polars_core/series/implementations/
mod.rs

1#![allow(unsafe_op_in_unsafe_fn)]
2#[cfg(feature = "dtype-array")]
3mod array;
4mod binary;
5mod binary_offset;
6mod boolean;
7#[cfg(feature = "dtype-categorical")]
8mod categorical;
9#[cfg(feature = "dtype-date")]
10mod date;
11#[cfg(feature = "dtype-datetime")]
12mod datetime;
13#[cfg(feature = "dtype-decimal")]
14mod decimal;
15#[cfg(feature = "dtype-duration")]
16mod duration;
17#[cfg(feature = "dtype-extension")]
18mod extension;
19mod floats;
20mod list;
21#[cfg(feature = "dtype-map")]
22mod map;
23pub(crate) mod null;
24#[cfg(feature = "object")]
25mod object;
26mod string;
27#[cfg(feature = "dtype-struct")]
28mod struct_;
29#[cfg(feature = "dtype-time")]
30mod time;
31
32use std::any::Any;
33use std::borrow::Cow;
34
35use arrow::bitmap::Bitmap;
36use polars_compute::rolling::QuantileMethod;
37use polars_utils::aliases::PlSeedableRandomStateQuality;
38
39use super::*;
40use crate::chunked_array::AsSinglePtr;
41use crate::chunked_array::ops::compare_inner::{
42    IntoTotalEqInner, IntoTotalOrdInner, TotalEqInner, TotalOrdInner,
43};
44
45// Utility wrapper struct
46#[repr(transparent)]
47pub(crate) struct SeriesWrap<T>(pub T);
48
49impl<T: PolarsDataType> From<ChunkedArray<T>> for SeriesWrap<ChunkedArray<T>> {
50    fn from(ca: ChunkedArray<T>) -> Self {
51        SeriesWrap(ca)
52    }
53}
54
55impl<T: PolarsDataType> Deref for SeriesWrap<ChunkedArray<T>> {
56    type Target = ChunkedArray<T>;
57
58    fn deref(&self) -> &Self::Target {
59        &self.0
60    }
61}
62
63unsafe impl<T: PolarsPhysicalType> IntoSeries for ChunkedArray<T> {
64    fn into_series(self) -> Series {
65        T::ca_into_series(self)
66    }
67}
68
69macro_rules! impl_dyn_series {
70    ($ca: ident, $pdt:ty) => {
71        impl private::PrivateSeries for SeriesWrap<$ca> {
72            fn compute_len(&mut self) {
73                self.0.compute_len()
74            }
75
76            fn _field(&self) -> Cow<'_, Field> {
77                Cow::Borrowed(self.0.ref_field())
78            }
79
80            fn _dtype(&self) -> &DataType {
81                self.0.ref_field().dtype()
82            }
83
84            fn _get_flags(&self) -> StatisticsFlags {
85                self.0.get_flags()
86            }
87
88            fn _set_flags(&mut self, flags: StatisticsFlags) {
89                self.0.set_flags(flags)
90            }
91
92            #[cfg(feature = "zip_with")]
93            fn zip_with_same_type(
94                &self,
95                mask: &BooleanChunked,
96                other: &Series,
97            ) -> PolarsResult<Series> {
98                ChunkZip::zip_with(&self.0, mask, other.as_ref().as_ref())
99                    .map(|ca| ca.into_series())
100            }
101            fn into_total_eq_inner<'a>(&'a self) -> Box<dyn TotalEqInner + 'a> {
102                (&self.0).into_total_eq_inner()
103            }
104            fn into_total_ord_inner<'a>(&'a self) -> Box<dyn TotalOrdInner + 'a> {
105                (&self.0).into_total_ord_inner()
106            }
107
108            fn vec_hash(
109                &self,
110                random_state: PlSeedableRandomStateQuality,
111                buf: &mut Vec<u64>,
112            ) -> PolarsResult<()> {
113                self.0.vec_hash(random_state, buf)?;
114                Ok(())
115            }
116
117            fn vec_hash_combine(
118                &self,
119                build_hasher: PlSeedableRandomStateQuality,
120                hashes: &mut [u64],
121            ) -> PolarsResult<()> {
122                self.0.vec_hash_combine(build_hasher, hashes)?;
123                Ok(())
124            }
125
126            #[cfg(feature = "algorithm_group_by")]
127            unsafe fn agg_min(&self, groups: &GroupsType) -> Series {
128                self.0.agg_min(groups)
129            }
130
131            #[cfg(feature = "algorithm_group_by")]
132            unsafe fn agg_max(&self, groups: &GroupsType) -> Series {
