polars_core/series/arithmetic/

borrowed.rs

use super::*;
use crate::utils::align_chunks_binary;

pub trait NumOpsDispatchInner: PolarsDataType + Sized {
    fn subtract(lhs: &ChunkedArray<Self>, rhs: &Series) -> PolarsResult<Series> {
        polars_bail!(opq = sub, lhs.dtype(), rhs.dtype());
    }
    fn add_to(lhs: &ChunkedArray<Self>, rhs: &Series) -> PolarsResult<Series> {
        polars_bail!(opq = add, lhs.dtype(), rhs.dtype());
    }
    fn multiply(lhs: &ChunkedArray<Self>, rhs: &Series) -> PolarsResult<Series> {
        polars_bail!(opq = mul, lhs.dtype(), rhs.dtype());
    }
    fn divide(lhs: &ChunkedArray<Self>, rhs: &Series) -> PolarsResult<Series> {
        polars_bail!(opq = div, lhs.dtype(), rhs.dtype());
    }
    fn remainder(lhs: &ChunkedArray<Self>, rhs: &Series) -> PolarsResult<Series> {
        polars_bail!(opq = rem, lhs.dtype(), rhs.dtype());
    }
}

pub trait NumOpsDispatch {
    fn subtract(&self, rhs: &Series) -> PolarsResult<Series>;
    fn add_to(&self, rhs: &Series) -> PolarsResult<Series>;
    fn multiply(&self, rhs: &Series) -> PolarsResult<Series>;
    fn divide(&self, rhs: &Series) -> PolarsResult<Series>;
    fn remainder(&self, rhs: &Series) -> PolarsResult<Series>;
}

impl<T: NumOpsDispatchInner> NumOpsDispatch for ChunkedArray<T> {
    fn subtract(&self, rhs: &Series) -> PolarsResult<Series> {
        T::subtract(self, rhs)
    }
    fn add_to(&self, rhs: &Series) -> PolarsResult<Series> {
        T::add_to(self, rhs)
    }
    fn multiply(&self, rhs: &Series) -> PolarsResult<Series> {
        T::multiply(self, rhs)
    }
    fn divide(&self, rhs: &Series) -> PolarsResult<Series> {
        T::divide(self, rhs)
    }
    fn remainder(&self, rhs: &Series) -> PolarsResult<Series> {
        T::remainder(self, rhs)
    }
}

impl<T> NumOpsDispatchInner for T
where
    T: PolarsNumericType,
    ChunkedArray<T>: IntoSeries,
{
    fn subtract(lhs: &ChunkedArray<T>, rhs: &Series) -> PolarsResult<Series> {
        // SAFETY:
        // There will be UB if a ChunkedArray is alive with the wrong datatype.
        // we now only create the potentially wrong dtype for a short time.
        // Note that the physical type correctness is checked!
        // The ChunkedArray with the wrong dtype is dropped after this operation
        let rhs = unsafe { lhs.unpack_series_matching_physical_type(rhs) };
        let out = lhs - rhs;
        Ok(out.into_series())
    }
    fn add_to(lhs: &ChunkedArray<T>, rhs: &Series) -> PolarsResult<Series> {
        // SAFETY:
        // see subtract
        let rhs = unsafe { lhs.unpack_series_matching_physical_type(rhs) };
        let out = lhs + rhs;
        Ok(out.into_series())
    }
    fn multiply(lhs: &ChunkedArray<T>, rhs: &Series) -> PolarsResult<Series> {
        // SAFETY:
        // see subtract
        let rhs = unsafe { lhs.unpack_series_matching_physical_type(rhs) };
        let out = lhs * rhs;
        Ok(out.into_series())
    }
    fn divide(lhs: &ChunkedArray<T>, rhs: &Series) -> PolarsResult<Series> {
        // SAFETY:
        // see subtract
        let rhs = unsafe { lhs.unpack_series_matching_physical_type(rhs) };
        let out = lhs / rhs;
        Ok(out.into_series())
    }
    fn remainder(lhs: &ChunkedArray<T>, rhs: &Series) -> PolarsResult<Series> {
        // SAFETY:
        // see subtract
        let rhs = unsafe { lhs.unpack_series_matching_physical_type(rhs) };
        let out = lhs % rhs;
        Ok(out.into_series())
    }
}

impl NumOpsDispatchInner for StringType {
    fn add_to(lhs: &StringChunked, rhs: &Series) -> PolarsResult<Series> {
        let rhs = lhs.unpack_series_matching_type(rhs)?;
        let out = lhs + rhs;
        Ok(out.into_series())
    }
}

impl NumOpsDispatchInner for BinaryType {
    fn add_to(lhs: &BinaryChunked, rhs: &Series) -> PolarsResult<Series> {
        let rhs = lhs.unpack_series_matching_type(rhs)?;
        let out = lhs + rhs;
        Ok(out.into_series())
    }
}

impl NumOpsDispatchInner for BooleanType {
    fn add_to(lhs: &BooleanChunked, rhs: &Series) -> PolarsResult<Series> {
        let rhs = lhs.unpack_series_matching_type(rhs)?;
        let out = lhs + rhs;
        Ok(out.into_series())
    }
}

