1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
607
608
609
610
611
612
613
614
615
616
617
618
619
620
621
622
623
624
625
626
627
628
629
630
631
632
633
634
635
636
637
638
639
640
641
642
643
644
645
646
647
648
649
650
651
652
653
654
655
656
657
658
659
660
661
662
663
664
665
666
667
668
669
670
671
672
673
674
675
676
677
678
679
680
681
682
683
684
685
686
687
688
689
690
691
692
693
694
695
696
697
698
699
700
701
702
703
704
705
706
707
708
709
710
711
712
713
714
715
716
717
718
719
720
721
722
723
724
725
726
727
728
729
730
731
732
733
734
735
736
737
738
739
740
741
742
743
744
745
746
747
748
749
750
751
752
753
754
755
756
757
758
759
760
761
762
763
764
765
766
767
768
769
770
771
772
773
774
775
776
777
778
779
780
781
782
783
784
785
786
787
788
789
790
791
792
793
794
795
796
797
798
799
800
801
802
803
804
805
806
807
808
809
810
811
812
813
814
815
816
817
818
819
820
821
822
823
824
825
826
827
828
829
830
831
832
833
834
835
836
837
838
839
840
841
842
843
844
845
846
847
848
849
850
851
852
853
854
855
856
857
858
859
860
861
862
863
864
865
866
867
868
869
870
871
872
873
874
875
876
877
878
879
880
881
882
883
884
885
886
887
888
889
890
891
892
893
894
895
896
897
898
899
900
901
902
903
904
905
906
907
908
909
910
911
912
913
914
915
916
917
918
919
920
921
922
923
924
925
926
927
928
929
930
931
932
933
934
935
936
937
938
939
940
941
942
943
944
945
946
947
948
949
950
951
952
953
954
955
956
957
958
959
960
961
962
963
964
965
966
967
968
969
970
971
972
973
974
975
976
977
978
979
980
981
982
983
984
985
986
987
988
989
990
991
992
993
994
995
996
997
998
999
1000
1001
1002
1003
1004
1005
1006
1007
1008
1009
1010
1011
1012
1013
1014
1015
1016
1017
1018
1019
1020
1021
1022
1023
1024
1025
1026
1027
1028
1029
1030
1031
1032
1033
1034
1035
1036
1037
1038
1039
1040
1041
1042
1043
1044
1045
1046
1047
1048
1049
1050
1051
1052
1053
1054
1055
1056
1057
1058
1059
1060
1061
1062
1063
1064
1065
1066
1067
1068
1069
1070
1071
1072
1073
1074
1075
1076
1077
1078
1079
1080
1081
1082
1083
1084
1085
1086
1087
1088
1089
1090
1091
1092
1093
1094
1095
1096
1097
1098
1099
1100
1101
1102
1103
1104
1105
1106
1107
1108
1109
1110
1111
1112
1113
1114
1115
1116
1117
1118
1119
1120
1121
1122
1123
1124
1125
1126
1127
1128
1129
1130
1131
1132
1133
1134
1135
1136
1137
1138
1139
1140
1141
1142
1143
1144
1145
1146
1147
1148
1149
1150
1151
1152
1153
1154
1155
1156
1157
1158
1159
1160
1161
1162
1163
1164
1165
1166
1167
1168
1169
1170
1171
1172
1173
1174
1175
1176
1177
1178
1179
1180
1181
1182
1183
1184
1185
1186
1187
1188
1189
1190
1191
1192
1193
1194
1195
1196
1197
1198
1199
1200
1201
1202
1203
1204
1205
1206
1207
1208
1209
1210
1211
1212
1213
1214
1215
1216
1217
1218
1219
1220
1221
1222
1223
1224
1225
1226
1227
1228
1229
1230
1231
1232
1233
1234
1235
1236
1237
1238
1239
1240
1241
1242
1243
1244
1245
1246
1247
1248
1249
1250
1251
1252
1253
1254
1255
1256
1257
1258
1259
1260
1261
1262
1263
1264
1265
1266
1267
1268
1269
1270
1271
1272
1273
1274
1275
1276
1277
1278
1279
1280
1281
1282
1283
1284
1285
1286
1287
1288
1289
1290
1291
1292
1293
1294
1295
1296
1297
1298
1299
1300
1301
1302
1303
1304
1305
1306
1307
1308
1309
1310
1311
1312
1313
1314
1315
1316
1317
1318
1319
1320
1321
1322
1323
1324
1325
1326
1327
1328
1329
1330
1331
1332
1333
1334
1335
1336
1337
1338
1339
1340
1341
1342
1343
1344
1345
1346
1347
1348
1349
1350
1351
1352
1353
1354
1355
1356
1357
1358
1359
1360
1361
1362
1363
1364
1365
1366
1367
1368
1369
1370
1371
1372
1373
1374
1375
1376
1377
1378
1379
1380
1381
1382
1383
1384
1385
1386
1387
1388
1389
1390
1391
1392
1393
1394
1395
1396
1397
1398
1399
1400
1401
1402
1403
1404
1405
1406
1407
1408
1409
1410
1411
1412
1413
1414
1415
1416
1417
1418
1419
1420
1421
1422
1423
1424
1425
1426
1427
1428
1429
1430
1431
1432
1433
1434
1435
1436
1437
1438
1439
1440
1441
1442
1443
1444
1445
1446
1447
1448
1449
1450
1451
1452
1453
1454
1455
1456
1457
1458
1459
1460
1461
1462
1463
1464
1465
1466
1467
1468
1469
1470
1471
1472
1473
1474
1475
1476
1477
1478
1479
1480
1481
1482
1483
1484
1485
1486
1487
1488
1489
1490
1491
1492
1493
1494
1495
1496
1497
1498
1499
1500
1501
1502
1503
1504
1505
1506
1507
1508
1509
1510
1511
1512
1513
1514
1515
1516
1517
1518
1519
1520
1521
1522
1523
1524
1525
1526
1527
1528
1529
1530
1531
1532
1533
1534
1535
1536
1537
1538
1539
1540
1541
1542
1543
1544
1545
1546
1547
1548
1549
1550
1551
1552
1553
1554
1555
1556
1557
1558
1559
1560
1561
1562
1563
1564
1565
1566
1567
1568
1569
1570
1571
1572
1573
1574
1575
1576
1577
1578
1579
1580
1581
1582
1583
1584
1585
1586
1587
1588
1589
1590
1591
1592
1593
1594
1595
1596
1597
1598
1599
1600
1601
1602
1603
1604
1605
1606
1607
1608
1609
1610
1611
1612
1613
1614
1615
1616
1617
1618
1619
1620
1621
1622
1623
1624
1625
1626
1627
1628
1629
1630
1631
1632
1633
1634
1635
1636
1637
1638
1639
1640
1641
1642
1643
1644
1645
1646
1647
1648
1649
1650
1651
1652
1653
1654
1655
1656
1657
1658
1659
1660
1661
1662
1663
1664
1665
1666
1667
1668
1669
1670
1671
1672
1673
1674
1675
1676
1677
1678
1679
1680
1681
1682
1683
1684
1685
1686
1687
1688
1689
1690
1691
1692
1693
1694
1695
1696
1697
1698
1699
1700
1701
1702
1703
1704
1705
1706
1707
1708
1709
1710
1711
1712
1713
1714
1715
1716
1717
1718
1719
1720
1721
1722
1723
1724
1725
1726
1727
1728
1729
1730
1731
1732
1733
1734
1735
1736
1737
1738
1739
1740
1741
1742
1743
1744
1745
1746
1747
1748
1749
1750
1751
1752
1753
1754
1755
1756
1757
1758
1759
1760
1761
1762
1763
1764
1765
1766
1767
1768
1769
1770
1771
1772
1773
1774
1775
1776