133                self.0.agg_max(groups)
134            }
135
136            #[cfg(feature = "algorithm_group_by")]
137            unsafe fn agg_arg_min(&self, groups: &GroupsType) -> Series {
138                self.0.agg_arg_min(groups)
139            }
140
141            #[cfg(feature = "algorithm_group_by")]
142            unsafe fn agg_arg_max(&self, groups: &GroupsType) -> Series {
143                self.0.agg_arg_max(groups)
144            }
145
146            #[cfg(feature = "algorithm_group_by")]
147            unsafe fn agg_sum(&self, groups: &GroupsType) -> Series {
148                use DataType::*;
149                match self.dtype() {
150                    Int8 | UInt8 | Int16 | UInt16 => self
151                        .cast(&Int64, CastOptions::Overflowing)
152                        .unwrap()
153                        .agg_sum(groups),
154                    _ => self.0.agg_sum(groups),
155                }
156            }
157
158            #[cfg(feature = "algorithm_group_by")]
159            unsafe fn agg_std(&self, groups: &GroupsType, ddof: u8) -> Series {
160                self.0.agg_std(groups, ddof)
161            }
162
163            #[cfg(feature = "algorithm_group_by")]
164            unsafe fn agg_var(&self, groups: &GroupsType, ddof: u8) -> Series {
165                self.0.agg_var(groups, ddof)
166            }
167
168            #[cfg(feature = "algorithm_group_by")]
169            unsafe fn agg_list(&self, groups: &GroupsType) -> Series {
170                self.0.agg_list(groups)
171            }
172
173            #[cfg(feature = "bitwise")]
174            unsafe fn agg_and(&self, groups: &GroupsType) -> Series {
175                self.0.agg_and(groups)
176            }
177            #[cfg(feature = "bitwise")]
178            unsafe fn agg_or(&self, groups: &GroupsType) -> Series {
179                self.0.agg_or(groups)
180            }
181            #[cfg(feature = "bitwise")]
182            unsafe fn agg_xor(&self, groups: &GroupsType) -> Series {
183                self.0.agg_xor(groups)
184            }
185
186            fn subtract(&self, rhs: &Series) -> PolarsResult<Series> {
187                NumOpsDispatch::subtract(&self.0, rhs)
188            }
189            fn add_to(&self, rhs: &Series) -> PolarsResult<Series> {
190                NumOpsDispatch::add_to(&self.0, rhs)
191            }
192            fn multiply(&self, rhs: &Series) -> PolarsResult<Series> {
193                NumOpsDispatch::multiply(&self.0, rhs)
194            }
195            fn divide(&self, rhs: &Series) -> PolarsResult<Series> {
196                NumOpsDispatch::divide(&self.0, rhs)
197            }
198            fn remainder(&self, rhs: &Series) -> PolarsResult<Series> {
199                NumOpsDispatch::remainder(&self.0, rhs)
200            }
201            #[cfg(feature = "algorithm_group_by")]
202            fn group_tuples(&self, multithreaded: bool, sorted: bool) -> PolarsResult<GroupsType> {
203                IntoGroupsType::group_tuples(&self.0, multithreaded, sorted)
204            }
205
206            fn arg_sort_multiple(
207                &self,
208                by: &[Column],
209                options: &SortMultipleOptions,
210            ) -> PolarsResult<IdxCa> {
211                self.0.arg_sort_multiple(by, options)
212            }
213        }
214
215        impl SeriesTrait for SeriesWrap<$ca> {
216            #[cfg(feature = "rolling_window")]
217            fn rolling_map(
218                &self,
219                _f: &dyn Fn(&Series) -> PolarsResult<Series>,
220                _options: RollingOptionsFixedWindow,
221            ) -> PolarsResult<Series> {
222                ChunkRollApply::rolling_map(&self.0, _f, _options).map(|ca| ca.into_series())
223            }
224
225            fn rename(&mut self, name: PlSmallStr) {
226                self.0.rename(name);
227            }
228