#[cfg(feature = "dtype-array")]
fn array_shape(dt: &DataType, infer: bool) -> Vec<ReshapeDimension> {
    fn inner(dt: &DataType, buf: &mut Vec<ReshapeDimension>) {
        if let DataType::Array(_, size) = dt {
            buf.push(ReshapeDimension::Specified(
                Dimension::try_from(*size as i64).unwrap(),
            ))
        }
    }

    let mut buf = vec![];
    if infer {
        buf.push(ReshapeDimension::Infer)
    }
    inner(dt, &mut buf);
    buf
}

#[cfg(feature = "dtype-array")]
fn broadcast_array(lhs: &ArrayChunked, rhs: &Series) -> PolarsResult<(ArrayChunked, Series)> {
    let out = match (lhs.len(), rhs.len()) {
        (1, _) => (lhs.new_from_index(0, rhs.len()), rhs.clone()),
        (_, 1) => {
            // Numeric scalars will be broadcasted implicitly without intermediate allocation.
            if rhs.dtype().is_numeric() {
                (lhs.clone(), rhs.clone())
            } else {
                (lhs.clone(), rhs.new_from_index(0, lhs.len()))
            }
        },
        (a, b) if a == b => (lhs.clone(), rhs.clone()),
        _ => {
            polars_bail!(
                InvalidOperation:
                "can only do arithmetic of arrays of the same type and shape; got {} and {}",
                lhs.dtype(), rhs.dtype()
            )
        },
    };
    Ok(out)
}

#[cfg(feature = "dtype-array")]
impl ArrayChunked {
    fn arithm_helper(
        &self,
        rhs: &Series,
        op: &dyn Fn(Series, Series) -> PolarsResult<Series>,
    ) -> PolarsResult<Series> {
        let (lhs, rhs) = broadcast_array(self, rhs)?;

        let l_leaf_array = lhs.clone().into_series().get_leaf_array();
        let shape = array_shape(lhs.dtype(), true);

        let r_leaf_array = if rhs.dtype().is_numeric() && rhs.len() == 1 {
            rhs.clone()
        } else {
            polars_ensure!(lhs.dtype() == rhs.dtype(), InvalidOperation: "can only do arithmetic of arrays of the same type and shape; got {} and {}", self.dtype(), rhs.dtype());
            rhs.get_leaf_array()
        };

        let out = op(l_leaf_array, r_leaf_array)?;
        out.reshape_array(&shape)
    }
}

#[cfg(feature = "dtype-array")]
impl NumOpsDispatchInner for FixedSizeListType {
    fn add_to(lhs: &ArrayChunked, rhs: &Series) -> PolarsResult<Series> {
        lhs.arithm_helper(rhs, &|l, r| l.add_to(&r))
    }
    fn subtract(lhs: &ArrayChunked, rhs: &Series) -> PolarsResult<Series> {
        lhs.arithm_helper(rhs, &|l, r| l.subtract(&r))
    }
    fn multiply(lhs: &ArrayChunked, rhs: &Series) -> PolarsResult<Series> {
        lhs.arithm_helper(rhs, &|l, r| l.multiply(&r))
    }
    fn divide(lhs: &ArrayChunked, rhs: &Series) -> PolarsResult<Series> {
        lhs.arithm_helper(rhs, &|l, r| l.divide(&r))
    }
    fn remainder(lhs: &ArrayChunked, rhs: &Series) -> PolarsResult<Series> {
        lhs.arithm_helper(rhs, &|l, r| l.remainder(&r))
    }
}

