refactor(pkg-py): inline duckdb result conversion calls

Remove duckdb_result_to_polars and duckdb_result_to_pandas functions
as thin abstractions that don't add value. Inline the .pl() and .df()
calls directly in PolarsLazySource.

Co-Authored-By: Claude Opus 4.5 <[email protected]>

Author: cpsievert

pkg-py/src/querychat/_datasource.py

@@ -10,8 +10,6 @@
 from sqlalchemy.sql import sqltypes
 
 from ._df_compat import (
-    duckdb_result_to_pandas,
-    duckdb_result_to_polars,
     read_sql_pandas,
     read_sql_polars,
     read_sql_pyarrow,
@@ -320,9 +318,9 @@ def execute_query(self, query: str) -> IntoDataFrameT:
         check_query(query)
         result = self._conn.execute(query)
         if self._df_lib == "polars":
-            return duckdb_result_to_polars(result)
+            return result.pl()
         else:
-            return duckdb_result_to_pandas(result)
+            return result.df()
 
     def test_query(
         self, query: str, *, require_all_columns: bool = False
@@ -352,10 +350,7 @@ def test_query(
         """
         check_query(query)
         result = self._conn.execute(f"{query} LIMIT 1")
-        if self._df_lib == "polars":
-            native_result = duckdb_result_to_polars(result)
-        else:
-            native_result = duckdb_result_to_pandas(result)
+        native_result = result.pl() if self._df_lib == "polars" else result.df()
 
         if require_all_columns:
             result_columns = set(native_result.columns)

pkg-py/src/querychat/_df_compat.py

@@ -9,7 +9,6 @@
 import narwhals.stable.v1 as nw
 
 if TYPE_CHECKING:
-    import duckdb
     from sqlalchemy.engine import Connection
     from sqlalchemy.sql.elements import TextClause
 
@@ -57,20 +56,6 @@ def read_sql_pyarrow(query: TextClause, conn: Connection):
     return pl.read_database(query, connection=conn).to_arrow()
 
 
-def duckdb_result_to_polars(
-    result: duckdb.DuckDBPyRelation | duckdb.DuckDBPyConnection,
-):
-    """Convert DuckDB result to native polars DataFrame."""
-    return result.pl()
-
-
-def duckdb_result_to_pandas(
-    result: duckdb.DuckDBPyRelation | duckdb.DuckDBPyConnection,
-):
-    """Convert DuckDB result to native pandas DataFrame."""
-    return result.df()
-
-
 def read_csv(path: str) -> nw.DataFrame:
     try:
         import polars as pl  # pyright: ignore[reportMissingImports]

pkg-py/tests/test_df_compat.py

@@ -4,10 +4,9 @@
 import tempfile
 from pathlib import Path
 
-import duckdb
 import narwhals.stable.v1 as nw
 import pytest
-from querychat._df_compat import duckdb_result_to_polars, read_csv
+from querychat._df_compat import read_csv
 
 # Check if polars and pyarrow are available (both needed for DuckDB + polars)
 try:
@@ -60,47 +59,6 @@ def test_read_csv_data_integrity(self, gzip_csv_file):
         assert names == ["Alice", "Bob", "Charlie"]
 
 
-@pytest.mark.skipif(
-    not HAS_POLARS_WITH_PYARROW, reason="polars or pyarrow not installed"
-)
-class TestDuckdbResultToPolars:
-    """Tests for the duckdb_result_to_polars function."""
-
-    @pytest.fixture
-    def duckdb_conn(self):
-        """Create a DuckDB connection with test data."""
-        conn = duckdb.connect(":memory:")
-        conn.execute("CREATE TABLE test (id INTEGER, name VARCHAR, value DOUBLE)")
-        conn.execute("INSERT INTO test VALUES (1, 'Alice', 10.5)")
-        conn.execute("INSERT INTO test VALUES (2, 'Bob', 20.5)")
-        yield conn
-        conn.close()
-
-    def test_duckdb_result_returns_polars_dataframe(self, duckdb_conn):
-        """Test that duckdb_result_to_polars returns a polars DataFrame."""
-        result = duckdb_conn.execute("SELECT * FROM test")
-        df = duckdb_result_to_polars(result)
-        assert isinstance(df, pl.DataFrame)
-
-    def test_duckdb_result_has_correct_data(self, duckdb_conn):
-        """Test that duckdb_result_to_polars preserves data correctly."""
-        result = duckdb_conn.execute("SELECT * FROM test ORDER BY id")
-        df = duckdb_result_to_polars(result)
-
-        assert df.shape == (2, 3)
-        assert list(df.columns) == ["id", "name", "value"]
-        assert df["id"].to_list() == [1, 2]
-        assert df["name"].to_list() == ["Alice", "Bob"]
-
-    def test_duckdb_result_empty_query(self, duckdb_conn):
-        """Test handling of empty query results."""
-        result = duckdb_conn.execute("SELECT * FROM test WHERE id > 100")
-        df = duckdb_result_to_polars(result)
-
-        assert isinstance(df, pl.DataFrame)
-        assert df.shape == (0, 3)
-
-
 @pytest.mark.skipif(
     not HAS_POLARS_WITH_PYARROW, reason="polars or pyarrow not installed"
 )