feat: check if by column is sorted, rather than just checking sorte…

…d flag, in `group_by_dynamic`, `upsample`, and `rolling`

crates/polars-core/src/utils/series.rs

@@ -1,6 +1,5 @@
 use crate::prelude::*;
 use crate::series::unstable::UnstableSeries;
-use crate::series::IsSorted;
 
 /// A utility that allocates an [`UnstableSeries`]. The applied function can then use that
 /// series container to save heap allocations and swap arrow arrays.
@@ -14,15 +13,6 @@ where
     f(&mut us)
 }
 
-pub fn ensure_sorted_arg(s: &Series, operation: &str) -> PolarsResult<()> {
-    polars_ensure!(!matches!(s.is_sorted_flag(), IsSorted::Not), InvalidOperation: "argument in operation '{}' is not explicitly sorted
-
-- If your data is ALREADY sorted, set the sorted flag with: '.set_sorted()'.
-- If your data is NOT sorted, sort the 'expr/series/column' first.
-    ", operation);
-    Ok(())
-}
-
 pub fn handle_casting_failures(input: &Series, output: &Series) -> PolarsResult<()> {
     let failure_mask = !input.is_null() & output.is_null();
     let failures = input.filter_threaded(&failure_mask, false)?;

crates/polars-ops/src/frame/join/asof/mod.rs

@@ -5,7 +5,6 @@ use std::borrow::Cow;
 use default::*;
 pub use groups::AsofJoinBy;
 use polars_core::prelude::*;
-use polars_core::utils::ensure_sorted_arg;
 #[cfg(feature = "serde")]
 use serde::{Deserialize, Serialize};
 use smartstring::alias::String as SmartString;
@@ -14,6 +13,7 @@ use smartstring::alias::String as SmartString;
 use super::_check_categorical_src;
 use super::{_finish_join, build_tables, prepare_bytes};
 use crate::frame::IntoDf;
+use crate::series::SeriesMethods;
 
 trait AsofJoinState<T>: Default {
     fn next<F: FnMut(IdxSize) -> Option<T>>(
@@ -185,8 +185,8 @@ fn check_asof_columns(
         a.dtype(), b.dtype()
     );
     if check_sorted {
-        ensure_sorted_arg(a, "asof_join")?;
-        ensure_sorted_arg(b, "asof_join")?;
+        a.ensure_sorted_arg("asof_join")?;
+        b.ensure_sorted_arg("asof_join")?;
     }
     Ok(())
 }

crates/polars-ops/src/series/ops/various.rs

@@ -51,6 +51,11 @@ pub trait SeriesMethods: SeriesSealed {
         }
     }
 
+    fn ensure_sorted_arg(&self, operation: &str) -> PolarsResult<()> {
+        polars_ensure!(self.is_sorted(Default::default())?, InvalidOperation: "argument in operation '{}' is not sorted, please sort the 'expr/series/column' first", operation);
+        Ok(())
+    }
+
     /// Checks if a [`Series`] is sorted. Tries to fail fast.
     fn is_sorted(&self, options: SortOptions) -> PolarsResult<bool> {
         let s = self.as_series();

crates/polars-time/src/group_by/dynamic.rs

@@ -3,9 +3,9 @@ use arrow::legacy::utils::CustomIterTools;
 use polars_core::export::rayon::prelude::*;
 use polars_core::prelude::*;
 use polars_core::series::IsSorted;
-use polars_core::utils::ensure_sorted_arg;
 use polars_core::utils::flatten::flatten_par;
 use polars_core::POOL;
+use polars_ops::series::SeriesMethods;
 use polars_utils::idx_vec::IdxVec;
 use polars_utils::slice::{GetSaferUnchecked, SortedSlice};
 #[cfg(feature = "serde")]
@@ -34,9 +34,6 @@ pub struct DynamicGroupOptions {
     pub include_boundaries: bool,
     pub closed_window: ClosedWindow,
     pub start_by: StartBy,
-    /// In cases sortedness cannot be checked by the sorted flag,
-    /// traverse the data to check sortedness.
-    pub check_sorted: bool,
 }
 