#[cfg(feature = "checked_arithmetic")]
pub mod checked {
    use num_traits::{CheckedDiv, One, ToPrimitive, Zero};

    use super::*;

    pub trait NumOpsDispatchCheckedInner: PolarsDataType + Sized {
        /// Checked integer division. Computes self / rhs, returning None if rhs == 0 or the division results in overflow.
        fn checked_div(lhs: &ChunkedArray<Self>, rhs: &Series) -> PolarsResult<Series> {
            polars_bail!(opq = checked_div, lhs.dtype(), rhs.dtype());
        }
        fn checked_div_num<T: ToPrimitive>(
            lhs: &ChunkedArray<Self>,
            _rhs: T,
        ) -> PolarsResult<Series> {
            polars_bail!(opq = checked_div_num, lhs.dtype(), Self::get_dtype());
        }
    }

    pub trait NumOpsDispatchChecked {
        /// Checked integer division. Computes self / rhs, returning None if rhs == 0 or the division results in overflow.
        fn checked_div(&self, rhs: &Series) -> PolarsResult<Series>;
        fn checked_div_num<T: ToPrimitive>(&self, _rhs: T) -> PolarsResult<Series>;
    }

    impl<S: NumOpsDispatchCheckedInner> NumOpsDispatchChecked for ChunkedArray<S> {
        fn checked_div(&self, rhs: &Series) -> PolarsResult<Series> {
            S::checked_div(self, rhs)
        }
        fn checked_div_num<T: ToPrimitive>(&self, rhs: T) -> PolarsResult<Series> {
            S::checked_div_num(self, rhs)
        }
    }

    impl<T> NumOpsDispatchCheckedInner for T
    where
        T: PolarsIntegerType,
        T::Native: CheckedDiv<Output = T::Native> + CheckedDiv<Output = T::Native> + Zero + One,
        ChunkedArray<T>: IntoSeries,
    {
        fn checked_div(lhs: &ChunkedArray<T>, rhs: &Series) -> PolarsResult<Series> {
            // SAFETY:
            // There will be UB if a ChunkedArray is alive with the wrong datatype.
            // we now only create the potentially wrong dtype for a short time.
            // Note that the physical type correctness is checked!
            // The ChunkedArray with the wrong dtype is dropped after this operation
            let rhs = unsafe { lhs.unpack_series_matching_physical_type(rhs) };

            Ok(
                arity::binary_elementwise(lhs, rhs, |opt_l, opt_r| match (opt_l, opt_r) {
                    (Some(l), Some(r)) => l.checked_div(&r),
                    _ => None,
                })
                .into_series(),
            )
        }
    }

    impl NumOpsDispatchCheckedInner for Float32Type {
        fn checked_div(lhs: &Float32Chunked, rhs: &Series) -> PolarsResult<Series> {
            // SAFETY:
            // see check_div for chunkedarray<T>
            let rhs = unsafe { lhs.unpack_series_matching_physical_type(rhs) };

            let ca: Float32Chunked =
                arity::binary_elementwise(lhs, rhs, |opt_l, opt_r| match (opt_l, opt_r) {
                    (Some(l), Some(r)) => {
                        if r.is_zero() {
                            None
                        } else {
                            Some(l / r)
                        }
                    },
                    _ => None,
                });
            Ok(ca.into_series())
        }
    }

    impl NumOpsDispatchCheckedInner for Float64Type {
        fn checked_div(lhs: &Float64Chunked, rhs: &Series) -> PolarsResult<Series> {
            // SAFETY:
            // see check_div
            let rhs = unsafe { lhs.unpack_series_matching_physical_type(rhs) };

            let ca: Float64Chunked =
                arity::binary_elementwise(lhs, rhs, |opt_l, opt_r| match (opt_l, opt_r) {
                    (Some(l), Some(r)) => {
                        if r.is_zero() {
                            None
                        } else {
                            Some(l / r)
                        }
                    },
                    _ => None,
                });
            Ok(ca.into_series())
        }
    }

    impl NumOpsDispatchChecked for Series {
        fn checked_div(&self, rhs: &Series) -> PolarsResult<Series> {
            let (lhs, rhs) = coerce_lhs_rhs(self, rhs).expect("cannot coerce datatypes");
            lhs.as_ref().as_ref().checked_div(rhs.as_ref())
        }

        fn checked_div_num<T: ToPrimitive>(&self, rhs: T) -> PolarsResult<Series> {
            use DataType::*;
            let s = self.to_physical_repr();

