feat: Support arithmetic between Series with dtype list

crates/polars-core/src/series/arithmetic/list_borrowed.rs

@@ -0,0 +1,177 @@
+//! Allow arithmetic operations for ListChunked.
+
+use super::*;
+use crate::chunked_array::builder::AnonymousListBuilder;
+
+/// Given an ArrayRef with some primitive values, wrap it in list(s) until it
+/// matches the requested shape.
+fn reshape_list_based_on(data: &ArrayRef, shape: &ArrayRef) -> ArrayRef {
+    if let Some(list_chunk) = shape.as_any().downcast_ref::<LargeListArray>() {
+        let result = LargeListArray::new(
+            list_chunk.dtype().clone(),
+            list_chunk.offsets().clone(),
+            reshape_list_based_on(data, list_chunk.values()),
+            list_chunk.validity().cloned(),
+        );
+        Box::new(result)
+    } else {
+        data.clone()
+    }
+}
+
+/// Given an ArrayRef, return true if it's a LargeListArrays and it has one or
+/// more nulls.
+fn does_list_have_nulls(data: &ArrayRef) -> bool {
+    if let Some(list_chunk) = data.as_any().downcast_ref::<LargeListArray>() {
+        if list_chunk
+            .validity()
+            .map(|bitmap| bitmap.unset_bits() > 0)
+            .unwrap_or(false)
+        {
+            true
+        } else {
+            does_list_have_nulls(list_chunk.values())
+        }
+    } else {
+        false
+    }
+}
+
+/// Return whether the left and right have the same shape. We assume neither has
+/// any nulls, recursively.
+fn lists_same_shapes(left: &ArrayRef, right: &ArrayRef) -> bool {
+    debug_assert!(!does_list_have_nulls(left));
+    debug_assert!(!does_list_have_nulls(right));
+    let left_as_list = left.as_any().downcast_ref::<LargeListArray>();
+    let right_as_list = right.as_any().downcast_ref::<LargeListArray>();
+    match (left_as_list, right_as_list) {
+        (Some(left), Some(right)) => {
+            left.offsets() == right.offsets() && lists_same_shapes(left.values(), right.values())
+        },
+        (None, None) => left.len() == right.len(),
+        _ => false,
+    }
+}
+
+impl ListChunked {
+    /// Helper function for NumOpsDispatchInner implementation for ListChunked.
+    ///
+    /// Run the given `op` on `self` and `rhs`.
+    fn arithm_helper(
+        &self,
+        rhs: &Series,
+        op: &dyn Fn(&Series, &Series) -> PolarsResult<Series>,
+        has_nulls: Option<bool>,
+    ) -> PolarsResult<Series> {
+        polars_ensure!(
+            self.len() == rhs.len(),
+            InvalidOperation: "can only do arithmetic operations on Series of the same size; got {} and {}",
+            self.len(),
+            rhs.len()
+        );
+
+        let mut has_nulls = has_nulls.unwrap_or(false);
+        if !has_nulls {
+            for chunk in self.chunks().iter() {
+                if does_list_have_nulls(chunk) {
+                    has_nulls = true;
+                    break;
+                }
+            }
+        }
+        if !has_nulls {
+            for chunk in rhs.chunks().iter() {
+                if does_list_have_nulls(chunk) {
+                    has_nulls = true;
+                    break;
+                }
+            }
+        }
+        if has_nulls {
+            // A slower implementation since we can't just add the underlying
+            // values Arrow arrays. Given nulls, the two values arrays might not
+            // line up the way we expect.
+            let mut result = AnonymousListBuilder::new(
+                self.name().clone(),
+                self.len(),
+                Some(self.inner_dtype().clone()),
+            );
+            let combined = self.amortized_iter().zip(rhs.list()?.amortized_iter()).map(|(a, b)| {
+                    let (Some(a_owner), Some(b_owner)) = (a, b) else {
+                        // Operations with nulls always result in nulls:
+                        return Ok(None);
+                    };
+                    let a = a_owner.as_ref();
+                    let b = b_owner.as_ref();
+                    polars_ensure!(
+                        a.len() == b.len(),
+                        InvalidOperation: "can only do arithmetic operations on lists of the same size; got {} and {}",
+                        a.len(),
+                        b.len()
+                    );
+                    let chunk_result = if let Ok(a_listchunked) = a.list() {
+                        // If `a` contains more lists, we're going to reach this
+                        // function recursively, and again have to decide whether to
+                        // use the fast path (no nulls) or slow path (there were
+                        // nulls). Since we know there were nulls, that means we
+                        // have to stick to the slow path, so pass that information
+                        // along.
+                        a_listchunked.arithm_helper(b, op, Some(true))
+                    } else {
+                        op(a, b)
+                    };
+                    chunk_result.map(Some)
+                }).collect::<PolarsResult<Vec<Option<Series>>>>()?;
+            for s in combined.iter() {
+                if let Some(s) = s {
+                    result.append_series(s)?;
+                } else {
+                    result.append_null();
+                }
+            }
+            return Ok(result.finish().into());
+        }
+        let l_rechunked = self.clone().rechunk().into_series();
+        let l_leaf_array = l_rechunked.get_leaf_array();
+        let r_leaf_array = rhs.rechunk().get_leaf_array();
+        polars_ensure!(
+            lists_same_shapes(&l_leaf_array.chunks()[0], &r_leaf_array.chunks()[0]),
+            InvalidOperation: "can only do arithmetic operations on lists of the same size"
+        );
+
+        let result = op(&l_leaf_array, &r_leaf_array)?;
+
+        // We now need to wrap the Arrow arrays with the metadata that turns
+        // them into lists:
+        // TODO is there a way to do this without cloning the underlying data?
+        let result_chunks = result.chunks();
+        assert_eq!(result_chunks.len(), 1);
+        let left_chunk = &l_rechunked.chunks()[0];
+        let result_chunk = reshape_list_based_on(&result_chunks[0], left_chunk);
+
+        unsafe {
+            let mut result =
+                ListChunked::new_with_dims(self.field.clone(), vec![result_chunk], 0, 0);
+            result.compute_len();
+            Ok(result.into())
+        }
+    }
+}
+
+impl NumOpsDispatchInner for ListType {
+    fn add_to(lhs: &ListChunked, rhs: &Series) -> PolarsResult<Series> {
+        lhs.arithm_helper(rhs, &|l, r| l.add_to(r), None)
+    }
+    fn subtract(lhs: &ListChunked, rhs: &Series) -> PolarsResult<Series> {
+        lhs.arithm_helper(rhs, &|l, r| l.subtract(r), None)
+    }
+    fn multiply(lhs: &ListChunked, rhs: &Series) -> PolarsResult<Series> {
+        lhs.arithm_helper(rhs, &|l, r| l.multiply(r), None)
+    }
+    fn divide(lhs: &ListChunked, rhs: &Series) -> PolarsResult<Series> {
+        lhs.arithm_helper(rhs, &|l, r| l.divide(r), None)
+    }
+    fn remainder(lhs: &ListChunked, rhs: &Series) -> PolarsResult<Series> {
+        lhs.arithm_helper(rhs, &|l, r| l.remainder(r), None)
+    }
+}

