I’m using pylance with Cursor/VS Code and keep seeing these errors that I’m spending money on having the ai fix. I may try to fix one manually once in a while, which I’m not sure why I would do that because the cost is about 4 cents a change.

Anyway this will be a list of common deprecated terms and fixes.

dict() has been deprecated in favor of model_dump()

From Claude 3.7:

Handling Pydantic's .dict() to .model_dump() Migration

You're right to be concerned about the deprecated .dict() method. Here's how to approach this:

Recommended Approach

I recommend a staged approach rather than a global search and replace:

Understand your Pydantic version first:
If you're using Pydantic v1.x, .dict() works but is deprecated with warnings

If you've upgraded to Pydantic v2.x, you should definitely migrate to .model_dump()
Check for compatibility issues:
.dict() and .model_dump() are similar but have some differences in their parameters

For example, .dict() uses exclude_unset, while .model_dump() uses exclude_unset_fields
Staged replacement:

Start with one file at a time, testing after each change

Focus on critical paths first

Use version-compatible code if you need to support both v1 and v2

Implementation Options

Option 1: File-by-file replacement (recommended)

Replace .dict() with .model_dump() in one file at a time, then test your application to ensure everything works correctly.

Option 2: Create a compatibility function

def model_to_dict(model):
    """Convert a Pydantic model to a dict, compatible with both v1 and v2."""
    if hasattr(model, 'model_dump'):
        return model.model_dump()
    return model.dict()  # Fallback for v1

Option 3: Global search and replace (risky)

Only do this if you're confident in your test coverage and have a way to revert changes quickly.

Common Patterns to Look For

When replacing .dict() with .model_dump(), watch for these patterns:
Simple usage: model.dict() → model.model_dump()

With parameters: model.dict(exclude_unset=True) → model.model_dump(exclude_unset_fields=True)
Unpacking: **model.dict() → **model.model_dump()

To Find your version of pydantic

pip show pydantic

Conclusion

I recommend the file-by-file approach, starting with the file you’re currently working on. This gives you more control and reduces the risk of breaking your application. After each change, run your tests to ensure everything still works correctly.

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