            let out = match s.dtype() {
                #[cfg(feature = "dtype-u8")]
                UInt8 => s
                    .u8()
                    .unwrap()
                    .apply(|opt_v| opt_v.and_then(|v| v.checked_div(rhs.to_u8().unwrap())))
                    .into_series(),
                #[cfg(feature = "dtype-i8")]
                Int8 => s
                    .i8()
                    .unwrap()
                    .apply(|opt_v| opt_v.and_then(|v| v.checked_div(rhs.to_i8().unwrap())))
                    .into_series(),
                #[cfg(feature = "dtype-i16")]
                Int16 => s
                    .i16()
                    .unwrap()
                    .apply(|opt_v| opt_v.and_then(|v| v.checked_div(rhs.to_i16().unwrap())))
                    .into_series(),
                #[cfg(feature = "dtype-u16")]
                UInt16 => s
                    .u16()
                    .unwrap()
                    .apply(|opt_v| opt_v.and_then(|v| v.checked_div(rhs.to_u16().unwrap())))
                    .into_series(),
                UInt32 => s
                    .u32()
                    .unwrap()
                    .apply(|opt_v| opt_v.and_then(|v| v.checked_div(rhs.to_u32().unwrap())))
                    .into_series(),
                Int32 => s
                    .i32()
                    .unwrap()
                    .apply(|opt_v| opt_v.and_then(|v| v.checked_div(rhs.to_i32().unwrap())))
                    .into_series(),
                UInt64 => s
                    .u64()
                    .unwrap()
                    .apply(|opt_v| opt_v.and_then(|v| v.checked_div(rhs.to_u64().unwrap())))
                    .into_series(),
                Int64 => s
                    .i64()
                    .unwrap()
                    .apply(|opt_v| opt_v.and_then(|v| v.checked_div(rhs.to_i64().unwrap())))
                    .into_series(),
                Float32 => s
                    .f32()
                    .unwrap()
                    .apply(|opt_v| {
                        opt_v.and_then(|v| {
                            let res = rhs.to_f32().unwrap();
                            if res.is_zero() {
                                None
                            } else {
                                Some(v / res)
                            }
                        })
                    })
                    .into_series(),
                Float64 => s
                    .f64()
                    .unwrap()
                    .apply(|opt_v| {
                        opt_v.and_then(|v| {
                            let res = rhs.to_f64().unwrap();
                            if res.is_zero() {
                                None
                            } else {
                                Some(v / res)
                            }
                        })
                    })
                    .into_series(),
                _ => panic!("dtype not yet supported in checked div"),
            };
            out.cast(self.dtype())
        }
    }
}

pub(crate) fn coerce_lhs_rhs<'a>(
    lhs: &'a Series,
    rhs: &'a Series,
) -> PolarsResult<(Cow<'a, Series>, Cow<'a, Series>)> {
    if let Some(result) = coerce_time_units(lhs, rhs) {
        return Ok(result);
    }
    let (left_dtype, right_dtype) = (lhs.dtype(), rhs.dtype());
    let leaf_super_dtype = match (left_dtype, right_dtype) {
        #[cfg(feature = "dtype-struct")]
        (DataType::Struct(_), DataType::Struct(_)) => {
            return Ok((Cow::Borrowed(lhs), Cow::Borrowed(rhs)))
        },
        _ => try_get_supertype(left_dtype.leaf_dtype(), right_dtype.leaf_dtype())?,
    };

    let mut new_left_dtype = left_dtype.cast_leaf(leaf_super_dtype.clone());
    let mut new_right_dtype = right_dtype.cast_leaf(leaf_super_dtype);

    // Cast List<->Array to List
    if (left_dtype.is_list() && right_dtype.is_array())
        || (left_dtype.is_array() && right_dtype.is_list())
    {
        new_left_dtype = try_get_supertype(&new_left_dtype, &new_right_dtype)?;
        new_right_dtype = new_left_dtype.clone();
    }

    let left = if lhs.dtype() == &new_left_dtype {
        Cow::Borrowed(lhs)
    } else {
        Cow::Owned(lhs.cast(&new_left_dtype)?)
    };
    let right = if rhs.dtype() == &new_right_dtype {
        Cow::Borrowed(rhs)
    } else {
        Cow::Owned(rhs.cast(&new_right_dtype)?)
    };
    Ok((left, right))
}

// Handle (Date | Datetime) +/- (Duration) | (Duration) +/- (Date | Datetime) | (Duration) +-
// (Duration)
// Time arithmetic is only implemented on the date / datetime so ensure that's on left

fn coerce_time_units<'a>(
    lhs: &'a Series,
    rhs: &'a Series,
) -> Option<(Cow<'a, Series>, Cow<'a, Series>)> {
    match (lhs.dtype(), rhs.dtype()) {
        (DataType::Datetime(lu, t), DataType::Duration(ru)) => {
            let units = get_time_units(lu, ru);
            let left = if *lu == units {
                Cow::Borrowed(lhs)
            } else {
                Cow::Owned(lhs.cast(&DataType::Datetime(units, t.clone())).ok()?)
            };
            let right = if *ru == units {
                Cow::Borrowed(rhs)
            } else {
                Cow::Owned(rhs.cast(&DataType::Duration(units)).ok()?)
            };
            Some((left, right))
        },
        // make sure to return Some here, so we don't cast to supertype.
        (DataType::Date, DataType::Duration(_)) => Some((Cow::Borrowed(lhs), Cow::Borrowed(rhs))),
        (DataType::Duration(lu), DataType::Duration(ru)) => {
            let units = get_time_units(lu, ru);
            let left = if *lu == units {
                Cow::Borrowed(lhs)
            } else {
                Cow::Owned(lhs.cast(&DataType::Duration(units)).ok()?)
            };
            let right = if *ru == units {
                Cow::Borrowed(rhs)
            } else {
                Cow::Owned(rhs.cast(&DataType::Duration(units)).ok()?)
            };
            Some((left, right))
        },
        // swap the order
        (DataType::Duration(_), DataType::Datetime(_, _))
        | (DataType::Duration(_), DataType::Date) => {
            let (right, left) = coerce_time_units(rhs, lhs)?;
            Some((left, right))
        },
        _ => None,
    }
}