1777
1778
1779
1780
1781
1782
1783
1784
1785
1786
1787
1788
1789
1790
1791
1792
1793
1794
1795
1796
1797
1798
1799
1800
1801
1802
1803
1804
1805
1806
1807
1808
1809
1810
1811
1812
1813
1814
1815
1816
1817
1818
1819
1820
1821
1822
1823
1824
1825
1826
1827
1828
1829
1830
1831
1832
1833
1834
1835
1836
1837
1838
1839
1840
1841
1842
1843
1844
1845
1846
1847
1848
1849
1850
1851
1852
1853
1854
1855
1856
1857
1858
1859
1860
1861
1862
1863
1864
1865
1866
1867
1868
1869
1870
1871
1872
1873
1874
1875
1876
1877
1878
1879
1880
1881
1882
1883
1884
1885
1886
1887
1888
1889
1890
1891
1892
1893
1894
1895
1896
1897
1898
1899
1900
1901
1902
1903
1904
1905
1906
1907
1908
1909
1910
1911
1912
1913
1914
1915
1916
1917
1918
1919
1920
1921
1922
1923
1924
1925
1926
1927
1928
1929
1930
1931
1932
1933
1934
1935
1936
1937
1938
1939
1940
1941
1942
1943
1944
1945
1946
1947
1948
1949
1950
1951
1952
1953
1954
1955
1956
1957
1958
1959
1960
1961
1962
1963
1964
1965
1966
1967
1968
1969
1970
1971
1972
1973
1974
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
2024
2025
2026
2027
2028
2029
2030
2031
2032
2033
2034
2035
2036
2037
2038
2039
2040
2041
2042
2043
2044
2045
2046
2047
2048
2049
2050
2051
2052
2053
2054
2055
2056
2057
2058
2059
2060
2061
2062
2063
2064
2065
2066
2067
2068
2069
2070
2071
2072
2073
2074
2075
2076
2077
2078
2079
2080
2081
2082
2083
2084
2085
2086
2087
2088
2089
2090
2091
2092
2093
2094
2095
2096
2097
2098
2099
2100
2101
2102
2103
2104
2105
2106
2107
2108
2109
2110
2111
2112
2113
2114
2115
2116
2117
2118
2119
2120
2121
2122
2123
2124
2125
2126
2127
2128
2129
2130
2131
2132
2133
2134
2135
2136
2137
2138
2139
2140
2141
2142
2143
2144
2145
2146
2147
2148
2149
2150
2151
2152
2153
2154
2155
2156
2157
2158
2159
2160
2161
2162
2163
2164
2165
2166
2167
2168
2169
2170
2171
2172
2173
2174
2175
2176
2177
2178
2179
2180
2181
2182
2183
2184
2185
2186
2187
2188
2189
2190
2191
2192
2193
2194
2195
2196
2197
2198
2199
2200
2201
2202
2203
2204
2205
2206
2207
2208
2209
2210
2211
2212
2213
2214
2215
2216
2217
2218
2219
2220
2221
2222
2223
2224
2225
2226
2227
2228
2229
2230
2231
2232
2233
2234
2235
2236
2237
2238
2239
2240
2241
2242
2243
2244
2245
2246
2247
2248
2249
2250
2251
2252
2253
2254
2255
2256
2257
2258
2259
2260
2261
2262
2263
2264
2265
2266
2267
2268
2269
2270
2271
2272
2273
2274
2275
2276
2277
2278
2279
2280
2281
2282
2283
2284
2285
2286
2287
2288
2289
2290
2291
2292
2293
2294
2295
2296
2297
2298
2299
2300
2301
2302
2303
2304
2305
2306
2307
2308
2309
2310
2311
2312
2313
2314
2315
2316
2317
2318
2319
2320
2321
2322
2323
2324
2325
2326
2327
2328
2329
2330
2331
2332
2333
2334
2335
2336
2337
2338
2339
2340
2341
2342
2343
2344
2345
2346
2347
2348
2349
2350
2351
2352
2353
2354
2355
2356
2357
2358
2359
2360
2361
2362
2363
2364
2365
2366
2367
2368
2369
2370
2371
2372
2373
2374
2375
2376
2377
2378
2379
2380
2381
2382
2383
2384
2385
2386
2387
2388
2389
2390
2391
2392
2393
2394
2395
2396
2397
2398
2399
2400
2401
2402
2403
2404
2405
2406
2407
2408
2409
2410
2411
2412
2413
2414
2415
2416
2417
2418
2419
2420
2421
2422
2423
2424
2425
2426
2427
2428
2429
2430
2431
2432
2433
2434
2435
2436
2437
2438
2439
2440
2441
2442
2443
2444
2445
2446
2447
2448
2449
2450
2451
2452
2453
2454
2455
2456
2457
2458
2459
2460
2461
2462
2463
2464
2465
2466
2467
2468
2469
2470
2471
2472
2473
2474
2475
2476
2477
2478
2479
2480
2481
2482
2483
2484
2485
2486
2487
2488
2489
2490
2491
2492
2493
2494
2495
2496
2497
2498
2499
2500
2501
2502
2503
2504
2505
2506
2507
2508
2509
2510
2511
2512
2513
2514
2515
2516
2517
2518
2519
2520
2521
2522
2523
2524
2525
2526
2527
2528
2529
2530
2531
2532
2533
2534
2535
2536
2537
2538
2539
2540
2541
2542
2543
2544
2545
2546
2547
2548
2549
2550
2551
2552
2553
2554
2555
2556
2557
2558
2559
2560
2561
2562
2563
2564
2565
2566
2567
2568
2569
2570
2571
2572
2573
2574
2575
2576
2577
2578
2579
2580
2581
2582
2583
2584
2585
2586
2587
2588
2589
2590
2591
2592
2593
2594
2595
2596
2597
2598
2599
2600
2601
2602
2603
2604
2605
2606
2607
2608
2609
2610
2611
2612
2613
2614
2615
2616
2617
2618
2619
2620
2621
2622
2623
2624
2625
2626
2627
2628
2629
2630
2631
2632
2633
2634
2635
2636
2637
2638
2639
2640
2641
2642
2643
2644
2645
2646
2647
2648
2649
2650
2651
2652
2653
2654
2655
2656
2657
2658
2659
2660
2661
2662
2663
2664
2665
2666
2667
2668
2669
2670
2671
2672
2673
2674
2675
2676
2677
2678
2679
2680
2681
2682
2683
2684
2685
2686
2687
2688
2689
2690
2691
2692
2693
2694
2695
2696
2697
2698
2699
2700
2701
2702
2703
2704
2705
2706
2707
2708
2709
2710
2711
2712
2713
2714
2715
2716
2717
2718
2719
2720
2721
2722
2723
2724
2725
2726
2727
2728
2729
2730
2731
2732
2733
2734
2735
2736
2737
2738
2739
2740
2741
2742
2743
2744
2745
2746
2747
2748
2749
2750
2751
2752
2753
2754
2755
2756
2757
2758
2759
2760
2761
2762
2763
2764
2765
2766
2767
2768
2769
2770
2771
2772
2773
2774
2775
2776
2777
2778
2779
2780
2781
2782
2783
2784
2785
2786
2787
2788
2789
2790
2791
2792
2793
2794
2795
2796
2797
2798
2799
2800
2801
2802
2803
2804
2805
2806
2807
2808
2809
2810
2811
2812
2813
2814
2815
2816
2817
2818
2819
2820
2821
2822
2823
2824
2825
2826
2827
2828
2829
2830
2831
2832
2833
2834
2835
2836
2837
2838
2839
2840
2841
2842
2843
2844
2845
2846
2847
2848
2849
2850
2851
2852
2853
2854
2855
2856
2857
2858
2859
2860
2861
2862
2863
2864
2865
2866
2867
2868
2869
2870
2871
2872
2873
2874
2875
2876
2877
2878
2879
2880
2881
2882
2883
2884
2885
2886
2887
2888
2889
2890
2891
2892
2893
2894
2895
2896
2897
2898
2899
2900
2901
2902
2903
2904
2905
2906
2907
2908
2909
2910
2911
2912
2913
2914
2915
2916
2917
2918
