#[cfg(feature = "dtype-array")]
mod array;
mod binary;
mod binary_offset;
mod boolean;
#[cfg(feature = "dtype-categorical")]
mod categorical;
#[cfg(feature = "dtype-date")]
mod date;
#[cfg(feature = "dtype-datetime")]
mod datetime;
#[cfg(feature = "dtype-decimal")]
mod decimal;
#[cfg(feature = "dtype-duration")]
mod duration;
mod floats;
mod list;
pub(crate) mod null;
#[cfg(feature = "object")]
mod object;
mod string;
#[cfg(feature = "dtype-struct")]
mod struct_;
#[cfg(feature = "dtype-time")]
mod time;
use std::any::Any;
use std::borrow::Cow;
use std::ops::{BitAnd, BitOr, BitXor};
use ahash::RandomState;
use super::*;
use crate::chunked_array::comparison::*;
use crate::chunked_array::ops::compare_inner::{
IntoTotalEqInner, IntoTotalOrdInner, TotalEqInner, TotalOrdInner,
};
use crate::chunked_array::ops::explode::ExplodeByOffsets;
use crate::chunked_array::AsSinglePtr;
pub(crate) struct SeriesWrap<T>(pub T);
impl<T: PolarsDataType> From<ChunkedArray<T>> for SeriesWrap<ChunkedArray<T>> {
fn from(ca: ChunkedArray<T>) -> Self {
SeriesWrap(ca)
}
}
impl<T: PolarsDataType> Deref for SeriesWrap<ChunkedArray<T>> {
type Target = ChunkedArray<T>;
fn deref(&self) -> &Self::Target {
&self.0
}
}
unsafe impl<T: PolarsDataType + 'static> IntoSeries for ChunkedArray<T>
where
SeriesWrap<ChunkedArray<T>>: SeriesTrait,
{
fn into_series(self) -> Series
where
Self: Sized,
{
Series(Arc::new(SeriesWrap(self)))
}
}
macro_rules! impl_dyn_series {
($ca: ident) => {
impl private::PrivateSeries for SeriesWrap<$ca> {
fn compute_len(&mut self) {
self.0.compute_len()
}
fn _field(&self) -> Cow<Field> {
Cow::Borrowed(self.0.ref_field())
}
fn _dtype(&self) -> &DataType {
self.0.ref_field().data_type()
}
fn _get_flags(&self) -> MetadataFlags {
self.0.get_flags()
}
fn _set_flags(&mut self, flags: MetadataFlags) {
self.0.set_flags(flags)
}
fn explode_by_offsets(&self, offsets: &[i64]) -> Series {
self.0.explode_by_offsets(offsets)
}
unsafe fn equal_element(
&self,
idx_self: usize,
idx_other: usize,
other: &Series,
) -> bool {
self.0.equal_element(idx_self, idx_other, other)
}
#[cfg(feature = "zip_with")]
fn zip_with_same_type(
&self,
mask: &BooleanChunked,
other: &Series,
) -> PolarsResult<Series> {
ChunkZip::zip_with(&self.0, mask, other.as_ref().as_ref())
.map(|ca| ca.into_series())
}
fn into_total_eq_inner<'a>(&'a self) -> Box<dyn TotalEqInner + 'a> {
(&self.0).into_total_eq_inner()
}
fn into_total_ord_inner<'a>(&'a self) -> Box<dyn TotalOrdInner + 'a> {
(&self.0).into_total_ord_inner()
}
fn vec_hash(&self, random_state: RandomState, buf: &mut Vec<u64>) -> PolarsResult<()> {
self.0.vec_hash(random_state, buf)?;
Ok(())
}
fn vec_hash_combine(
&self,
build_hasher: RandomState,
hashes: &mut [u64],
) -> PolarsResult<()> {
self.0.vec_hash_combine(build_hasher, hashes)?;
Ok(())
}
#[cfg(feature = "algorithm_group_by")]
unsafe fn agg_min(&self, groups: &GroupsProxy) -> Series {
self.0.agg_min(groups)
}
#[cfg(feature = "algorithm_group_by")]
unsafe fn agg_max(&self, groups: &GroupsProxy) -> Series {
self.0.agg_max(groups)
}
#[cfg(feature = "algorithm_group_by")]
unsafe fn agg_sum(&self, groups: &GroupsProxy) -> Series {
use DataType::*;
match self.dtype() {
Int8 | UInt8 | Int16 | UInt16 => self
.cast(&Int64, CastOptions::Overflowing)
.unwrap()
.agg_sum(groups),
_ => self.0.agg_sum(groups),
}
}
#[cfg(feature = "algorithm_group_by")]
unsafe fn agg_std(&self, groups: &GroupsProxy, ddof: u8) -> Series {
self.0.agg_std(groups, ddof)
}
#[cfg(feature = "algorithm_group_by")]
unsafe fn agg_var(&self, groups: &GroupsProxy, ddof: u8) -> Series {
self.0.agg_var(groups, ddof)
}
#[cfg(feature = "algorithm_group_by")]
unsafe fn agg_list(&self, groups: &GroupsProxy) -> Series {
self.0.agg_list(groups)
}
