feat!: disallow concat(..., how="horizontal") for LazyFrame

narwhals/_dask/namespace.py

@@ -175,24 +175,6 @@ def concat(
                 backend_version=self._backend_version,
                 version=self._version,
             )
-        if how == "horizontal":
-            all_column_names: list[str] = [
-                column for frame in dfs for column in frame.columns
-            ]
-            if len(all_column_names) != len(set(all_column_names)):  # pragma: no cover
-                duplicates = [
-                    i for i in all_column_names if all_column_names.count(i) > 1
-                ]
-                msg = (
-                    f"Columns with name(s): {', '.join(duplicates)} "
-                    "have more than one occurrence"
-                )
-                raise AssertionError(msg)
-            return DaskLazyFrame(
-                dd.concat(dfs, axis=1, join="outer"),
-                backend_version=self._backend_version,
-                version=self._version,
-            )
         if how == "diagonal":
             return DaskLazyFrame(
                 dd.concat(dfs, axis=0, join="outer"),

narwhals/_duckdb/namespace.py

@@ -60,21 +60,16 @@ def _lazyframe(self) -> type[DuckDBLazyFrame]:
         return DuckDBLazyFrame
 
     def concat(
-        self, items: Iterable[DuckDBLazyFrame], *, how: ConcatMethod
+        self: Self, items: Iterable[DuckDBLazyFrame], *, how: ConcatMethod
     ) -> DuckDBLazyFrame:
-        if how == "horizontal":
-            msg = "horizontal concat not supported for duckdb. Please join instead"
-            raise TypeError(msg)
-        if how == "diagonal":
-            msg = "Not implemented yet"
-            raise NotImplementedError(msg)
+        native_items = [item._native_frame for item in items]
         items = list(items)
         first = items[0]
         schema = first.schema
         if how == "vertical" and not all(x.schema == schema for x in items[1:]):
             msg = "inputs should all have the same schema"
             raise TypeError(msg)
-        res = reduce(lambda x, y: x.union(y), (item._native_frame for item in items))
+        res = reduce(lambda x, y: x.union(y), native_items)
         return first._with_native(res)
 
     def concat_str(

narwhals/_spark_like/namespace.py

@@ -192,13 +192,6 @@ def concat(
         self, items: Iterable[SparkLikeLazyFrame], *, how: ConcatMethod
     ) -> SparkLikeLazyFrame:
         dfs = [item._native_frame for item in items]
-        if how == "horizontal":
-            msg = (
-                "Horizontal concatenation is not supported for LazyFrame backed by "
-                "a PySpark DataFrame."
-            )
-            raise NotImplementedError(msg)
-
         if how == "vertical":
             cols_0 = dfs[0].columns
             for i, df in enumerate(dfs[1:], start=1):

narwhals/functions.py

@@ -27,6 +27,7 @@
 from narwhals.dependencies import is_numpy_array
 from narwhals.dependencies import is_numpy_array_2d
 from narwhals.dependencies import is_pyarrow_table
+from narwhals.exceptions import InvalidOperationError
 from narwhals.expr import Expr
 from narwhals.series import Series
 from narwhals.translate import from_native
@@ -79,12 +80,13 @@ def concat(items: Iterable[FrameT], *, how: ConcatMethod = "vertical") -> FrameT
 
             - vertical: Concatenate vertically. Column names must match.
             - horizontal: Concatenate horizontally. If lengths don't match, then
-                missing rows are filled with null values.
+                missing rows are filled with null values. This is only supported
+                when all inputs are (eager) DataFrames.
             - diagonal: Finds a union between the column schemas and fills missing column
                 values with null.
 
     Returns:
-        A new DataFrame, Lazyframe resulting from the concatenation.
+        A new DataFrame or Lazyframe resulting from the concatenation.
 
     Raises:
         TypeError: The items to concatenate should either all be eager, or all lazy
@@ -151,16 +153,25 @@ def concat(items: Iterable[FrameT], *, how: ConcatMethod = "vertical") -> FrameT
         |z: [[null,null],["x","y"]]|
         └──────────────────────────┘
     """
-    if how not in {"horizontal", "vertical", "diagonal"}:  # pragma: no cover
-        msg = "Only vertical, horizontal and diagonal concatenations are supported."
-        raise NotImplementedError(msg)
+    from narwhals.dataframe import LazyFrame
+
     if not items:
-        msg = "No items to concatenate"
+        msg = "No items to concatenate."
         raise ValueError(msg)
     items = list(items)
     validate_laziness(items)
+    if how not in {"horizontal", "vertical", "diagonal"}:  # pragma: no cover
+        msg = "Only vertical, horizontal and diagonal concatenations are supported."
+        raise NotImplementedError(msg)
     first_item = items[0]
     plx = first_item.__narwhals_namespace__()
+    if isinstance(first_item, LazyFrame) and how == "horizontal":
+        msg = (
+            "Horizontal concatenation is not supported for LazyFrames.\n\n"
+            "Hint: you may want to use `join` instead."
+        )
+        raise InvalidOperationError(msg)
+
     return first_item._with_compliant(
         plx.concat([df._compliant_frame for df in items], how=how),
     )

narwhals/stable/v1/__init__.py

@@ -2069,12 +2069,13 @@ def concat(items: Iterable[FrameT], *, how: ConcatMethod = "vertical") -> FrameT
 
             - vertical: Concatenate vertically. Column names must match.
             - horizontal: Concatenate horizontally. If lengths don't match, then
-                missing rows are filled with null values.
+                missing rows are filled with null values. This is only supported
+                when all inputs are (eager) DataFrames.
             - diagonal: Finds a union between the column schemas and fills missing column
                 values with null.
 
