[Python] How do I efficiently hash a Polars dataframe?

I am trying to implement some caching logic on a function that acts on a Polars dataframe (this is all in Python).

To avoid needlessly re-computing the result, it'd be great if I could quickly check if the dataframe has changed - ie. a hash comparison.

I am currently using:

_my_hash = df.hash_rows().sum() # int


But curious to know if there are better options.

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