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

polars_core/series/implementations/
mod.rs