crates/polars-core/src/series/arithmetic/mod.rs

@@ -1,4 +1,5 @@
 mod borrowed;
+mod list_borrowed;
 mod owned;
 
 use std::borrow::Cow;

crates/polars-core/src/series/implementations/list.rs

@@ -43,6 +43,24 @@ impl private::PrivateSeries for SeriesWrap<ListChunked> {
     fn into_total_eq_inner<'a>(&'a self) -> Box<dyn TotalEqInner + 'a> {
         (&self.0).into_total_eq_inner()
     }
+
+    fn add_to(&self, rhs: &Series) -> PolarsResult<Series> {
+        self.0.add_to(rhs)
+    }
+
+    fn subtract(&self, rhs: &Series) -> PolarsResult<Series> {
+        self.0.subtract(rhs)
+    }
+
+    fn multiply(&self, rhs: &Series) -> PolarsResult<Series> {
+        self.0.multiply(rhs)
+    }
+    fn divide(&self, rhs: &Series) -> PolarsResult<Series> {
+        self.0.divide(rhs)
+    }
+    fn remainder(&self, rhs: &Series) -> PolarsResult<Series> {
+        self.0.remainder(rhs)
+    }
 }
 
 impl SeriesTrait for SeriesWrap<ListChunked> {

crates/polars-expr/src/expressions/binary.rs

@@ -75,6 +75,11 @@ pub fn apply_operator(left: &Series, right: &Series, op: Operator) -> PolarsResu
                 let right_dt = right.dtype().cast_leaf(Float64);
                 left.cast(&left_dt)? / right.cast(&right_dt)?
             },
+            dt @ List(_) => {
+                let left_dt = dt.cast_leaf(Float64);
+                let right_dt = right.dtype().cast_leaf(Float64);
+                left.cast(&left_dt)? / right.cast(&right_dt)?
+            },
             _ => {
                 if right.dtype().is_temporal() {
                     return left / right;

crates/polars-expr/src/expressions/cast.rs

@@ -13,7 +13,14 @@ pub struct CastExpr {
 
 impl CastExpr {
     fn finish(&self, input: &Series) -> PolarsResult<Series> {
-        input.cast_with_options(&self.dtype, self.options)
+        let dtype = if matches!(input.dtype(), DataType::List(_)) && !self.dtype.is_nested() {
+            // Necessary for expressions that e.g. add UInt8 to List[Int64] to
+            // work.
+            &input.dtype().cast_leaf(self.dtype.clone())
+        } else {
+            &self.dtype
+        };
+        input.cast_with_options(dtype, self.options)
     }
 }
 

py-polars/polars/series/series.py

@@ -1058,6 +1058,22 @@ def __sub__(self, other: Any) -> Self | Expr:
             return F.lit(self) - other
         return self._arithmetic(other, "sub", "sub_<>")
 
+    def _recursive_cast_to_dtype(self, leaf_dtype: PolarsDataType) -> Series:
+        """
+        Convert leaf dtype the to given primitive datatype.
+
+        This is equivalent to logic in DataType::cast_leaf() in Rust.
+        """
+
+        def convert_to_primitive(dtype: PolarsDataType) -> PolarsDataType:
+            if isinstance(dtype, Array):
+                return Array(convert_to_primitive(dtype.inner), shape=dtype.shape)
+            if isinstance(dtype, List):
+                return List(convert_to_primitive(dtype.inner))
+            return leaf_dtype
+
+        return self.cast(convert_to_primitive(self.dtype))
+
     @overload
     def __truediv__(self, other: Expr) -> Expr: ...
 
@@ -1073,9 +1089,11 @@ def __truediv__(self, other: Any) -> Series | Expr:
 
         # this branch is exactly the floordiv function without rounding the floats
         if self.dtype.is_float() or self.dtype == Decimal:
-            return self._arithmetic(other, "div", "div_<>")
+            as_float = self
+        else:
+            as_float = self._recursive_cast_to_dtype(Float64())
 
-        return self.cast(Float64) / other
+        return as_float._arithmetic(other, "div", "div_<>")
 
     @overload
     def __floordiv__(self, other: Expr) -> Expr: ...