added PyarrowTableResult

[zilto]

You can pass to.SAVER(dependencies=["NODE_NAME"], combine=PyarrowTableResult()) to convert the specified node to the pyarrow.Table before materialization. The first motivation was to support more than pd.DataFrame and pyarrow.Table with the dlt DataSaver plugin. More generally, it can be useful for platform teams that want to have a "single way to store parquet files" that is independent of the specific API of a library (e.g., pandas, polars)

see #829 for more details

Changes

• added h_pyarrow and tests
• updated the dlt plugin example notebook

How I tested this

• added 2 tests

Notes

Checklist

• PR has an informative and human-readable title (this will be pulled into the release notes)
• Changes are limited to a single goal (no scope creep)
• Code passed the pre-commit check & code is left cleaner/nicer than when first encountered.
• Any change in functionality is tested
• New functions are documented (with a description, list of inputs, and expected output)
• Placeholder code is flagged / future TODOs are captured in comments
• Project documentation has been updated if adding/changing functionality.

[skrawcz]

it would be nice to be stricter on types...

[skrawcz]

e.g.

def input_types(self) -> List[Type[Type]]:
    """Gives the applicable types to this result builder.
    This is optional for backwards compatibility, but is recommended.

    :return: A list of types that this can apply to.
    """
    _types = []
    try:
       import ...
   except ...
    return _types

[zilto]

In that case, the real check is if it implements __dataframe__(), which is done through pyarrow.interchange.from_dataframe() under build_result(). The PyarrowTableResult serve a slightly different role of "universal adapter" to help us avoid maintaining an explicit list of types (which is bound to grow). I opted to not include input_types() if it was to return Any.