229            fn chunk_lengths(&self) -> ChunkLenIter<'_> {
230                self.0.chunk_lengths()
231            }
232            fn name(&self) -> &PlSmallStr {
233                self.0.name()
234            }
235
236            fn chunks(&self) -> &Vec<ArrayRef> {
237                self.0.chunks()
238            }
239            unsafe fn chunks_mut(&mut self) -> &mut Vec<ArrayRef> {
240                self.0.chunks_mut()
241            }
242            fn shrink_to_fit(&mut self) {
243                self.0.shrink_to_fit()
244            }
245
246            fn slice(&self, offset: i64, length: usize) -> Series {
247                self.0.slice(offset, length).into_series()
248            }
249
250            fn split_at(&self, offset: i64) -> (Series, Series) {
251                let (a, b) = self.0.split_at(offset);
252                (a.into_series(), b.into_series())
253            }
254
255            fn append(&mut self, other: &Series) -> PolarsResult<()> {
256                polars_ensure!(self.0.dtype() == other.dtype(), append);
257                self.0.append(other.as_ref().as_ref())?;
258                Ok(())
259            }
260            fn append_owned(&mut self, other: Series) -> PolarsResult<()> {
261                polars_ensure!(self.0.dtype() == other.dtype(), append);
262                self.0.append_owned(other.take_inner())
263            }
264
265            fn extend(&mut self, other: &Series) -> PolarsResult<()> {
266                polars_ensure!(self.0.dtype() == other.dtype(), extend);
267                self.0.extend(other.as_ref().as_ref())?;
268                Ok(())
269            }
270
271            fn filter(&self, filter: &BooleanChunked) -> PolarsResult<Series> {
272                ChunkFilter::filter(&self.0, filter).map(|ca| ca.into_series())
273            }
274
275            fn _sum_as_f64(&self) -> f64 {
276                self.0._sum_as_f64()
277            }
278
279            fn mean(&self) -> Option<f64> {
280                self.0.mean()
281            }
282
283            fn median(&self) -> Option<f64> {
284                self.0.median()
285            }
286
287            fn std(&self, ddof: u8) -> Option<f64> {
288                self.0.std(ddof)
289            }
290
291            fn var(&self, ddof: u8) -> Option<f64> {
292                self.0.var(ddof)
293            }
294
295            fn take(&self, indices: &IdxCa) -> PolarsResult<Series> {
296                Ok(self.0.take(indices)?.into_series())
297            }
298
299            unsafe fn take_unchecked(&self, indices: &IdxCa) -> Series {
300                self.0.take_unchecked(indices).into_series()
301            }
302
303            fn take_slice(&self, indices: &[IdxSize]) -> PolarsResult<Series> {
304                Ok(self.0.take(indices)?.into_series())
305            }
306
307            unsafe fn take_slice_unchecked(&self, indices: &[IdxSize]) -> Series {
308                self.0.take_unchecked(indices).into_series()
309            }
310
311            fn deposit(&self, validity: &Bitmap) -> Series {
312                self.0.deposit(validity).into_series()
313            }
314
315            fn len(&self) -> usize {
316                self.0.len()
317            }
318
319            fn rechunk(&self) -> Series {
320                self.0.rechunk().into_owned().into_series()
321            }
322
323            fn with_validity(&self, validity: Option<Bitmap>) -> Series {
324                self.0.clone().with_validity(validity).into_series()
325            }
326
327            fn new_from_index(&self, index: usize, length: usize) -> Series {
328                ChunkExpandAtIndex::new_from_index(&self.0, index, length).into_series()
329            }
330
331            fn cast(&self, dtype: &DataType, options: CastOptions) -> PolarsResult<Series> {
332                self.0.cast_with_options(dtype, options)
333            }
334
335            #[inline]