     Returns:
-        A new DataFrame, Lazyframe resulting from the concatenation.
+        A new DataFrame or Lazyframe resulting from the concatenation.
 
     Raises:
         TypeError: The items to concatenate should either all be eager, or all lazy

tests/frame/concat_test.py

@@ -3,20 +3,18 @@
 import pytest
 
 import narwhals.stable.v1 as nw
+from narwhals.exceptions import InvalidOperationError
 from tests.utils import Constructor
+from tests.utils import ConstructorEager
 from tests.utils import assert_equal_data
 
 
-def test_concat_horizontal(
-    constructor: Constructor, request: pytest.FixtureRequest
-) -> None:
-    if ("pyspark" in str(constructor)) or "duckdb" in str(constructor):
-        request.applymarker(pytest.mark.xfail)
+def test_concat_horizontal(constructor_eager: ConstructorEager) -> None:
     data = {"a": [1, 3, 2], "b": [4, 4, 6], "z": [7.0, 8.0, 9.0]}
-    df_left = nw.from_native(constructor(data)).lazy()
+    df_left = nw.from_native(constructor_eager(data), eager_only=True)
 
     data_right = {"c": [6, 12, -1], "d": [0, -4, 2]}
-    df_right = nw.from_native(constructor(data_right)).lazy()
+    df_right = nw.from_native(constructor_eager(data_right), eager_only=True)
 
     result = nw.concat([df_left, df_right], how="horizontal")
     expected = {
@@ -30,6 +28,8 @@ def test_concat_horizontal(
 
     with pytest.raises(ValueError, match="No items"):
         nw.concat([])
+    with pytest.raises(InvalidOperationError):
+        nw.concat([df_left.lazy()], how="horizontal")
 
 
 def test_concat_vertical(constructor: Constructor) -> None:

tests/series_only/hist_test.py

@@ -13,6 +13,11 @@
 from tests.utils import ConstructorEager
 from tests.utils import assert_equal_data
 
+xfail_hist = pytest.mark.xfail(
+    reason="https://github.com/narwhals-dev/narwhals/issues/2348", strict=False
+)
+
+
 data = {
     "int": [0, 1, 2, 3, 4, 5, 6],
 }
@@ -76,6 +81,7 @@
 ]
 
 
+@xfail_hist
 @pytest.mark.parametrize("params", bins_and_expected)
 @pytest.mark.parametrize("include_breakpoint", [True, False])
 @pytest.mark.filterwarnings(
@@ -161,6 +167,7 @@ def test_hist_bin(
         assert_equal_data(result, expected)
 
 
+@xfail_hist
 @pytest.mark.parametrize("params", counts_and_expected)
 @pytest.mark.parametrize("include_breakpoint", [True, False])
 @pytest.mark.filterwarnings(
@@ -232,6 +239,7 @@ def test_hist_count(
             )
 
 
+@xfail_hist
 @pytest.mark.filterwarnings(
     "ignore:`Series.hist` is being called from the stable API although considered an unstable feature."
 )
@@ -268,6 +276,7 @@ def test_hist_count_no_spread(
     assert_equal_data(result, expected)
 
 
+@xfail_hist
 @pytest.mark.filterwarnings(
     "ignore:`Series.hist` is being called from the stable API although considered an unstable feature."
 )
@@ -283,6 +292,7 @@ def test_hist_bin_and_bin_count() -> None:
         s.hist(bins=[1, 3], bin_count=4)
 
 
+@xfail_hist
 @pytest.mark.filterwarnings(
     "ignore:`Series.hist` is being called from the stable API although considered an unstable feature."
 )
@@ -331,6 +341,7 @@ def test_hist_small_bins(
         s["values"].hist(bins=[1, 3], bin_count=4)
 
 
+@xfail_hist
 @pytest.mark.filterwarnings(
     "ignore:`Series.hist` is being called from the stable API although considered an unstable feature."
 )
@@ -365,6 +376,7 @@ def test_hist_non_monotonic(constructor_eager: ConstructorEager) -> None:
         st.floats(min_value=0.001, max_value=1_000, allow_nan=False), max_size=50
     ),
 )
+@xfail_hist
 @pytest.mark.filterwarnings(
     "ignore:`Series.hist` is being called from the stable API although considered an unstable feature.",
     "ignore:invalid value encountered in cast:RuntimeWarning",
@@ -421,6 +433,7 @@ def test_hist_bin_hypotheis(
     ),
     bin_count=st.integers(min_value=0, max_value=1_000),
 )
+@xfail_hist
 @pytest.mark.skipif(
     POLARS_VERSION < (1, 15),
     reason="hist(bin_count=...) behavior significantly changed after this version",