2919
2920
2921
2922
2923
2924
2925
2926
2927
2928
2929
2930
2931
2932
2933
2934
2935
2936
2937
2938
2939
2940
2941
2942
2943
2944
2945
2946
2947
2948
2949
2950
2951
2952
2953
2954
2955
2956
2957
2958
2959
2960
2961
2962
2963
2964
2965
2966
2967
2968
2969
2970
2971
2972
2973
2974
2975
2976
2977
2978
2979
2980
2981
2982
2983
2984
2985
2986
2987
2988
2989
2990
2991
2992
2993
2994
2995
2996
2997
2998
2999
3000
3001
3002
3003
3004
3005
3006
3007
3008
3009
3010
3011
3012
3013
3014
3015
3016
3017
3018
3019
3020
3021
3022
3023
3024
3025
3026
3027
3028
3029
3030
3031
3032
3033
3034
3035
3036
3037
3038
3039
3040
3041
3042
3043
3044
3045
3046
3047
3048
3049
3050
3051
3052
3053
3054
3055
3056
3057
3058
3059
3060
3061
3062
3063
3064
3065
3066
3067
3068
3069
3070
3071
3072
3073
3074
3075
3076
3077
3078
3079
3080
3081
3082
3083
3084
3085
3086
3087
3088
3089
3090
3091
3092
3093
3094
3095
3096
3097
3098
3099
3100
3101
3102
3103
3104
3105
3106
3107
3108
3109
3110
3111
3112
3113
3114
3115
3116
3117
3118
3119
3120
3121
3122
3123
3124
3125
3126
3127
3128
3129
3130
3131
3132
3133
3134
3135
3136
3137
3138
3139
3140
3141
3142
3143
3144
3145
3146
3147
3148
3149
3150
3151
3152
3153
3154
3155
3156
3157
3158
3159
3160
3161
3162
3163
3164
3165
3166
3167
3168
3169
3170
3171
3172
3173
3174
3175
3176
3177
3178
3179
3180
3181
3182
3183
3184
3185
3186
3187
3188
3189
3190
3191
3192
3193
3194
3195
3196
3197
3198
3199
3200
3201
3202
3203
3204
3205
3206
3207
3208
3209
3210
3211
3212
3213
3214
3215
3216
3217
3218
3219
3220
3221
3222
3223
3224
3225
3226
3227
3228
3229
3230
3231
3232
3233
3234
3235
3236
3237
3238
3239
3240
3241
3242
3243
3244
3245
3246
3247
3248
3249
3250
3251
3252
3253
3254
3255
3256
3257
3258
3259
3260
3261
3262
3263
3264
3265
3266
3267
3268
3269
3270
3271
3272
3273
3274
3275
3276
3277
3278
3279
3280
3281
3282
3283
3284
3285
3286
3287
3288
3289
3290
3291
3292
3293
3294
3295
3296
3297
3298
3299
3300
3301
3302
3303
3304
3305
3306
3307
3308
3309
3310
//! Traits for writing parallel programs using an iterator-style interface
//!
//! You will rarely need to interact with this module directly unless you have
//! need to name one of the iterator types.
//!
//! Parallel iterators make it easy to write iterator-like chains that
//! execute in parallel: typically all you have to do is convert the
//! first `.iter()` (or `iter_mut()`, `into_iter()`, etc) method into
//! `par_iter()` (or `par_iter_mut()`, `into_par_iter()`, etc). For
//! example, to compute the sum of the squares of a sequence of
//! integers, one might write:
//!
//! ```rust
//! use rayon::prelude::*;
//! fn sum_of_squares(input: &[i32]) -> i32 {
//!     input.par_iter()
//!          .map(|i| i * i)
//!          .sum()
//! }
//! ```
//!
//! Or, to increment all the integers in a slice, you could write:
//!
//! ```rust
//! use rayon::prelude::*;
//! fn increment_all(input: &mut [i32]) {
//!     input.par_iter_mut()
//!          .for_each(|p| *p += 1);
//! }
//! ```
//!
//! To use parallel iterators, first import the traits by adding
//! something like `use rayon::prelude::*` to your module. You can
//! then call `par_iter`, `par_iter_mut`, or `into_par_iter` to get a
//! parallel iterator. Like a [regular iterator][], parallel
//! iterators work by first constructing a computation and then
//! executing it.
//!
//! In addition to `par_iter()` and friends, some types offer other
//! ways to create (or consume) parallel iterators:
//!
//! - Slices (`&[T]`, `&mut [T]`) offer methods like `par_split` and
//!   `par_windows`, as well as various parallel sorting
//!   operations. See [the `ParallelSlice` trait] for the full list.
//! - Strings (`&str`) offer methods like `par_split` and `par_lines`.
//!   See [the `ParallelString` trait] for the full list.
//! - Various collections offer [`par_extend`], which grows a
//!   collection given a parallel iterator. (If you don't have a
//!   collection to extend, you can use [`collect()`] to create a new
//!   one from scratch.)
//!
//! [the `ParallelSlice` trait]: ../slice/trait.ParallelSlice.html
//! [the `ParallelString` trait]: ../str/trait.ParallelString.html
//! [`par_extend`]: trait.ParallelExtend.html
//! [`collect()`]: trait.ParallelIterator.html#method.collect
//!
//! To see the full range of methods available on parallel iterators,
//! check out the [`ParallelIterator`] and [`IndexedParallelIterator`]
//! traits.
//!
//! If you'd like to build a custom parallel iterator, or to write your own
//! combinator, then check out the [split] function and the [plumbing] module.
//!
//! [regular iterator]: https://doc.rust-lang.org/std/iter/trait.Iterator.html
//! [`ParallelIterator`]: trait.ParallelIterator.html
//! [`IndexedParallelIterator`]: trait.IndexedParallelIterator.html
//! [split]: fn.split.html
//! [plumbing]: plumbing/index.html
//!
//! Note: Several of the `ParallelIterator` methods rely on a `Try` trait which
//! has been deliberately obscured from the public API.  This trait is intended
//! to mirror the unstable `std::ops::Try` with implementations for `Option` and
//! `Result`, where `Some`/`Ok` values will let those iterators continue, but
//! `None`/`Err` values will exit early.
//!
//! A note about object safety: It is currently _not_ possible to wrap
//! a `ParallelIterator` (or any trait that depends on it) using a
//! `Box<dyn ParallelIterator>` or other kind of dynamic allocation,
//! because `ParallelIterator` is **not object-safe**.
//! (This keeps the implementation simpler and allows extra optimizations.)

