done

lib/python3.11/site-packages/narwhals/_spark_like/group_by.py

@@ -0,0 +1,37 @@
+from __future__ import annotations
+
+from typing import TYPE_CHECKING
+
+from narwhals._sql.group_by import SQLGroupBy
+
+if TYPE_CHECKING:
+    from collections.abc import Sequence
+
+    from sqlframe.base.column import Column  # noqa: F401
+
+    from narwhals._spark_like.dataframe import SparkLikeLazyFrame
+    from narwhals._spark_like.expr import SparkLikeExpr
+
+
+class SparkLikeLazyGroupBy(SQLGroupBy["SparkLikeLazyFrame", "SparkLikeExpr", "Column"]):
+    def __init__(
+        self,
+        df: SparkLikeLazyFrame,
+        keys: Sequence[SparkLikeExpr] | Sequence[str],
+        /,
+        *,
+        drop_null_keys: bool,
+    ) -> None:
+        frame, self._keys, self._output_key_names = self._parse_keys(df, keys=keys)
+        self._compliant_frame = frame.drop_nulls(self._keys) if drop_null_keys else frame
+
+    def agg(self, *exprs: SparkLikeExpr) -> SparkLikeLazyFrame:
+        result = (
+            self.compliant.native.groupBy(*self._keys).agg(*agg_columns)
+            if (agg_columns := list(self._evaluate_exprs(exprs)))
+            else self.compliant.native.select(*self._keys).dropDuplicates()
+        )
+
+        return self.compliant._with_native(result).rename(
+            dict(zip(self._keys, self._output_key_names))
+        )