doc: demostrate retrieving query result in arrow format

compatibility/pg-pytools/pyarrow_test.py

@@ -48,3 +48,16 @@
             df_from_pg = df_from_pg.astype({'id': 'int64', 'num': 'int64'})
             # Compare the original DataFrame with the DataFrame from PostgreSQL
             assert df.equals(df_from_pg), "DataFrames are not equal"
+
+        # Copy query result to a pandas DataFrame
+        arrow_data = io.BytesIO()
+        with cur.copy("COPY (SELECT id, num * num AS num FROM test.tb1) TO STDOUT (FORMAT arrow)") as copy:
+            for block in copy:
+                arrow_data.write(block)
+
+            with pa.ipc.open_stream(arrow_data.getvalue()) as reader:
+                df_from_pg = reader.read_pandas().astype({'id': 'int64', 'num': 'int64'})
+                df['num'] = df['num'] ** 2
+                df = df.drop('data', axis='columns')
+                # Compare the original DataFrame with the DataFrame from PostgreSQL
+                assert df.equals(df_from_pg), "DataFrames are not equal"

docs/tutorial/pg-python-data-tools.md

@@ -119,3 +119,25 @@ polars_df = pl.from_arrow(arrow_df)
 ```python
 polars_df = pl.from_pandas(pandas_df)
 ```
+
+## 4. Retrieving Query Results as DataFrames
+
+You can also retrieve query results from MyDuck Server as DataFrames using Arrow format. Here is an example:
+
+```python
+import io
+import polars as pl
+import pyarrow as pa
+import psycopg
+
+# Copy query result to a Polars DataFrame
+arrow_data = io.BytesIO()
+with cur.copy("COPY (SELECT id, num * num AS num FROM test.tb1) TO STDOUT (FORMAT arrow)") as copy:
+    for block in copy:
+        arrow_data.write(block)
+
+    with pa.ipc.open_stream(arrow_data.getvalue()) as reader:
+        arrow_table = reader.read_all()
+        polars_df = pl.from_arrow(arrow_table)
+        print(polars_df)
+```