use self::plumbing::*;
use self::private::Try;
pub use either::Either;
use std::cmp::{self, Ordering};
use std::iter::{Product, Sum};
use std::ops::{Fn, RangeBounds};

pub mod plumbing;

#[cfg(test)]
mod test;

// There is a method to the madness here:
//
// - These modules are private but expose certain types to the end-user
//   (e.g., `enumerate::Enumerate`) -- specifically, the types that appear in the
//   public API surface of the `ParallelIterator` traits.
// - In **this** module, those public types are always used unprefixed, which forces
//   us to add a `pub use` and helps identify if we missed anything.
// - In contrast, items that appear **only** in the body of a method,
//   e.g. `find::find()`, are always used **prefixed**, so that they
//   can be readily distinguished.

mod chain;
mod chunks;
mod cloned;
mod collect;
mod copied;
mod empty;
mod enumerate;
mod extend;
mod filter;
mod filter_map;
mod find;
mod find_first_last;
mod flat_map;
mod flat_map_iter;
mod flatten;
mod flatten_iter;
mod fold;
mod for_each;
mod from_par_iter;
mod inspect;
mod interleave;
mod interleave_shortest;
mod intersperse;
mod len;
mod map;
mod map_with;
mod multizip;
mod noop;
mod once;
mod panic_fuse;
mod par_bridge;
mod positions;
mod product;
mod reduce;
mod repeat;
mod rev;
mod skip;
mod splitter;
mod sum;
mod take;
mod try_fold;
mod try_reduce;
mod try_reduce_with;
mod unzip;
mod update;
mod while_some;
mod zip;
mod zip_eq;

pub use self::{
    chain::Chain,
    chunks::Chunks,
    cloned::Cloned,
    copied::Copied,
    empty::{empty, Empty},
    enumerate::Enumerate,
    filter::Filter,
    filter_map::FilterMap,
    flat_map::FlatMap,
    flat_map_iter::FlatMapIter,
    flatten::Flatten,
    flatten_iter::FlattenIter,
    fold::{Fold, FoldWith},
    inspect::Inspect,
    interleave::Interleave,
    interleave_shortest::InterleaveShortest,
    intersperse::Intersperse,
    len::{MaxLen, MinLen},
    map::Map,
    map_with::{MapInit, MapWith},
    multizip::MultiZip,
    once::{once, Once},
    panic_fuse::PanicFuse,
    par_bridge::{IterBridge, ParallelBridge},
    positions::Positions,
    repeat::{repeat, repeatn, Repeat, RepeatN},
    rev::Rev,
    skip::Skip,
    splitter::{split, Split},
    take::Take,
    try_fold::{TryFold, TryFoldWith},
    update::Update,
    while_some::WhileSome,
    zip::Zip,
    zip_eq::ZipEq,
};

mod step_by;
#[cfg(has_step_by_rev)]
pub use self::step_by::StepBy;

/// `IntoParallelIterator` implements the conversion to a [`ParallelIterator`].
///
/// By implementing `IntoParallelIterator` for a type, you define how it will
/// transformed into an iterator. This is a parallel version of the standard
/// library's [`std::iter::IntoIterator`] trait.
///
/// [`ParallelIterator`]: trait.ParallelIterator.html
/// [`std::iter::IntoIterator`]: https://doc.rust-lang.org/std/iter/trait.IntoIterator.html
pub trait IntoParallelIterator {
    /// The parallel iterator type that will be created.
    type Iter: ParallelIterator<Item = Self::Item>;

    /// The type of item that the parallel iterator will produce.
    type Item: Send;

