Add Arrow-NativeFile and PythonFile support to read_parquet and read_csv in cudf

[rjzamora]

This PR implements a simple but critical subset of the the features implemented and discussed in #8961 and #9225. Note that I suggest those PRs be closed in favor of a few simpler PRs (like this one).

What this PR DOES do:

• Enables users to pass Arrow-based file objects directly to the cudf read_parquet and read_csv functions. For example:

import cudf
import pyarrow.fs as pa_fs

fs, path = pa_fs.FileSystem.from_uri("s3://my-bucket/some-file.parquet")
with fs.open_input_file(path) as fil:
    gdf = cudf.read_parquet(fil)

• Adds automatic conversion of fsspec AbstractBufferedFile objects into Arrow-backed PythonFile objects. For read_parquet, an Arrow-backed PythonFile object can be used (in place of an optimized fsspec transfer) by passing use_python_file_object=True:

import cudf

gdf = cudf.read_parquet(path, use_python_file_object=True)

or

import cudf
from fsspec.core import get_fs_token_paths

fs = get_fs_token_paths(path)[0]
with fs.open(path, mode="rb") as fil:
    gdf = cudf.read_parquet(fil, use_python_file_object=True)

What this PR does NOT do:

• cudf will not automatically produce "direct" (e.g. HadoopFileSystem/S3FileSystem-based) Arrow NativeFile objects for explicit file-path input. It is still up to the user to create/supply a direct NativeFile object to read_csv/parquet if they do not want any python overhead.
• cudf will not accept NativeFile input for IO functions other than read_csv and read_parquet
• dask-cudf does not yet have a mechanism to open/process s3 files as "direct" NativeFile objects - Those changes only apply to direct cudf usage

Props to @shridharathi for doing most of the work for this in #8961 (this PR only extends that work to include parquet and add tests).

[vyasr]

C++ approval

[jrhemstad]

Default constructor is not safe.

[rjzamora]

@gpucibot merge