Python code runs smoothly and efficiently.