    /// Converts `self` into a parallel iterator.
    ///
    /// # Examples
    ///
    /// ```
    /// use rayon::prelude::*;
    ///
    /// println!("counting in parallel:");
    /// (0..100).into_par_iter()
    ///     .for_each(|i| println!("{}", i));
    /// ```
    ///
    /// This conversion is often implicit for arguments to methods like [`zip`].
    ///
    /// ```
    /// use rayon::prelude::*;
    ///
    /// let v: Vec<_> = (0..5).into_par_iter().zip(5..10).collect();
    /// assert_eq!(v, [(0, 5), (1, 6), (2, 7), (3, 8), (4, 9)]);
    /// ```
    ///
    /// [`zip`]: trait.IndexedParallelIterator.html#method.zip
    fn into_par_iter(self) -> Self::Iter;
}

/// `IntoParallelRefIterator` implements the conversion to a
/// [`ParallelIterator`], providing shared references to the data.
///
/// This is a parallel version of the `iter()` method
/// defined by various collections.
///
/// This trait is automatically implemented
/// `for I where &I: IntoParallelIterator`. In most cases, users
/// will want to implement [`IntoParallelIterator`] rather than implement
/// this trait directly.
///
/// [`ParallelIterator`]: trait.ParallelIterator.html
/// [`IntoParallelIterator`]: trait.IntoParallelIterator.html
pub trait IntoParallelRefIterator<'data> {
    /// The type of the parallel iterator that will be returned.
    type Iter: ParallelIterator<Item = Self::Item>;

    /// The type of item that the parallel iterator will produce.
    /// This will typically be an `&'data T` reference type.
    type Item: Send + 'data;

    /// Converts `self` into a parallel iterator.
    ///
    /// # Examples
    ///
    /// ```
    /// use rayon::prelude::*;
    ///
    /// let v: Vec<_> = (0..100).collect();
    /// assert_eq!(v.par_iter().sum::<i32>(), 100 * 99 / 2);
    ///
    /// // `v.par_iter()` is shorthand for `(&v).into_par_iter()`,
    /// // producing the exact same references.
    /// assert!(v.par_iter().zip(&v)
    ///          .all(|(a, b)| std::ptr::eq(a, b)));
    /// ```
    fn par_iter(&'data self) -> Self::Iter;
}

impl<'data, I: 'data + ?Sized> IntoParallelRefIterator<'data> for I
where
    &'data I: IntoParallelIterator,
{
    type Iter = <&'data I as IntoParallelIterator>::Iter;
    type Item = <&'data I as IntoParallelIterator>::Item;

    fn par_iter(&'data self) -> Self::Iter {
        self.into_par_iter()
    }
}

/// `IntoParallelRefMutIterator` implements the conversion to a
/// [`ParallelIterator`], providing mutable references to the data.
///
/// This is a parallel version of the `iter_mut()` method
/// defined by various collections.
///
/// This trait is automatically implemented
/// `for I where &mut I: IntoParallelIterator`. In most cases, users
/// will want to implement [`IntoParallelIterator`] rather than implement
/// this trait directly.
///
/// [`ParallelIterator`]: trait.ParallelIterator.html
/// [`IntoParallelIterator`]: trait.IntoParallelIterator.html
pub trait IntoParallelRefMutIterator<'data> {
    /// The type of iterator that will be created.
    type Iter: ParallelIterator<Item = Self::Item>;

    /// The type of item that will be produced; this is typically an
    /// `&'data mut T` reference.
    type Item: Send + 'data;

    /// Creates the parallel iterator from `self`.
    ///
    /// # Examples
    ///
    /// ```
    /// use rayon::prelude::*;
    ///
    /// let mut v = vec![0usize; 5];
    /// v.par_iter_mut().enumerate().for_each(|(i, x)| *x = i);
    /// assert_eq!(v, [0, 1, 2, 3, 4]);
    /// ```
    fn par_iter_mut(&'data mut self) -> Self::Iter;
}

impl<'data, I: 'data + ?Sized> IntoParallelRefMutIterator<'data> for I
where
    &'data mut I: IntoParallelIterator,
{
    type Iter = <&'data mut I as IntoParallelIterator>::Iter;
    type Item = <&'data mut I as IntoParallelIterator>::Item;

    fn par_iter_mut(&'data mut self) -> Self::Iter {
        self.into_par_iter()
    }
}

/// Parallel version of the standard iterator trait.
///
/// The combinators on this trait are available on **all** parallel
/// iterators.  Additional methods can be found on the
/// [`IndexedParallelIterator`] trait: those methods are only
/// available for parallel iterators where the number of items is
/// known in advance (so, e.g., after invoking `filter`, those methods
/// become unavailable).
///
/// For examples of using parallel iterators, see [the docs on the
/// `iter` module][iter].
///
/// [iter]: index.html
/// [`IndexedParallelIterator`]: trait.IndexedParallelIterator.html
pub trait ParallelIterator: Sized + Send {
    /// The type of item that this parallel iterator produces.
    /// For example, if you use the [`for_each`] method, this is the type of
    /// item that your closure will be invoked with.
    ///
    /// [`for_each`]: #method.for_each
    type Item: Send;

    /// Executes `OP` on each item produced by the iterator, in parallel.
    ///
    /// # Examples
    ///
    /// ```
    /// use rayon::prelude::*;
    ///
    /// (0..100).into_par_iter().for_each(|x| println!("{:?}", x));
    /// ```
    fn for_each<OP>(self, op: OP)
    where
        OP: Fn(Self::Item) + Sync + Send,
    {
        for_each::for_each(self, &op)
    }

    /// Executes `OP` on the given `init` value with each item produced by
    /// the iterator, in parallel.
    ///
    /// The `init` value will be cloned only as needed to be paired with
    /// the group of items in each rayon job.  It does not require the type
    /// to be `Sync`.
    ///
    /// # Examples
    ///
    /// ```
    /// use std::sync::mpsc::channel;
    /// use rayon::prelude::*;
    ///
    /// let (sender, receiver) = channel();
    ///
    /// (0..5).into_par_iter().for_each_with(sender, |s, x| s.send(x).unwrap());
    ///
    /// let mut res: Vec<_> = receiver.iter().collect();
    ///
    /// res.sort();
    ///
    /// assert_eq!(&res[..], &[0, 1, 2, 3, 4])
    /// ```
    fn for_each_with<OP, T>(self, init: T, op: OP)
    where
        OP: Fn(&mut T, Self::Item) + Sync + Send,
        T: Send + Clone,
    {
        self.map_with(init, op).collect()
    }