 impl Default for DynamicGroupOptions {
@@ -50,7 +47,6 @@ impl Default for DynamicGroupOptions {
             include_boundaries: false,
             closed_window: ClosedWindow::Left,
             start_by: Default::default(),
-            check_sorted: true,
         }
     }
 }
@@ -64,9 +60,6 @@ pub struct RollingGroupOptions {
     pub period: Duration,
     pub offset: Duration,
     pub closed_window: ClosedWindow,
-    /// In cases sortedness cannot be checked by the sorted flag,
-    /// traverse the data to check sortedness.
-    pub check_sorted: bool,
 }
 
 impl Default for RollingGroupOptions {
@@ -76,7 +69,6 @@ impl Default for RollingGroupOptions {
             period: Duration::new(1),
             offset: Duration::new(1),
             closed_window: ClosedWindow::Left,
-            check_sorted: true,
         }
     }
 }
@@ -133,10 +125,10 @@ impl Wrap<&DataFrame> {
                         "rolling window period should be strictly positive",
         );
         let time = self.0.column(&options.index_column)?.clone();
-        if group_by.is_empty() && options.check_sorted {
+        if group_by.is_empty() {
             // If by is given, the column must be sorted in the 'by' arg, which we can not check now
             // this will be checked when the groups are materialized.
-            ensure_sorted_arg(&time, "rolling")?;
+            time.ensure_sorted_arg("rolling")?;
         }
         let time_type = time.dtype();
 
@@ -202,10 +194,10 @@ impl Wrap<&DataFrame> {
         options: &DynamicGroupOptions,
     ) -> PolarsResult<(Series, Vec<Series>, GroupsProxy)> {
         let time = self.0.column(&options.index_column)?.rechunk();
-        if group_by.is_empty() && options.check_sorted {
+        if group_by.is_empty() {
             // If by is given, the column must be sorted in the 'by' arg, which we can not check now
             // this will be checked when the groups are materialized.
-            ensure_sorted_arg(&time, "group_by_dynamic")?;
+            time.ensure_sorted_arg("group_by_dynamic")?;
         }
         let time_type = time.dtype();
 
@@ -349,9 +341,7 @@ impl Wrap<&DataFrame> {
                                 let dt = unsafe { dt.take_unchecked(base_g.1) };
                                 let vals = dt.downcast_iter().next().unwrap();
                                 let ts = vals.values().as_slice();
-                                if options.check_sorted
-                                    && !matches!(dt.is_sorted_flag(), IsSorted::Ascending)
-                                {
+                                if !matches!(dt.is_sorted_flag(), IsSorted::Ascending) {
                                     check_sortedness_slice(ts)?
                                 }
                                 let (sub_groups, lower, upper) = group_by_windows(
@@ -428,9 +418,7 @@ impl Wrap<&DataFrame> {
                                 let dt = unsafe { dt.take_unchecked(base_g.1) };
                                 let vals = dt.downcast_iter().next().unwrap();
                                 let ts = vals.values().as_slice();
-                                if options.check_sorted
-                                    && !matches!(dt.is_sorted_flag(), IsSorted::Ascending)
-                                {
+                                if !matches!(dt.is_sorted_flag(), IsSorted::Ascending) {
                                     check_sortedness_slice(ts)?
                                 }
                                 let (sub_groups, _, _) = group_by_windows(
@@ -573,9 +561,7 @@ impl Wrap<&DataFrame> {
                             let dt = unsafe { dt_local.take_unchecked(base_g.1) };
                             let vals = dt.downcast_iter().next().unwrap();
                             let ts = vals.values().as_slice();
-                            if options.check_sorted
-                                && !matches!(dt.is_sorted_flag(), IsSorted::Ascending)
-                            {
+                            if !matches!(dt.is_sorted_flag(), IsSorted::Ascending) {
                                 check_sortedness_slice(ts)?
                             }
 
