fix: Fix order observability of group-by-dyn

crates/polars-plan/src/plans/optimizer/set_order.rs

@@ -123,11 +123,6 @@ pub(super) fn set_order_flags(
                 ..
             } => {
                 debug_assert!(options.slice.is_none());
-                if !maintain_order_above && *maintain_order {
-                    *maintain_order = false;
-                    continue;
-                }
-
                 if apply.is_some()
                     || *maintain_order
                     || options.is_rolling()
@@ -136,6 +131,11 @@ pub(super) fn set_order_flags(
                     maintain_order_above = true;
                     continue;
                 }
+                if !maintain_order_above && *maintain_order {
+                    *maintain_order = false;
+                    continue;
+                }
+
                 if all_elementwise(keys, expr_arena)
                     && all_order_independent(aggs, expr_arena, Context::Aggregation)
                 {

py-polars/tests/unit/lazyframe/optimizations.py

@@ -4,33 +4,6 @@
 from polars.testing import assert_frame_equal
 
 
-def test_remove_double_sort() -> None:
-    assert (
-        pl.LazyFrame({"a": [1, 2, 3, 3]}).sort("a").sort("a").explain().count("SORT")
-        == 1
-    )
-
-
-def test_double_sort_maintain_order_18558() -> None:
-    df = pl.DataFrame(
-        {
-            "col1": [1, 2, 2, 4, 5, 6],
-            "col2": [2, 2, 0, 0, 2, None],
-        }
-    )
-
-    lf = df.lazy().sort("col2").sort("col1", maintain_order=True)
-
-    expect = pl.DataFrame(
-        [
-            pl.Series("col1", [1, 2, 2, 4, 5, 6], dtype=pl.Int64),
-            pl.Series("col2", [2, 0, 2, 0, 2, None], dtype=pl.Int64),
-        ]
-    )
-
-    assert_frame_equal(lf.collect(), expect)
-
-
 def test_fast_count_alias_18581() -> None:
     f = io.BytesIO()
     f.write(b"a,b,c\n1,2,3\n4,5,6")
@@ -40,13 +13,3 @@ def test_fast_count_alias_18581() -> None:
     df = pl.scan_csv(f).select(pl.len().alias("weird_name")).collect()
 
     assert_frame_equal(pl.DataFrame({"weird_name": 2}), df)
-
-
-def test_order_observability() -> None:
-    q = pl.LazyFrame({"a": [1, 2, 3], "b": [1, 2, 3]}).sort("a")
-
-    assert "SORT" not in q.group_by("a").sum().explain(_check_order=True)
-    assert "SORT" not in q.group_by("a").min().explain(_check_order=True)
-    assert "SORT" not in q.group_by("a").max().explain(_check_order=True)
-    assert "SORT" in q.group_by("a").last().explain(_check_order=True)
-    assert "SORT" in q.group_by("a").first().explain(_check_order=True)

py-polars/tests/unit/lazyframe/test_order_observability.py

@@ -0,0 +1,53 @@
+import polars as pl
+from polars.testing import assert_frame_equal
+
+
+def test_order_observability() -> None:
+    q = pl.LazyFrame({"a": [1, 2, 3], "b": [1, 2, 3]}).sort("a")
+
+    assert "SORT" not in q.group_by("a").sum().explain(_check_order=True)
+    assert "SORT" not in q.group_by("a").min().explain(_check_order=True)
+    assert "SORT" not in q.group_by("a").max().explain(_check_order=True)
+    assert "SORT" in q.group_by("a").last().explain(_check_order=True)
+    assert "SORT" in q.group_by("a").first().explain(_check_order=True)
+
+
+def test_order_observability_group_by_dynamic() -> None:
+    assert (
+        pl.LazyFrame(
+            {"REGIONID": [1, 23, 4], "INTERVAL_END": [32, 43, 12], "POWER": [12, 3, 1]}
+        )
+        .sort("REGIONID", "INTERVAL_END")
+        .group_by_dynamic(index_column="INTERVAL_END", every="1i", group_by="REGIONID")
+        .agg(pl.col("POWER").sum())
+        .sort("POWER")
+        .head()
+        .explain()
+    ).count("SORT") == 2
+
+
+def test_remove_double_sort() -> None:
+    assert (
+        pl.LazyFrame({"a": [1, 2, 3, 3]}).sort("a").sort("a").explain().count("SORT")
+        == 1
+    )
+
+
+def test_double_sort_maintain_order_18558() -> None:
+    df = pl.DataFrame(
+        {
+            "col1": [1, 2, 2, 4, 5, 6],
+            "col2": [2, 2, 0, 0, 2, None],
+        }
+    )
+
+    lf = df.lazy().sort("col2").sort("col1", maintain_order=True)
+
+    expect = pl.DataFrame(
+        [
+            pl.Series("col1", [1, 2, 2, 4, 5, 6], dtype=pl.Int64),
+            pl.Series("col2", [2, 0, 2, 0, 2, None], dtype=pl.Int64),
+        ]
+    )
+
+    assert_frame_equal(lf.collect(), expect)