    /// Executes `OP` on a value returned by `init` with each item produced by
    /// the iterator, in parallel.
    ///
    /// The `init` function will be called only as needed for a value to be
    /// paired with the group of items in each rayon job.  There is no
    /// constraint on that returned type at all!
    ///
    /// # Examples
    ///
    /// ```
    /// use rand::Rng;
    /// use rayon::prelude::*;
    ///
    /// let mut v = vec![0u8; 1_000_000];
    ///
    /// v.par_chunks_mut(1000)
    ///     .for_each_init(
    ///         || rand::thread_rng(),
    ///         |rng, chunk| rng.fill(chunk),
    ///     );
    ///
    /// // There's a remote chance that this will fail...
    /// for i in 0u8..=255 {
    ///     assert!(v.contains(&i));
    /// }
    /// ```
    fn for_each_init<OP, INIT, T>(self, init: INIT, op: OP)
    where
        OP: Fn(&mut T, Self::Item) + Sync + Send,
        INIT: Fn() -> T + Sync + Send,
    {
        self.map_init(init, op).collect()
    }

    /// Executes a fallible `OP` on each item produced by the iterator, in parallel.
    ///
    /// If the `OP` returns `Result::Err` or `Option::None`, we will attempt to
    /// stop processing the rest of the items in the iterator as soon as
    /// possible, and we will return that terminating value.  Otherwise, we will
    /// return an empty `Result::Ok(())` or `Option::Some(())`.  If there are
    /// multiple errors in parallel, it is not specified which will be returned.
    ///
    /// # Examples
    ///
    /// ```
    /// use rayon::prelude::*;
    /// use std::io::{self, Write};
    ///
    /// // This will stop iteration early if there's any write error, like
    /// // having piped output get closed on the other end.
    /// (0..100).into_par_iter()
    ///     .try_for_each(|x| writeln!(io::stdout(), "{:?}", x))
    ///     .expect("expected no write errors");
    /// ```
    fn try_for_each<OP, R>(self, op: OP) -> R
    where
        OP: Fn(Self::Item) -> R + Sync + Send,
        R: Try<Output = ()> + Send,
    {
        fn ok<R: Try<Output = ()>>(_: (), _: ()) -> R {
            R::from_output(())
        }

        self.map(op).try_reduce(<()>::default, ok)
    }

    /// Executes a fallible `OP` on the given `init` value with each item
    /// produced by the iterator, in parallel.
    ///
    /// This combines the `init` semantics of [`for_each_with()`] and the
    /// failure semantics of [`try_for_each()`].
    ///
    /// [`for_each_with()`]: #method.for_each_with
    /// [`try_for_each()`]: #method.try_for_each
    ///
    /// # Examples
    ///
    /// ```
    /// use std::sync::mpsc::channel;
    /// use rayon::prelude::*;
    ///
    /// let (sender, receiver) = channel();
    ///
    /// (0..5).into_par_iter()
    ///     .try_for_each_with(sender, |s, x| s.send(x))
    ///     .expect("expected no send errors");
    ///
    /// let mut res: Vec<_> = receiver.iter().collect();
    ///
    /// res.sort();
    ///
    /// assert_eq!(&res[..], &[0, 1, 2, 3, 4])
    /// ```
    fn try_for_each_with<OP, T, R>(self, init: T, op: OP) -> R
    where
        OP: Fn(&mut T, Self::Item) -> R + Sync + Send,
        T: Send + Clone,
        R: Try<Output = ()> + Send,
    {
        fn ok<R: Try<Output = ()>>(_: (), _: ()) -> R {
            R::from_output(())
        }

        self.map_with(init, op).try_reduce(<()>::default, ok)
    }

    /// Executes a fallible `OP` on a value returned by `init` with each item
    /// produced by the iterator, in parallel.
    ///
    /// This combines the `init` semantics of [`for_each_init()`] and the
    /// failure semantics of [`try_for_each()`].
    ///
    /// [`for_each_init()`]: #method.for_each_init
    /// [`try_for_each()`]: #method.try_for_each
    ///
    /// # Examples
    ///
    /// ```
    /// use rand::Rng;
    /// use rayon::prelude::*;
    ///
    /// let mut v = vec![0u8; 1_000_000];
    ///
    /// v.par_chunks_mut(1000)
    ///     .try_for_each_init(
    ///         || rand::thread_rng(),
    ///         |rng, chunk| rng.try_fill(chunk),
    ///     )
    ///     .expect("expected no rand errors");
    ///
    /// // There's a remote chance that this will fail...
    /// for i in 0u8..=255 {
    ///     assert!(v.contains(&i));
    /// }
    /// ```
    fn try_for_each_init<OP, INIT, T, R>(self, init: INIT, op: OP) -> R
    where
        OP: Fn(&mut T, Self::Item) -> R + Sync + Send,
        INIT: Fn() -> T + Sync + Send,
        R: Try<Output = ()> + Send,
    {
        fn ok<R: Try<Output = ()>>(_: (), _: ()) -> R {
            R::from_output(())
        }

        self.map_init(init, op).try_reduce(<()>::default, ok)
    }

    /// Counts the number of items in this parallel iterator.
    ///
    /// # Examples
    ///
    /// ```
    /// use rayon::prelude::*;
    ///
    /// let count = (0..100).into_par_iter().count();
    ///
    /// assert_eq!(count, 100);
    /// ```
    fn count(self) -> usize {
        fn one<T>(_: T) -> usize {
            1
        }

        self.map(one).sum()
    }

    /// Applies `map_op` to each item of this iterator, producing a new
    /// iterator with the results.
    ///
    /// # Examples
    ///
    /// ```
    /// use rayon::prelude::*;
    ///
    /// let mut par_iter = (0..5).into_par_iter().map(|x| x * 2);
    ///
    /// let doubles: Vec<_> = par_iter.collect();
    ///
    /// assert_eq!(&doubles[..], &[0, 2, 4, 6, 8]);
    /// ```
    fn map<F, R>(self, map_op: F) -> Map<Self, F>
    where
        F: Fn(Self::Item) -> R + Sync + Send,
        R: Send,
    {
        Map::new(self, map_op)
    }

    /// Applies `map_op` to the given `init` value with each item of this
    /// iterator, producing a new iterator with the results.
    ///
    /// The `init` value will be cloned only as needed to be paired with
    /// the group of items in each rayon job.  It does not require the type
    /// to be `Sync`.
    ///
    /// # Examples
    ///
    /// ```
    /// use std::sync::mpsc::channel;
    /// use rayon::prelude::*;
    ///
    /// let (sender, receiver) = channel();
    ///
    /// let a: Vec<_> = (0..5)
    ///                 .into_par_iter()            // iterating over i32
    ///                 .map_with(sender, |s, x| {
    ///                     s.send(x).unwrap();     // sending i32 values through the channel
    ///                     x                       // returning i32
    ///                 })
    ///                 .collect();                 // collecting the returned values into a vector
    ///
    /// let mut b: Vec<_> = receiver.iter()         // iterating over the values in the channel
    ///                             .collect();     // and collecting them
    /// b.sort();
    ///
    /// assert_eq!(a, b);
    /// ```
    fn map_with<F, T, R>(self, init: T, map_op: F) -> MapWith<Self, T, F>
    where
        F: Fn(&mut T, Self::Item) -> R + Sync + Send,
        T: Send + Clone,
        R: Send,
    {
        MapWith::new(self, init, map_op)
    }