#[cfg(feature = "dtype-struct")]
pub fn _struct_arithmetic<F: FnMut(&Series, &Series) -> PolarsResult<Series>>(
    s: &Series,
    rhs: &Series,
    mut func: F,
) -> PolarsResult<Series> {
    let s = s.struct_().unwrap();
    let rhs = rhs.struct_().unwrap();

    let s_fields = s.fields_as_series();
    let rhs_fields = rhs.fields_as_series();

    match (s_fields.len(), rhs_fields.len()) {
        (_, 1) => {
            let rhs = &rhs.fields_as_series()[0];
            Ok(s.try_apply_fields(|s| func(s, rhs))?.into_series())
        },
        (1, _) => {
            let s = &s.fields_as_series()[0];
            Ok(rhs.try_apply_fields(|rhs| func(s, rhs))?.into_series())
        },
        _ => {
            let (s, rhs) = align_chunks_binary(s, rhs);
            let mut s = s.into_owned();
            s.zip_outer_validity(rhs.as_ref());

            let mut rhs_iter = rhs.fields_as_series().into_iter();

            Ok(s.try_apply_fields(|s| match rhs_iter.next() {
                Some(rhs) => func(s, &rhs),
                None => Ok(s.clone()),
            })?
            .into_series())
        },
    }
}

fn check_lengths(a: &Series, b: &Series) -> PolarsResult<()> {
    match (a.len(), b.len()) {
        // broadcasting
        (1, _) | (_, 1) => Ok(()),
        // equal
        (a, b) if a == b => Ok(()),
        // unequal
        (a, b) => {
            polars_bail!(InvalidOperation: "cannot do arithmetic operation on series of different lengths: got {} and {}", a, b)
        },
    }
}

impl Add for &Series {
    type Output = PolarsResult<Series>;

    fn add(self, rhs: Self) -> Self::Output {
        check_lengths(self, rhs)?;
        match (self.dtype(), rhs.dtype()) {
            #[cfg(feature = "dtype-struct")]
            (DataType::Struct(_), DataType::Struct(_)) => {
                _struct_arithmetic(self, rhs, |a, b| a.add(b))
            },
            (DataType::List(_), _) | (_, DataType::List(_)) => {
                list_borrowed::NumericListOp::Add.execute(self, rhs)
            },
            _ => {
                let (lhs, rhs) = coerce_lhs_rhs(self, rhs)?;
                lhs.add_to(rhs.as_ref())
            },
        }
    }
}

impl Sub for &Series {
    type Output = PolarsResult<Series>;

    fn sub(self, rhs: Self) -> Self::Output {
        check_lengths(self, rhs)?;
        match (self.dtype(), rhs.dtype()) {
            #[cfg(feature = "dtype-struct")]
            (DataType::Struct(_), DataType::Struct(_)) => {
                _struct_arithmetic(self, rhs, |a, b| a.sub(b))
            },
            (DataType::List(_), _) | (_, DataType::List(_)) => {
                list_borrowed::NumericListOp::Sub.execute(self, rhs)
            },
            _ => {
                let (lhs, rhs) = coerce_lhs_rhs(self, rhs)?;
                lhs.subtract(rhs.as_ref())
            },
        }
    }
}

impl Mul for &Series {
    type Output = PolarsResult<Series>;

