Add public APIs to Access Underlying cudf and pandas Objects from cudf.pandas Proxy Objects

docs/cudf/source/cudf_pandas/faq.md

@@ -142,6 +142,24 @@ cuDF (learn more in [this
 blog](https://medium.com/rapids-ai/easy-cpu-gpu-arrays-and-dataframes-run-your-dask-code-where-youd-like-e349d92351d)) and the [RAPIDS Accelerator for Apache Spark](https://nvidia.github.io/spark-rapids/)
 provides a similar configuration-based plugin for Spark.
 
+
+## Recommendation for libraries that are type aware.
+
+When working with `cudf.pandas` proxy objects, it is important to access the real underlying objects to ensure compatibility with libraries that are `cudf` or `pandas` aware. You can use the following methods to retrieve the actual `cudf` or `pandas` objects:
+
+- `get_cudf_pandas_fast_object()`: This method returns the fast `cudf` object from the proxy.
+- `get_cudf_pandas_slow_object()`: This method returns the slow `pandas` object from the proxy.
+
+Here is an example of how to use these methods:
+
+```python
+# Assuming `proxy_obj` is a cudf.pandas proxy object
+fast_obj = proxy_obj.get_cudf_pandas_fast_object()
+slow_obj = proxy_obj.get_cudf_pandas_slow_object()
+
+# Now you can use `fast_obj` and `slow_obj` with libraries that are cudf or pandas aware
+```
+
 (are-there-any-known-limitations)=
 ## Are there any known limitations?
 

python/cudf/cudf/pandas/fast_slow_proxy.py

@@ -204,6 +204,12 @@ def _fsproxy_fast_to_slow(self):
             return fast_to_slow(self._fsproxy_wrapped)
         return self._fsproxy_wrapped
 
+    def get_cudf_pandas_fast_object(self):
+        return self._fsproxy_slow_to_fast()
+
+    def get_cudf_pandas_slow_object(self):
+        return self._fsproxy_fast_to_slow()
+
     @property  # type: ignore
     def _fsproxy_state(self) -> _State:
         return (
@@ -221,6 +227,8 @@ def _fsproxy_state(self) -> _State:
         "_fsproxy_slow_type": slow_type,
         "_fsproxy_slow_to_fast": _fsproxy_slow_to_fast,
         "_fsproxy_fast_to_slow": _fsproxy_fast_to_slow,
+        "get_cudf_pandas_fast_object": get_cudf_pandas_fast_object,
+        "get_cudf_pandas_slow_object": get_cudf_pandas_slow_object,
         "_fsproxy_state": _fsproxy_state,
     }
 

python/cudf/cudf_pandas_tests/test_cudf_pandas.py

@@ -1885,3 +1885,9 @@ def test_dataframe_setitem():
     new_df = df + 1
     df[df.columns] = new_df
     tm.assert_equal(df, new_df)
+
+
+def test_dataframe_get_fast_slow_methods():
+    df = xpd.DataFrame({"a": [1, 2, 3], "b": [1, 2, 3]})
+    assert isinstance(df.get_cudf_pandas_fast_object(), cudf.DataFrame)
+    assert isinstance(df.get_cudf_pandas_slow_object(), pd.DataFrame)