    /// Applies `map_op` to a value returned by `init` with each item of this
    /// iterator, producing a new iterator with the results.
    ///
    /// The `init` function will be called only as needed for a value to be
    /// paired with the group of items in each rayon job.  There is no
    /// constraint on that returned type at all!
    ///
    /// # Examples
    ///
    /// ```
    /// use rand::Rng;
    /// use rayon::prelude::*;
    ///
    /// let a: Vec<_> = (1i32..1_000_000)
    ///     .into_par_iter()
    ///     .map_init(
    ///         || rand::thread_rng(),  // get the thread-local RNG
    ///         |rng, x| if rng.gen() { // randomly negate items
    ///             -x
    ///         } else {
    ///             x
    ///         },
    ///     ).collect();
    ///
    /// // There's a remote chance that this will fail...
    /// assert!(a.iter().any(|&x| x < 0));
    /// assert!(a.iter().any(|&x| x > 0));
    /// ```
    fn map_init<F, INIT, T, R>(self, init: INIT, map_op: F) -> MapInit<Self, INIT, F>
    where
        F: Fn(&mut T, Self::Item) -> R + Sync + Send,
        INIT: Fn() -> T + Sync + Send,
        R: Send,
    {
        MapInit::new(self, init, map_op)
    }

    /// Creates an iterator which clones all of its elements.  This may be
    /// useful when you have an iterator over `&T`, but you need `T`, and
    /// that type implements `Clone`. See also [`copied()`].
    ///
    /// [`copied()`]: #method.copied
    ///
    /// # Examples
    ///
    /// ```
    /// use rayon::prelude::*;
    ///
    /// let a = [1, 2, 3];
    ///
    /// let v_cloned: Vec<_> = a.par_iter().cloned().collect();
    ///
    /// // cloned is the same as .map(|&x| x), for integers
    /// let v_map: Vec<_> = a.par_iter().map(|&x| x).collect();
    ///
    /// assert_eq!(v_cloned, vec![1, 2, 3]);
    /// assert_eq!(v_map, vec![1, 2, 3]);
    /// ```
    fn cloned<'a, T>(self) -> Cloned<Self>
    where
        T: 'a + Clone + Send,
        Self: ParallelIterator<Item = &'a T>,
    {
        Cloned::new(self)
    }

    /// Creates an iterator which copies all of its elements.  This may be
    /// useful when you have an iterator over `&T`, but you need `T`, and
    /// that type implements `Copy`. See also [`cloned()`].
    ///
    /// [`cloned()`]: #method.cloned
    ///
    /// # Examples
    ///
    /// ```
    /// use rayon::prelude::*;
    ///
    /// let a = [1, 2, 3];
    ///
    /// let v_copied: Vec<_> = a.par_iter().copied().collect();
    ///
    /// // copied is the same as .map(|&x| x), for integers
    /// let v_map: Vec<_> = a.par_iter().map(|&x| x).collect();
    ///
    /// assert_eq!(v_copied, vec![1, 2, 3]);
    /// assert_eq!(v_map, vec![1, 2, 3]);
    /// ```
    fn copied<'a, T>(self) -> Copied<Self>
    where
        T: 'a + Copy + Send,
        Self: ParallelIterator<Item = &'a T>,
    {
        Copied::new(self)
    }

    /// Applies `inspect_op` to a reference to each item of this iterator,
    /// producing a new iterator passing through the original items.  This is
    /// often useful for debugging to see what's happening in iterator stages.
    ///
    /// # Examples
    ///
    /// ```
    /// use rayon::prelude::*;
    ///
    /// let a = [1, 4, 2, 3];
    ///
    /// // this iterator sequence is complex.
    /// let sum = a.par_iter()
    ///             .cloned()
    ///             .filter(|&x| x % 2 == 0)
    ///             .reduce(|| 0, |sum, i| sum + i);
    ///
    /// println!("{}", sum);
    ///
    /// // let's add some inspect() calls to investigate what's happening
    /// let sum = a.par_iter()
    ///             .cloned()
    ///             .inspect(|x| println!("about to filter: {}", x))
    ///             .filter(|&x| x % 2 == 0)
    ///             .inspect(|x| println!("made it through filter: {}", x))
    ///             .reduce(|| 0, |sum, i| sum + i);
    ///
    /// println!("{}", sum);
    /// ```
    fn inspect<OP>(self, inspect_op: OP) -> Inspect<Self, OP>
    where
        OP: Fn(&Self::Item) + Sync + Send,
    {
        Inspect::new(self, inspect_op)
    }

    /// Mutates each item of this iterator before yielding it.
    ///
    /// # Examples
    ///
    /// ```
    /// use rayon::prelude::*;
    ///
    /// let par_iter = (0..5).into_par_iter().update(|x| {*x *= 2;});
    ///
    /// let doubles: Vec<_> = par_iter.collect();
    ///
    /// assert_eq!(&doubles[..], &[0, 2, 4, 6, 8]);
    /// ```
    fn update<F>(self, update_op: F) -> Update<Self, F>
    where
        F: Fn(&mut Self::Item) + Sync + Send,
    {
        Update::new(self, update_op)
    }

    /// Applies `filter_op` to each item of this iterator, producing a new
    /// iterator with only the items that gave `true` results.
    ///
    /// # Examples
    ///
    /// ```
    /// use rayon::prelude::*;
    ///
    /// let mut par_iter = (0..10).into_par_iter().filter(|x| x % 2 == 0);
    ///
    /// let even_numbers: Vec<_> = par_iter.collect();
    ///
    /// assert_eq!(&even_numbers[..], &[0, 2, 4, 6, 8]);
    /// ```
    fn filter<P>(self, filter_op: P) -> Filter<Self, P>
    where
        P: Fn(&Self::Item) -> bool + Sync + Send,
    {
        Filter::new(self, filter_op)
    }