    /// ```
    /// # use polars_core::prelude::*;
    /// let s: Series = [1, 2, 3].iter().collect();
    /// let out = (&s * &s).unwrap();
    /// ```
    fn mul(self, rhs: Self) -> Self::Output {
        check_lengths(self, rhs)?;

        use DataType::*;
        match (self.dtype(), rhs.dtype()) {
            #[cfg(feature = "dtype-struct")]
            (Struct(_), Struct(_)) => _struct_arithmetic(self, rhs, |a, b| a.mul(b)),
            // temporal lh
            (Duration(_), _) | (Date, _) | (Datetime(_, _), _) | (Time, _) => self.multiply(rhs),
            // temporal rhs
            (_, Date) | (_, Datetime(_, _)) | (_, Time) => {
                polars_bail!(opq = mul, self.dtype(), rhs.dtype())
            },
            (_, Duration(_)) => {
                // swap order
                let out = rhs.multiply(self)?;
                Ok(out.with_name(self.name().clone()))
            },
            (DataType::List(_), _) | (_, DataType::List(_)) => {
                list_borrowed::NumericListOp::Mul.execute(self, rhs)
            },
            _ => {
                let (lhs, rhs) = coerce_lhs_rhs(self, rhs)?;
                lhs.multiply(rhs.as_ref())
            },
        }
    }
}

impl Div for &Series {
    type Output = PolarsResult<Series>;

    /// ```
    /// # use polars_core::prelude::*;
    /// let s: Series = [1, 2, 3].iter().collect();
    /// let out = (&s / &s).unwrap();
    /// ```
    fn div(self, rhs: Self) -> Self::Output {
        check_lengths(self, rhs)?;
        use DataType::*;
        match (self.dtype(), rhs.dtype()) {
            #[cfg(feature = "dtype-struct")]
            (Struct(_), Struct(_)) => _struct_arithmetic(self, rhs, |a, b| a.div(b)),
            (Duration(_), _) => self.divide(rhs),
            (Date, _)
            | (Datetime(_, _), _)
            | (Time, _)
            | (_, Duration(_))
            | (_, Time)
            | (_, Date)
            | (_, Datetime(_, _)) => polars_bail!(opq = div, self.dtype(), rhs.dtype()),
            (DataType::List(_), _) | (_, DataType::List(_)) => {
                list_borrowed::NumericListOp::Div.execute(self, rhs)
            },
            _ => {
                let (lhs, rhs) = coerce_lhs_rhs(self, rhs)?;
                lhs.divide(rhs.as_ref())
            },
        }
    }
}

impl Rem for &Series {
    type Output = PolarsResult<Series>;

    /// ```
    /// # use polars_core::prelude::*;
    /// let s: Series = [1, 2, 3].iter().collect();
    /// let out = (&s / &s).unwrap();
    /// ```
    fn rem(self, rhs: Self) -> Self::Output {
        check_lengths(self, rhs)?;
        match (self.dtype(), rhs.dtype()) {
            #[cfg(feature = "dtype-struct")]
            (DataType::Struct(_), DataType::Struct(_)) => {
                _struct_arithmetic(self, rhs, |a, b| a.rem(b))
            },
            (DataType::List(_), _) | (_, DataType::List(_)) => {
                list_borrowed::NumericListOp::Rem.execute(self, rhs)
            },
            _ => {
                let (lhs, rhs) = coerce_lhs_rhs(self, rhs)?;
                lhs.remainder(rhs.as_ref())
            },
        }
    }
}

// Series +-/* numbers instead of Series

fn finish_cast(inp: &Series, out: Series) -> Series {
    match inp.dtype() {
        #[cfg(feature = "dtype-date")]
        DataType::Date => out.into_date(),
        #[cfg(feature = "dtype-datetime")]
        DataType::Datetime(tu, tz) => out.into_datetime(*tu, tz.clone()),
        #[cfg(feature = "dtype-duration")]
        DataType::Duration(tu) => out.into_duration(*tu),
        #[cfg(feature = "dtype-time")]
        DataType::Time => out.into_time(),
        _ => out,
    }
}

impl<T> Sub<T> for &Series
where
    T: Num + NumCast,
{
    type Output = Series;

    fn sub(self, rhs: T) -> Self::Output {
        let s = self.to_physical_repr();
        macro_rules! sub {
            ($ca:expr) => {{
                $ca.sub(rhs).into_series()
            }};
        }

        let out = downcast_as_macro_arg_physical!(s, sub);
        finish_cast(self, out)
    }
}

impl<T> Sub<T> for Series
where
    T: Num + NumCast,
{
    type Output = Self;

    fn sub(self, rhs: T) -> Self::Output {
        (&self).sub(rhs)
    }
}

impl<T> Add<T> for &Series
where
    T: Num + NumCast,
{
    type Output = Series;

    fn add(self, rhs: T) -> Self::Output {
        let s = self.to_physical_repr();
        macro_rules! add {
            ($ca:expr) => {{
                $ca.add(rhs).into_series()
            }};
        }
        let out = downcast_as_macro_arg_physical!(s, add);
        finish_cast(self, out)
    }
}

impl<T> Add<T> for Series
where
    T: Num + NumCast,
{
    type Output = Self;