336            unsafe fn get_unchecked(&self, index: usize) -> AnyValue<'_> {
337                self.0.get_any_value_unchecked(index)
338            }
339
340            fn sort_with(&self, options: SortOptions) -> PolarsResult<Series> {
341                Ok(ChunkSort::sort_with(&self.0, options).into_series())
342            }
343
344            fn arg_sort(&self, options: SortOptions) -> IdxCa {
345                ChunkSort::arg_sort(&self.0, options)
346            }
347
348            fn null_count(&self) -> usize {
349                self.0.null_count()
350            }
351
352            fn has_nulls(&self) -> bool {
353                self.0.has_nulls()
354            }
355
356            #[cfg(feature = "algorithm_group_by")]
357            fn unique(&self) -> PolarsResult<Series> {
358                ChunkUnique::unique(&self.0).map(|ca| ca.into_series())
359            }
360
361            #[cfg(feature = "algorithm_group_by")]
362            fn n_unique(&self) -> PolarsResult<usize> {
363                ChunkUnique::n_unique(&self.0)
364            }
365
366            #[cfg(feature = "algorithm_group_by")]
367            fn arg_unique(&self) -> PolarsResult<IdxCa> {
368                ChunkUnique::arg_unique(&self.0)
369            }
370
371            #[cfg(feature = "algorithm_group_by")]
372            fn unique_id(&self) -> PolarsResult<(IdxSize, Vec<IdxSize>)> {
373                ChunkUnique::unique_id(&self.0)
374            }
375
376            fn is_null(&self) -> BooleanChunked {
377                self.0.is_null()
378            }
379
380            fn is_not_null(&self) -> BooleanChunked {
381                self.0.is_not_null()
382            }
383
384            fn reverse(&self) -> Series {
385                ChunkReverse::reverse(&self.0).into_series()
386            }
387
388            fn as_single_ptr(&mut self) -> PolarsResult<usize> {
389                self.0.as_single_ptr()
390            }
391
392            fn shift(&self, periods: i64) -> Series {
393                ChunkShift::shift(&self.0, periods).into_series()
394            }
395
396            fn sum_reduce(&self) -> PolarsResult<Scalar> {
397                Ok(ChunkAggSeries::sum_reduce(&self.0))
398            }
399            fn max_reduce(&self) -> PolarsResult<Scalar> {
400                Ok(ChunkAggSeries::max_reduce(&self.0))
401            }
402            fn min_reduce(&self) -> PolarsResult<Scalar> {
403                Ok(ChunkAggSeries::min_reduce(&self.0))
404            }
405            fn mean_reduce(&self) -> PolarsResult<Scalar> {
406                Ok(Scalar::new(DataType::Float64, self.mean().into()))
407            }
408            fn median_reduce(&self) -> PolarsResult<Scalar> {
409                Ok(QuantileAggSeries::median_reduce(&self.0))
410            }
411            fn var_reduce(&self, ddof: u8) -> PolarsResult<Scalar> {
412                Ok(VarAggSeries::var_reduce(&self.0, ddof))
413            }
414            fn std_reduce(&self, ddof: u8) -> PolarsResult<Scalar> {
415                Ok(VarAggSeries::std_reduce(&self.0, ddof))
416            }
417
418            fn quantile_reduce(
419                &self,
420                quantile: f64,
421                method: QuantileMethod,
422            ) -> PolarsResult<Scalar> {
423                QuantileAggSeries::quantile_reduce(&self.0, quantile, method)
424            }
425
426            fn quantiles_reduce(
427                &self,
428                quantiles: &[f64],
429                method: QuantileMethod,
430            ) -> PolarsResult<Scalar> {
431                QuantileAggSeries::quantiles_reduce(&self.0, quantiles, method)
432            }
433
434            #[cfg(feature = "bitwise")]
435            fn and_reduce(&self) -> PolarsResult<Scalar> {
436                let dt = <$pdt as PolarsDataType>::get_static_dtype();
437                let av = self.0.and_reduce().map_or(AnyValue::Null, Into::into);
438
439                Ok(Scalar::new(dt, av))
