Expose object_store for direct use

Commencez par examiner le binding ObjectStore de datafusion-python et l’API object_store Rust sous-jacente décrite dans l’issue. Déterminez quelles opérations directes sur les objets doivent être exposées et vérifiez que l’interface Python résultante fonctionne pour les stores locaux et ceux adossés au cloud ; le travail est terminé lorsque les utilisateurs peuvent réutiliser un ObjectStore configuré aussi bien pour le nettoyage des artefacts que pour l’accès à DataFusion.

Is your feature request related to a problem or challenge? Please describe what you are trying to do.
I need to be able to delete old resources generated by write_parquet() and similar methods, move them out of the way, or do other such operations that broadly fall in the category of 'data/artifact cleanup'. Datafusion doesn't directly implement such move/delete operations, so this requires a different library. Depending on what environment i'm operating in (local file system, S3, google bucket) this requires a slightly different setup and operation.

However, datafusion ships with ObjectStore, a generic frontend for many different object store systems, mainly S3 and its equivalents in other cloud environments, but also providing an api-compatible local file storage version of this. This is used to be able to read and write to such object stores from within datafusion. In datafusion-python, these ObjectStore objects are opaque handles that are only useful for registering with a session context. In rust however, these also allow the user to directly manipulate objects in these stores, fetch them, delete them, move them, etc.

Describe the solution you'd like
I would like the datafusion-python version of ObjectStore to not just be an opaque handle, but instead allow access to the underlying methods. this will allow me to generically implement operations on generated artifacts that are not doable in datafusion directly.

Describe alternatives you've considered
The workaround is to use an s3-compatible library directly. This doesn't help with local files though, which still requires a separate code path.

Another possibility is to have a separate python library wrapping the rust object_store crate, as arguably it's not the job of datafusion-python to provide a good API for this. However, it's useful to be able to define just one ObjectStore (like from a configuration) and use it both for datafusion and for related object-store operations like artifact cleanup.