    fn add(self, rhs: T) -> Self::Output {
        (&self).add(rhs)
    }
}

impl<T> Div<T> for &Series
where
    T: Num + NumCast,
{
    type Output = Series;

    fn div(self, rhs: T) -> Self::Output {
        let s = self.to_physical_repr();
        macro_rules! div {
            ($ca:expr) => {{
                $ca.div(rhs).into_series()
            }};
        }

        let out = downcast_as_macro_arg_physical!(s, div);
        finish_cast(self, out)
    }
}

impl<T> Div<T> for Series
where
    T: Num + NumCast,
{
    type Output = Self;

    fn div(self, rhs: T) -> Self::Output {
        (&self).div(rhs)
    }
}

// TODO: remove this, temporary band-aid.
impl Series {
    pub fn wrapping_trunc_div_scalar<T: Num + NumCast>(&self, rhs: T) -> Self {
        let s = self.to_physical_repr();
        macro_rules! div {
            ($ca:expr) => {{
                let rhs = NumCast::from(rhs).unwrap();
                $ca.wrapping_trunc_div_scalar(rhs).into_series()
            }};
        }

        let out = downcast_as_macro_arg_physical!(s, div);
        finish_cast(self, out)
    }
}

impl<T> Mul<T> for &Series
where
    T: Num + NumCast,
{
    type Output = Series;

    fn mul(self, rhs: T) -> Self::Output {
        let s = self.to_physical_repr();
        macro_rules! mul {
            ($ca:expr) => {{
                $ca.mul(rhs).into_series()
            }};
        }
        let out = downcast_as_macro_arg_physical!(s, mul);
        finish_cast(self, out)
    }
}

impl<T> Mul<T> for Series
where
    T: Num + NumCast,
{
    type Output = Self;

    fn mul(self, rhs: T) -> Self::Output {
        (&self).mul(rhs)
    }
}

impl<T> Rem<T> for &Series
where
    T: Num + NumCast,
{
    type Output = Series;

    fn rem(self, rhs: T) -> Self::Output {
        let s = self.to_physical_repr();
        macro_rules! rem {
            ($ca:expr) => {{
                $ca.rem(rhs).into_series()
            }};
        }
        let out = downcast_as_macro_arg_physical!(s, rem);
        finish_cast(self, out)
    }
}

impl<T> Rem<T> for Series
where
    T: Num + NumCast,
{
    type Output = Self;

    fn rem(self, rhs: T) -> Self::Output {
        (&self).rem(rhs)
    }
}

/// We cannot override the left hand side behaviour. So we create a trait LhsNumOps.
/// This allows for 1.add(&Series)
///
impl<T> ChunkedArray<T>
where
    T: PolarsNumericType,
    ChunkedArray<T>: IntoSeries,
{
    /// Apply lhs - self
    #[must_use]
    pub fn lhs_sub<N: Num + NumCast>(&self, lhs: N) -> Self {
        let lhs: T::Native = NumCast::from(lhs).expect("could not cast");
        ArithmeticChunked::wrapping_sub_scalar_lhs(lhs, self)
    }

    /// Apply lhs / self
    #[must_use]
    pub fn lhs_div<N: Num + NumCast>(&self, lhs: N) -> Self {
        let lhs: T::Native = NumCast::from(lhs).expect("could not cast");
        ArithmeticChunked::legacy_div_scalar_lhs(lhs, self)
    }

    /// Apply lhs % self
    #[must_use]
    pub fn lhs_rem<N: Num + NumCast>(&self, lhs: N) -> Self {
        let lhs: T::Native = NumCast::from(lhs).expect("could not cast");
        ArithmeticChunked::wrapping_mod_scalar_lhs(lhs, self)
    }
}

pub trait LhsNumOps {
    type Output;

    fn add(self, rhs: &Series) -> Self::Output;
    fn sub(self, rhs: &Series) -> Self::Output;
    fn div(self, rhs: &Series) -> Self::Output;
    fn mul(self, rhs: &Series) -> Self::Output;
    fn rem(self, rem: &Series) -> Self::Output;
}

impl<T> LhsNumOps for T
where
    T: Num + NumCast,
{
    type Output = Series;

    fn add(self, rhs: &Series) -> Self::Output {
        // order doesn't matter, dispatch to rhs + lhs
        rhs + self
    }
    fn sub(self, rhs: &Series) -> Self::Output {
        let s = rhs.to_physical_repr();
        macro_rules! sub {
            ($rhs:expr) => {{
                $rhs.lhs_sub(self).into_series()
            }};
        }
        let out = downcast_as_macro_arg_physical!(s, sub);