@@ -716,7 +702,6 @@ mod test {
                         period: Duration::parse("2d"),
                         offset: Duration::parse("-2d"),
                         closed_window: ClosedWindow::Right,
-                        ..Default::default()
                     },
                 )
                 .unwrap();
@@ -764,7 +749,6 @@ mod test {
                     period: Duration::parse("2d"),
                     offset: Duration::parse("-2d"),
                     closed_window: ClosedWindow::Right,
-                    ..Default::default()
                 },
             )
             .unwrap();
@@ -848,7 +832,6 @@ mod test {
                     include_boundaries: true,
                     closed_window: ClosedWindow::Both,
                     start_by: Default::default(),
-                    ..Default::default()
                 },
             )
             .unwrap();
@@ -969,7 +952,6 @@ mod test {
                     include_boundaries: true,
                     closed_window: ClosedWindow::Both,
                     start_by: Default::default(),
-                    ..Default::default()
                 },
             )
             .unwrap();

crates/polars-time/src/upsample.rs

@@ -1,8 +1,8 @@
 #[cfg(feature = "timezones")]
 use polars_core::chunked_array::temporal::parse_time_zone;
 use polars_core::prelude::*;
-use polars_core::utils::ensure_sorted_arg;
 use polars_ops::prelude::*;
+use polars_ops::series::SeriesMethods;
 
 use crate::prelude::*;
 
@@ -128,7 +128,7 @@ fn upsample_impl(
     stable: bool,
 ) -> PolarsResult<DataFrame> {
     let s = source.column(index_column)?;
-    ensure_sorted_arg(s, "upsample")?;
+    s.ensure_sorted_arg("upsample")?;
     let time_type = s.dtype();
     if matches!(time_type, DataType::Date) {
         let mut df = source.clone();

py-polars/polars/dataframe/frame.py

@@ -5472,7 +5472,7 @@ def rolling(
         offset: str | timedelta | None = None,
         closed: ClosedInterval = "right",
         group_by: IntoExpr | Iterable[IntoExpr] | None = None,
-        check_sorted: bool = True,
+        check_sorted: bool | None = None,
     ) -> RollingGroupBy:
         """
         Create rolling groups based on a temporal or integer column.
@@ -5547,6 +5547,10 @@ def rolling(
             data within the groups is sorted, you can set this to `False`.
             Doing so incorrectly will lead to incorrect output
 
+            .. deprecated:: 0.20.31
+                Sortedness is now verified in a quick manner, you can safely remove
+                this argument.
+
         Returns
         -------
         RollingGroupBy
@@ -5622,7 +5626,7 @@ def group_by_dynamic(
         label: Label = "left",
         group_by: IntoExpr | Iterable[IntoExpr] | None = None,
         start_by: StartBy = "window",
-        check_sorted: bool = True,
+        check_sorted: bool | None = None,
     ) -> DynamicGroupBy:
         """
         Group based on a time value (or index value of type Int32, Int64).
@@ -5707,6 +5711,10 @@ def group_by_dynamic(
             data within the groups is sorted, you can set this to `False`.
             Doing so incorrectly will lead to incorrect output
 
+            .. deprecated:: 0.20.31
+                Sortedness is now verified in a quick manner, you can safely remove
+                this argument.
+
         Returns
         -------
         DynamicGroupBy
@@ -10733,7 +10741,7 @@ def groupby_rolling(
         offset: str | timedelta | None = None,
         closed: ClosedInterval = "right",
         by: IntoExpr | Iterable[IntoExpr] | None = None,
-        check_sorted: bool = True,
+        check_sorted: bool | None = None,
     ) -> RollingGroupBy:
         """
         Create rolling groups based on a time, Int32, or Int64 column.
@@ -10787,7 +10795,7 @@ def group_by_rolling(
         offset: str | timedelta | None = None,
         closed: ClosedInterval = "right",
         by: IntoExpr | Iterable[IntoExpr] | None = None,
-        check_sorted: bool = True,
+        check_sorted: bool | None = None,
     ) -> RollingGroupBy:
         """
         Create rolling groups based on a time, Int32, or Int64 column.
@@ -10845,7 +10853,7 @@ def groupby_dynamic(
         closed: ClosedInterval = "left",
         by: IntoExpr | Iterable[IntoExpr] | None = None,
         start_by: StartBy = "window",
-        check_sorted: bool = True,
+        check_sorted: bool | None = None,
     ) -> DynamicGroupBy:
         """
         Group based on a time value (or index value of type Int32, Int64).