440            }
441
442            #[cfg(feature = "bitwise")]
443            fn or_reduce(&self) -> PolarsResult<Scalar> {
444                let dt = <$pdt as PolarsDataType>::get_static_dtype();
445                let av = self.0.or_reduce().map_or(AnyValue::Null, Into::into);
446
447                Ok(Scalar::new(dt, av))
448            }
449
450            #[cfg(feature = "bitwise")]
451            fn xor_reduce(&self) -> PolarsResult<Scalar> {
452                let dt = <$pdt as PolarsDataType>::get_static_dtype();
453                let av = self.0.xor_reduce().map_or(AnyValue::Null, Into::into);
454
455                Ok(Scalar::new(dt, av))
456            }
457
458            #[cfg(feature = "approx_unique")]
459            fn approx_n_unique(&self) -> PolarsResult<IdxSize> {
460                Ok(ChunkApproxNUnique::approx_n_unique(&self.0))
461            }
462
463            fn clone_inner(&self) -> Arc<dyn SeriesTrait> {
464                Arc::new(SeriesWrap(Clone::clone(&self.0)))
465            }
466
467            fn find_validity_mismatch(&self, other: &Series, idxs: &mut Vec<IdxSize>) {
468                self.0.find_validity_mismatch(other, idxs)
469            }
470
471            #[cfg(feature = "checked_arithmetic")]
472            fn checked_div(&self, rhs: &Series) -> PolarsResult<Series> {
473                self.0.checked_div(rhs)
474            }
475
476            fn as_any(&self) -> &dyn Any {
477                &self.0
478            }
479
480            fn as_any_mut(&mut self) -> &mut dyn Any {
481                &mut self.0
482            }
483
484            fn as_phys_any(&self) -> &dyn Any {
485                &self.0
486            }
487
488            fn as_arc_any(self: Arc<Self>) -> Arc<dyn Any + Send + Sync> {
489                self as _
490            }
491        }
492    };
493}
494
495#[cfg(feature = "dtype-u8")]
496impl_dyn_series!(UInt8Chunked, UInt8Type);
497#[cfg(feature = "dtype-u16")]
498impl_dyn_series!(UInt16Chunked, UInt16Type);
499impl_dyn_series!(UInt32Chunked, UInt32Type);
500impl_dyn_series!(UInt64Chunked, UInt64Type);
501#[cfg(feature = "dtype-u128")]
502impl_dyn_series!(UInt128Chunked, UInt128Type);
503#[cfg(feature = "dtype-i8")]
504impl_dyn_series!(Int8Chunked, Int8Type);
505#[cfg(feature = "dtype-i16")]
506impl_dyn_series!(Int16Chunked, Int16Type);
507impl_dyn_series!(Int32Chunked, Int32Type);
508impl_dyn_series!(Int64Chunked, Int64Type);
509#[cfg(feature = "dtype-i128")]
510impl_dyn_series!(Int128Chunked, Int128Type);
511
512impl<T: PolarsNumericType> private::PrivateSeriesNumeric for SeriesWrap<ChunkedArray<T>> {
513    fn bit_repr(&self) -> Option<BitRepr> {
514        Some(self.0.to_bit_repr())
515    }
516}
517
518impl private::PrivateSeriesNumeric for SeriesWrap<StringChunked> {
519    fn bit_repr(&self) -> Option<BitRepr> {
520        None
521    }
522}
523impl private::PrivateSeriesNumeric for SeriesWrap<BinaryChunked> {
524    fn bit_repr(&self) -> Option<BitRepr> {
525        None
526    }
527}
528impl private::PrivateSeriesNumeric for SeriesWrap<BinaryOffsetChunked> {
529    fn bit_repr(&self) -> Option<BitRepr> {
530        None
531    }
532}
533impl private::PrivateSeriesNumeric for SeriesWrap<ListChunked> {
534    fn bit_repr(&self) -> Option<BitRepr> {
535        None
536    }
537}
538#[cfg(feature = "dtype-array")]
539impl private::PrivateSeriesNumeric for SeriesWrap<ArrayChunked> {
540    fn bit_repr(&self) -> Option<BitRepr> {
541        None
542    }
543}
544impl private::PrivateSeriesNumeric for SeriesWrap<BooleanChunked> {
545    fn bit_repr(&self) -> Option<BitRepr> {
546        let repr = self
547            .0
548            .cast_with_options(&DataType::UInt32, CastOptions::NonStrict)
549            .unwrap()
550            .u32()
551            .unwrap()
552            .clone();
553
554        Some(BitRepr::U32(repr))
555    }
556}
polars_core/series/implementations/mod.rs

polars_core/series/implementations/
mod.rs