        finish_cast(rhs, out)
    }
    fn div(self, rhs: &Series) -> Self::Output {
        let s = rhs.to_physical_repr();
        macro_rules! div {
            ($rhs:expr) => {{
                $rhs.lhs_div(self).into_series()
            }};
        }
        let out = downcast_as_macro_arg_physical!(s, div);

        finish_cast(rhs, out)
    }
    fn mul(self, rhs: &Series) -> Self::Output {
        // order doesn't matter, dispatch to rhs * lhs
        rhs * self
    }
    fn rem(self, rhs: &Series) -> Self::Output {
        let s = rhs.to_physical_repr();
        macro_rules! rem {
            ($rhs:expr) => {{
                $rhs.lhs_rem(self).into_series()
            }};
        }

        let out = downcast_as_macro_arg_physical!(s, rem);

        finish_cast(rhs, out)
    }
}

#[cfg(test)]
mod test {
    use crate::prelude::*;

    #[test]
    #[allow(clippy::eq_op)]
    fn test_arithmetic_series() -> PolarsResult<()> {
        // Series +-/* Series
        let s = Series::new("foo".into(), [1, 2, 3]);
        assert_eq!(
            Vec::from((&s * &s)?.i32().unwrap()),
            [Some(1), Some(4), Some(9)]
        );
        assert_eq!(
            Vec::from((&s / &s)?.i32().unwrap()),
            [Some(1), Some(1), Some(1)]
        );
        assert_eq!(
            Vec::from((&s - &s)?.i32().unwrap()),
            [Some(0), Some(0), Some(0)]
        );
        assert_eq!(
            Vec::from((&s + &s)?.i32().unwrap()),
            [Some(2), Some(4), Some(6)]
        );
        // Series +-/* Number
        assert_eq!(
            Vec::from((&s + 1).i32().unwrap()),
            [Some(2), Some(3), Some(4)]
        );
        assert_eq!(
            Vec::from((&s - 1).i32().unwrap()),
            [Some(0), Some(1), Some(2)]
        );
        assert_eq!(
            Vec::from((&s * 2).i32().unwrap()),
            [Some(2), Some(4), Some(6)]
        );
        assert_eq!(
            Vec::from((&s / 2).i32().unwrap()),
            [Some(0), Some(1), Some(1)]
        );

        // Lhs operations
        assert_eq!(
            Vec::from((1.add(&s)).i32().unwrap()),
            [Some(2), Some(3), Some(4)]
        );
        assert_eq!(
            Vec::from((1.sub(&s)).i32().unwrap()),
            [Some(0), Some(-1), Some(-2)]
        );
        assert_eq!(
            Vec::from((1.div(&s)).i32().unwrap()),
            [Some(1), Some(0), Some(0)]
        );
        assert_eq!(
            Vec::from((1.mul(&s)).i32().unwrap()),
            [Some(1), Some(2), Some(3)]
        );
        assert_eq!(
            Vec::from((1.rem(&s)).i32().unwrap()),
            [Some(0), Some(1), Some(1)]
        );

        assert_eq!((&s * &s)?.name().as_str(), "foo");
        assert_eq!((&s * 1).name().as_str(), "foo");
        assert_eq!((1.div(&s)).name().as_str(), "foo");

        Ok(())
    }

    #[test]
    #[cfg(feature = "checked_arithmetic")]
    fn test_checked_div() {
        let s = Series::new("foo".into(), [1i32, 0, 1]);
        let out = s.checked_div(&s).unwrap();
        assert_eq!(Vec::from(out.i32().unwrap()), &[Some(1), None, Some(1)]);
        let out = s.checked_div_num(0).unwrap();
        assert_eq!(Vec::from(out.i32().unwrap()), &[None, None, None]);

        let s_f32 = Series::new("float32".into(), [1.0f32, 0.0, 1.0]);
        let out = s_f32.checked_div(&s_f32).unwrap();
        assert_eq!(
            Vec::from(out.f32().unwrap()),
            &[Some(1.0f32), None, Some(1.0f32)]
        );
        let out = s_f32.checked_div_num(0.0f32).unwrap();
        assert_eq!(Vec::from(out.f32().unwrap()), &[None, None, None]);

        let s_f64 = Series::new("float64".into(), [1.0f64, 0.0, 1.0]);
        let out = s_f64.checked_div(&s_f64).unwrap();
        assert_eq!(
            Vec::from(out.f64().unwrap()),
            &[Some(1.0f64), None, Some(1.0f64)]
        );
        let out = s_f64.checked_div_num(0.0f64).unwrap();
        assert_eq!(Vec::from(out.f64().unwrap()), &[None, None, None]);
    }
}