[Coming soon] Support Polars objects for cache hashing

[BartSchuurmans]

Checklist

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Summary

When passing a Polars dataframe to a function that is decorated with @st.cache_data, you get the following error:

UnhashableParamError: Cannot hash argument 'my_df' (of type polars.dataframe.frame.DataFrame) in 'my_func'.

Follow-up of #5088 (comment)

Why?

I want to be able to cache functions that have a Polars dataframe as input.

How?

There is already support for Pandas dataframes:

streamlit/lib/streamlit/runtime/caching/hashing.py

Lines 434 to 453 in 9914751

	elif type_util.is_type(obj, "pandas.core.frame.DataFrame"):
	import pandas as pd
	obj = cast(pd.DataFrame, obj)
	self.update(h, obj.shape)
	if len(obj) >= _PANDAS_ROWS_LARGE:
	obj = obj.sample(n=_PANDAS_SAMPLE_SIZE, random_state=0)
	try:
	column_hash_bytes = self.to_bytes(
	pd.util.hash_pandas_object(obj.dtypes)
	)
	self.update(h, column_hash_bytes)
	values_hash_bytes = self.to_bytes(pd.util.hash_pandas_object(obj))
	self.update(h, values_hash_bytes)
	return h.digest()
	except TypeError:
	# Use pickle if pandas cannot hash the object for example if
	# it contains unhashable objects.
	return b"%s" % pickle.dumps(obj, pickle.HIGHEST_PROTOCOL)

Support for Polars dataframes could be implemented the same way.
Alternative: Use https://github.com/narwhals-dev/narwhals for a dataframe-agnostic implementation.

Additional Context

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[MarcoGorelli]

Hey

Alternative: Use https://github.com/narwhals-dev/narwhals for a dataframe-agnostic implementation.

I just wanted to note that Streamlit depends on Altair, which in turn already depends on Narwhals. So, Streamlit would be able to use Narwhals functionality with zero cost to its users as they all already have it installed because of Altair