fix(python,rust): Align new_columns argument for scan_csv and `read…

…_csv` (#11575)

py-polars/polars/io/csv/functions.py

@@ -799,8 +799,8 @@ def scan_csv(
         Single byte end of line character
     new_columns
         Provide an explicit list of string column names to use (for example, when
-        scanning a headerless CSV file). Note that unlike ``read_csv`` it is considered
-        an error to provide fewer column names than there are columns in the file.
+        scanning a headerless CSV file). If the given list is shorter than the width of
+        the DataFrame the remaining columns will have their original name.
     raise_if_empty
         When there is no data in the source,``NoDataError`` is raised. If this parameter
         is set to False, an empty LazyFrame (with no columns) is returned instead.
@@ -885,8 +885,11 @@ def scan_csv(
             dtypes = dict(zip(new_columns, dtypes))
 
         # wrap new column names as a callable
-        def with_column_names(_cols: list[str]) -> list[str]:
-            return new_columns  # type: ignore[return-value]
+        def with_column_names(cols: list[str]) -> list[str]:
+            if len(cols) > len(new_columns):
+                return new_columns + cols[len(new_columns) :]  # type: ignore[operator]
+            else:
+                return new_columns  # type: ignore[return-value]
 
     _check_arg_is_1byte("separator", separator, can_be_empty=False)
     _check_arg_is_1byte("comment_char", comment_char, can_be_empty=False)

py-polars/src/lazyframe.rs

@@ -217,8 +217,9 @@ impl PyLazyFrame {
                     let new_names = out
                         .extract::<Vec<String>>(py)
                         .expect("python function should return List[str]");
-                    assert_eq!(new_names.len(), schema.len(), "The length of the new names list should be equal to the original column length");
-
+                    polars_ensure!(new_names.len() == schema.len(),
+                        ShapeMismatch: "The length of the new names list should be equal to or less than the original column length",
+                    );
                     Ok(schema
                         .iter_dtypes()
                         .zip(new_names)

py-polars/tests/unit/io/test_csv.py

@@ -1329,6 +1329,19 @@ def test_csv_scan_categorical(tmp_path: Path) -> None:
     assert result["x"].dtype == pl.Categorical
 
 
+@pytest.mark.write_disk()
+def test_csv_scan_new_columns_less_than_original_columns(tmp_path: Path) -> None:
+    tmp_path.mkdir(exist_ok=True)
+
+    df = pl.DataFrame({"x": ["A"], "y": ["A"], "z": "A"})
+
+    file_path = tmp_path / "test_csv_scan_new_columns.csv"
+    df.write_csv(file_path)
+    result = pl.scan_csv(file_path, new_columns=["x_new", "y_new"]).collect()
+
+    assert result.columns == ["x_new", "y_new", "z"]
+
+
 def test_read_csv_chunked() -> None:
     """Check that row count is properly functioning."""
     N = 10_000

py-polars/tests/unit/io/test_lazy_csv.py

@@ -6,7 +6,6 @@
 import pytest
 
 import polars as pl
-from polars.exceptions import PolarsPanicError
 from polars.testing import assert_frame_equal
 
 if TYPE_CHECKING:
@@ -150,12 +149,21 @@ def test_scan_csv_schema_new_columns_dtypes(
         == df1.select(["sugars", pl.col("calories").cast(pl.Int64)]).rows()
     )
 
-    # expect same number of column names as there are columns in the file
-    with pytest.raises(PolarsPanicError, match="should be equal"):
+    # partially rename columns / overwrite dtypes
+    df4 = pl.scan_csv(
+        file_path,
+        dtypes=[pl.Utf8, pl.Utf8],
+        new_columns=["category", "calories"],
+    ).collect()
+    assert df4.dtypes == [pl.Utf8, pl.Utf8, pl.Float64, pl.Int64]
+    assert df4.columns == ["category", "calories", "fats_g", "sugars_g"]
+
+    # cannot have len(new_columns) > len(actual columns)
+    with pytest.raises(pl.ShapeError):
         pl.scan_csv(
             file_path,
             dtypes=[pl.Utf8, pl.Utf8],
-            new_columns=["category", "calories"],
+            new_columns=["category", "calories", "c3", "c4", "c5"],
         ).collect()
 
     # cannot set both 'new_columns' and 'with_column_names'