fn subtract(&self, rhs: &Series) -> PolarsResult<Series> {
NumOpsDispatch::subtract(&self.0, rhs)
}
fn add_to(&self, rhs: &Series) -> PolarsResult<Series> {
NumOpsDispatch::add_to(&self.0, rhs)
}
fn multiply(&self, rhs: &Series) -> PolarsResult<Series> {
NumOpsDispatch::multiply(&self.0, rhs)
}
fn divide(&self, rhs: &Series) -> PolarsResult<Series> {
NumOpsDispatch::divide(&self.0, rhs)
}
fn remainder(&self, rhs: &Series) -> PolarsResult<Series> {
NumOpsDispatch::remainder(&self.0, rhs)
}
#[cfg(feature = "algorithm_group_by")]
fn group_tuples(&self, multithreaded: bool, sorted: bool) -> PolarsResult<GroupsProxy> {
IntoGroupsProxy::group_tuples(&self.0, multithreaded, sorted)
}
fn arg_sort_multiple(
&self,
by: &[Series],
options: &SortMultipleOptions,
) -> PolarsResult<IdxCa> {
self.0.arg_sort_multiple(by, options)
}
}
impl SeriesTrait for SeriesWrap<$ca> {
#[cfg(feature = "rolling_window")]
fn rolling_map(
&self,
_f: &dyn Fn(&Series) -> Series,
_options: RollingOptionsFixedWindow,
) -> PolarsResult<Series> {
ChunkRollApply::rolling_map(&self.0, _f, _options).map(|ca| ca.into_series())
}
fn bitand(&self, other: &Series) -> PolarsResult<Series> {
let other = if other.len() == 1 {
Cow::Owned(other.cast(self.dtype())?)
} else {
Cow::Borrowed(other)
};
let other = self.0.unpack_series_matching_type(&other)?;
Ok(self.0.bitand(&other).into_series())
}
fn bitor(&self, other: &Series) -> PolarsResult<Series> {
let other = if other.len() == 1 {
Cow::Owned(other.cast(self.dtype())?)
} else {
Cow::Borrowed(other)
};
let other = self.0.unpack_series_matching_type(&other)?;
Ok(self.0.bitor(&other).into_series())
}
fn bitxor(&self, other: &Series) -> PolarsResult<Series> {
let other = if other.len() == 1 {
Cow::Owned(other.cast(self.dtype())?)
} else {
Cow::Borrowed(other)
};
let other = self.0.unpack_series_matching_type(&other)?;
Ok(self.0.bitxor(&other).into_series())
}
fn rename(&mut self, name: &str) {
self.0.rename(name);
}
fn chunk_lengths(&self) -> ChunkLenIter {
self.0.chunk_lengths()
}
fn name(&self) -> &str {
self.0.name()
}
fn chunks(&self) -> &Vec<ArrayRef> {
self.0.chunks()
}
unsafe fn chunks_mut(&mut self) -> &mut Vec<ArrayRef> {
self.0.chunks_mut()
}
fn shrink_to_fit(&mut self) {
self.0.shrink_to_fit()
}
fn slice(&self, offset: i64, length: usize) -> Series {
return self.0.slice(offset, length).into_series();
}
fn append(&mut self, other: &Series) -> PolarsResult<()> {
polars_ensure!(self.0.dtype() == other.dtype(), append);
self.0.append(other.as_ref().as_ref());
Ok(())
}
fn extend(&mut self, other: &Series) -> PolarsResult<()> {
polars_ensure!(self.0.dtype() == other.dtype(), extend);
self.0.extend(other.as_ref().as_ref());
Ok(())
}
fn filter(&self, filter: &BooleanChunked) -> PolarsResult<Series> {
ChunkFilter::filter(&self.0, filter).map(|ca| ca.into_series())
}
fn mean(&self) -> Option<f64> {
self.0.mean()
}
fn median(&self) -> Option<f64> {
self.0.median()
}
fn std(&self, ddof: u8) -> Option<f64> {
self.0.std(ddof)
}
fn var(&self, ddof: u8) -> Option<f64> {
self.0.var(ddof)
}
fn take(&self, indices: &IdxCa) -> PolarsResult<Series> {
Ok(self.0.take(indices)?.into_series())
}
unsafe fn take_unchecked(&self, indices: &IdxCa) -> Series {
self.0.take_unchecked(indices).into_series()
}
fn take_slice(&self, indices: &[IdxSize]) -> PolarsResult<Series> {
Ok(self.0.take(indices)?.into_series())
}
unsafe fn take_slice_unchecked(&self, indices: &[IdxSize]) -> Series {
self.0.take_unchecked(indices).into_series()
}
fn len(&self) -> usize {
self.0.len()
}
fn rechunk(&self) -> Series {
self.0.rechunk().into_series()
}
fn new_from_index(&self, index: usize, length: usize) -> Series {
ChunkExpandAtIndex::new_from_index(&self.0, index, length).into_series()
}