py-polars/polars/dataframe/group_by.py

@@ -806,8 +806,13 @@ def __init__(
         offset: str | timedelta | None,
         closed: ClosedInterval,
         group_by: IntoExpr | Iterable[IntoExpr] | None,
-        check_sorted: bool,
+        check_sorted: bool | None = None,
     ):
+        if check_sorted is not None:
+            issue_deprecation_warning(
+                "`check_sorted` is now deprecated in `rolling`, you can safely remove this argument.",
+                version="0.20.31",
+            )
         period = parse_as_duration_string(period)
         offset = parse_as_duration_string(offset)
 
@@ -817,7 +822,6 @@ def __init__(
         self.offset = offset
         self.closed = closed
         self.group_by = group_by
-        self.check_sorted = check_sorted
 
     def __iter__(self) -> Self:
         temp_col = "__POLARS_GB_GROUP_INDICES"
@@ -829,7 +833,6 @@ def __iter__(self) -> Self:
                 offset=self.offset,
                 closed=self.closed,
                 group_by=self.group_by,
-                check_sorted=self.check_sorted,
             )
             .agg(F.first().agg_groups().alias(temp_col))
             .collect(no_optimization=True)
@@ -888,7 +891,6 @@ def agg(
                 offset=self.offset,
                 closed=self.closed,
                 group_by=self.group_by,
-                check_sorted=self.check_sorted,
             )
             .agg(*aggs, **named_aggs)
             .collect(no_optimization=True)
@@ -931,7 +933,6 @@ def map_groups(
                 offset=self.offset,
                 closed=self.closed,
                 group_by=self.group_by,
-                check_sorted=self.check_sorted,
             )
             .map_groups(function, schema)
             .collect(no_optimization=True)
@@ -983,8 +984,13 @@ def __init__(
         label: Label,
         group_by: IntoExpr | Iterable[IntoExpr] | None,
         start_by: StartBy,
-        check_sorted: bool,
+        check_sorted: bool | None = None,
     ):
+        if check_sorted is not None:
+            issue_deprecation_warning(
+                "`check_sorted` is now deprecated in `rolling`, you can safely remove this argument.",
+                version="0.20.31",
+            )
         every = parse_as_duration_string(every)
         period = parse_as_duration_string(period)
         offset = parse_as_duration_string(offset)
@@ -1000,7 +1006,6 @@ def __init__(
         self.closed = closed
         self.group_by = group_by
         self.start_by = start_by
-        self.check_sorted = check_sorted
 
     def __iter__(self) -> Self:
         temp_col = "__POLARS_GB_GROUP_INDICES"
@@ -1017,7 +1022,6 @@ def __iter__(self) -> Self:
                 closed=self.closed,
                 group_by=self.group_by,
                 start_by=self.start_by,
-                check_sorted=self.check_sorted,
             )
             .agg(F.first().agg_groups().alias(temp_col))
             .collect(no_optimization=True)
@@ -1081,7 +1085,6 @@ def agg(
                 closed=self.closed,
                 group_by=self.group_by,
                 start_by=self.start_by,
-                check_sorted=self.check_sorted,
             )
             .agg(*aggs, **named_aggs)
             .collect(no_optimization=True)
@@ -1128,7 +1131,6 @@ def map_groups(
                 closed=self.closed,
                 group_by=self.group_by,
                 start_by=self.start_by,
-                check_sorted=self.check_sorted,
             )
             .map_groups(function, schema)
             .collect(no_optimization=True)

py-polars/polars/expr/expr.py

@@ -3771,7 +3771,7 @@ def rolling(
         period: str | timedelta,
         offset: str | timedelta | None = None,
         closed: ClosedInterval = "right",
-        check_sorted: bool = True,
+        check_sorted: bool | None = None,
     ) -> Self:
         """
         Create rolling groups based on a temporal or integer column.
@@ -3875,7 +3875,7 @@ def rolling(
         offset = parse_as_duration_string(offset)
 
         return self._from_pyexpr(
-            self._pyexpr.rolling(index_column, period, offset, closed, check_sorted)
+            self._pyexpr.rolling(index_column, period, offset, closed)
         )
 
     def is_unique(self) -> Self: