kylebarron commented on issue #1008:
URL: 
https://github.com/apache/datafusion-python/issues/1008#issuecomment-2622430293

   I agree! This is why I created 
[obstore](https://github.com/developmentseed/obstore). It's a fast Python 
binding for `object_store`.
   
   > 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.
   
   This is the goal of 
[`pyo3_object_store`](https://github.com/developmentseed/obstore/tree/main/pyo3-object_store),
 so that we can define configuration and builders around `object_store` _once_ 
and then reuse it across many different Rust-Python libraries that internally 
use `object_store`.
   
   I.e. `obstore` is for Python end users who want to use `object_store` from 
Python, while `pyo3_object_store` is for other Rust developers creating their 
own Python packages who want to use `object_store` from Rust.
   
   So far, I've put more effort into publishing `obstore` than 
`pyo3_object_store`, but I'd like to polish up `pyo3_object_store` (especially 
after the next `object_store` release) and I'd be happy to explore using it 
inside `datafusion-python` if there's interest.
   
   Unfortunately, you can't currently use _one_ store class across multiple 
Python libraries because `object_store` is not FFI stable. So you need to use 
the class _exported from `obstore`_ whenever you use obstore methods, and you'd 
need to use the class _exported from `datafusion.python`_ whenever you use 
datafusion methods (even though each class would take the same builder params). 
Or, we could try to solve the object_store FFI problem.


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