fn cast(&self, data_type: &DataType, options: CastOptions) -> PolarsResult<Series> {
self.0.cast_with_options(data_type, options)
}
fn get(&self, index: usize) -> PolarsResult<AnyValue> {
self.0.get_any_value(index)
}
#[inline]
unsafe fn get_unchecked(&self, index: usize) -> AnyValue {
self.0.get_any_value_unchecked(index)
}
fn sort_with(&self, options: SortOptions) -> PolarsResult<Series> {
Ok(ChunkSort::sort_with(&self.0, options).into_series())
}
fn arg_sort(&self, options: SortOptions) -> IdxCa {
ChunkSort::arg_sort(&self.0, options)
}
fn null_count(&self) -> usize {
self.0.null_count()
}
fn has_validity(&self) -> bool {
self.0.has_validity()
}
#[cfg(feature = "algorithm_group_by")]
fn unique(&self) -> PolarsResult<Series> {
ChunkUnique::unique(&self.0).map(|ca| ca.into_series())
}
#[cfg(feature = "algorithm_group_by")]
fn n_unique(&self) -> PolarsResult<usize> {
ChunkUnique::n_unique(&self.0)
}
#[cfg(feature = "algorithm_group_by")]
fn arg_unique(&self) -> PolarsResult<IdxCa> {
ChunkUnique::arg_unique(&self.0)
}
fn is_null(&self) -> BooleanChunked {
self.0.is_null()
}
fn is_not_null(&self) -> BooleanChunked {
self.0.is_not_null()
}
fn reverse(&self) -> Series {
ChunkReverse::reverse(&self.0).into_series()
}
fn as_single_ptr(&mut self) -> PolarsResult<usize> {
self.0.as_single_ptr()
}
fn shift(&self, periods: i64) -> Series {
ChunkShift::shift(&self.0, periods).into_series()
}
fn sum_reduce(&self) -> PolarsResult<Scalar> {
Ok(ChunkAggSeries::sum_reduce(&self.0))
}
fn max_reduce(&self) -> PolarsResult<Scalar> {
Ok(ChunkAggSeries::max_reduce(&self.0))
}
fn min_reduce(&self) -> PolarsResult<Scalar> {
Ok(ChunkAggSeries::min_reduce(&self.0))
}
fn median_reduce(&self) -> PolarsResult<Scalar> {
Ok(QuantileAggSeries::median_reduce(&self.0))
}
fn var_reduce(&self, ddof: u8) -> PolarsResult<Scalar> {
Ok(VarAggSeries::var_reduce(&self.0, ddof))
}
fn std_reduce(&self, ddof: u8) -> PolarsResult<Scalar> {
Ok(VarAggSeries::std_reduce(&self.0, ddof))
}
fn quantile_reduce(
&self,
quantile: f64,
interpol: QuantileInterpolOptions,
) -> PolarsResult<Scalar> {
QuantileAggSeries::quantile_reduce(&self.0, quantile, interpol)
}
fn clone_inner(&self) -> Arc<dyn SeriesTrait> {
Arc::new(SeriesWrap(Clone::clone(&self.0)))
}
#[cfg(feature = "checked_arithmetic")]
fn checked_div(&self, rhs: &Series) -> PolarsResult<Series> {
self.0.checked_div(rhs)
}
fn as_any(&self) -> &dyn Any {
&self.0
}
}
};
}
#[cfg(feature = "dtype-u8")]
impl_dyn_series!(UInt8Chunked);
#[cfg(feature = "dtype-u16")]
impl_dyn_series!(UInt16Chunked);
impl_dyn_series!(UInt32Chunked);
impl_dyn_series!(UInt64Chunked);
#[cfg(feature = "dtype-i8")]
impl_dyn_series!(Int8Chunked);
#[cfg(feature = "dtype-i16")]
impl_dyn_series!(Int16Chunked);
impl_dyn_series!(Int32Chunked);
impl_dyn_series!(Int64Chunked);
impl<T: PolarsNumericType> private::PrivateSeriesNumeric for SeriesWrap<ChunkedArray<T>> {
fn bit_repr_is_large(&self) -> bool {
ChunkedArray::<T>::bit_repr_is_large()
}
fn bit_repr_large(&self) -> UInt64Chunked {
self.0.bit_repr_large()
}
fn bit_repr_small(&self) -> UInt32Chunked {
self.0.bit_repr_small()
}
}
impl private::PrivateSeriesNumeric for SeriesWrap<StringChunked> {}
impl private::PrivateSeriesNumeric for SeriesWrap<BinaryChunked> {}
impl private::PrivateSeriesNumeric for SeriesWrap<BinaryOffsetChunked> {}
impl private::PrivateSeriesNumeric for SeriesWrap<ListChunked> {}
#[cfg(feature = "dtype-array")]
impl private::PrivateSeriesNumeric for SeriesWrap<ArrayChunked> {}
impl private::PrivateSeriesNumeric for SeriesWrap<BooleanChunked> {
fn bit_repr_is_large(&self) -> bool {
false
}
fn bit_repr_small(&self) -> UInt32Chunked {
self.0
.cast_with_options(&DataType::UInt32, CastOptions::NonStrict)
.unwrap()
.u32()
.unwrap()
.clone()
}
}