    /// Applies `filter_op` to each item of this iterator to get an `Option`,
    /// producing a new iterator with only the items from `Some` results.
    ///
    /// # Examples
    ///
    /// ```
    /// use rayon::prelude::*;
    ///
    /// let mut par_iter = (0..10).into_par_iter()
    ///                         .filter_map(|x| {
    ///                             if x % 2 == 0 { Some(x * 3) }
    ///                             else { None }
    ///                         });
    ///
    /// let even_numbers: Vec<_> = par_iter.collect();
    ///
    /// assert_eq!(&even_numbers[..], &[0, 6, 12, 18, 24]);
    /// ```
    fn filter_map<P, R>(self, filter_op: P) -> FilterMap<Self, P>
    where
        P: Fn(Self::Item) -> Option<R> + Sync + Send,
        R: Send,
    {
        FilterMap::new(self, filter_op)
    }

    /// Applies `map_op` to each item of this iterator to get nested parallel iterators,
    /// producing a new parallel iterator that flattens these back into one.
    ///
    /// See also [`flat_map_iter`](#method.flat_map_iter).
    ///
    /// # Examples
    ///
    /// ```
    /// use rayon::prelude::*;
    ///
    /// let a = [[1, 2], [3, 4], [5, 6], [7, 8]];
    ///
    /// let par_iter = a.par_iter().cloned().flat_map(|a| a.to_vec());
    ///
    /// let vec: Vec<_> = par_iter.collect();
    ///
    /// assert_eq!(&vec[..], &[1, 2, 3, 4, 5, 6, 7, 8]);
    /// ```
    fn flat_map<F, PI>(self, map_op: F) -> FlatMap<Self, F>
    where
        F: Fn(Self::Item) -> PI + Sync + Send,
        PI: IntoParallelIterator,
    {
        FlatMap::new(self, map_op)
    }

    /// Applies `map_op` to each item of this iterator to get nested serial iterators,
    /// producing a new parallel iterator that flattens these back into one.
    ///
    /// # `flat_map_iter` versus `flat_map`
    ///
    /// These two methods are similar but behave slightly differently. With [`flat_map`],
    /// each of the nested iterators must be a parallel iterator, and they will be further
    /// split up with nested parallelism. With `flat_map_iter`, each nested iterator is a
    /// sequential `Iterator`, and we only parallelize _between_ them, while the items
    /// produced by each nested iterator are processed sequentially.
    ///
    /// When choosing between these methods, consider whether nested parallelism suits the
    /// potential iterators at hand. If there's little computation involved, or its length
    /// is much less than the outer parallel iterator, then it may perform better to avoid
    /// the overhead of parallelism, just flattening sequentially with `flat_map_iter`.
    /// If there is a lot of computation, potentially outweighing the outer parallel
    /// iterator, then the nested parallelism of `flat_map` may be worthwhile.
    ///
    /// [`flat_map`]: #method.flat_map
    ///
    /// # Examples
    ///
    /// ```
    /// use rayon::prelude::*;
    /// use std::cell::RefCell;
    ///
    /// let a = [[1, 2], [3, 4], [5, 6], [7, 8]];
    ///
    /// let par_iter = a.par_iter().flat_map_iter(|a| {
    ///     // The serial iterator doesn't have to be thread-safe, just its items.
    ///     let cell_iter = RefCell::new(a.iter().cloned());
    ///     std::iter::from_fn(move || cell_iter.borrow_mut().next())
    /// });
    ///
    /// let vec: Vec<_> = par_iter.collect();
    ///
    /// assert_eq!(&vec[..], &[1, 2, 3, 4, 5, 6, 7, 8]);
    /// ```
    fn flat_map_iter<F, SI>(self, map_op: F) -> FlatMapIter<Self, F>
    where
        F: Fn(Self::Item) -> SI + Sync + Send,
        SI: IntoIterator,
        SI::Item: Send,
    {
        FlatMapIter::new(self, map_op)
    }

    /// An adaptor that flattens parallel-iterable `Item`s into one large iterator.
    ///
    /// See also [`flatten_iter`](#method.flatten_iter).
    ///
    /// # Examples
    ///
    /// ```
    /// use rayon::prelude::*;
    ///
    /// let x: Vec<Vec<_>> = vec![vec![1, 2], vec![3, 4]];
    /// let y: Vec<_> = x.into_par_iter().flatten().collect();
    ///
    /// assert_eq!(y, vec![1, 2, 3, 4]);
    /// ```
    fn flatten(self) -> Flatten<Self>
    where
        Self::Item: IntoParallelIterator,
    {
        Flatten::new(self)
    }

    /// An adaptor that flattens serial-iterable `Item`s into one large iterator.
    ///
    /// See also [`flatten`](#method.flatten) and the analogous comparison of
    /// [`flat_map_iter` versus `flat_map`](#flat_map_iter-versus-flat_map).
    ///
    /// # Examples
    ///
    /// ```
    /// use rayon::prelude::*;
    ///
    /// let x: Vec<Vec<_>> = vec![vec![1, 2], vec![3, 4]];
    /// let iters: Vec<_> = x.into_iter().map(Vec::into_iter).collect();
    /// let y: Vec<_> = iters.into_par_iter().flatten_iter().collect();
    ///
    /// assert_eq!(y, vec![1, 2, 3, 4]);
    /// ```
    fn flatten_iter(self) -> FlattenIter<Self>
    where
        Self::Item: IntoIterator,
        <Self::Item as IntoIterator>::Item: Send,
    {
        FlattenIter::new(self)
    }

    /// Reduces the items in the iterator into one item using `op`.
    /// The argument `identity` should be a closure that can produce
    /// "identity" value which may be inserted into the sequence as
    /// needed to create opportunities for parallel execution. So, for
    /// example, if you are doing a summation, then `identity()` ought
    /// to produce something that represents the zero for your type
    /// (but consider just calling `sum()` in that case).
    ///
    /// # Examples
    ///
    /// ```
    /// // Iterate over a sequence of pairs `(x0, y0), ..., (xN, yN)`
    /// // and use reduce to compute one pair `(x0 + ... + xN, y0 + ... + yN)`
    /// // where the first/second elements are summed separately.
    /// use rayon::prelude::*;
    /// let sums = [(0, 1), (5, 6), (16, 2), (8, 9)]
    ///            .par_iter()        // iterating over &(i32, i32)
    ///            .cloned()          // iterating over (i32, i32)
    ///            .reduce(|| (0, 0), // the "identity" is 0 in both columns
    ///                    |a, b| (a.0 + b.0, a.1 + b.1));
    /// assert_eq!(sums, (0 + 5 + 16 + 8, 1 + 6 + 2 + 9));
    /// ```
    ///
    /// **Note:** unlike a sequential `fold` operation, the order in
    /// which `op` will be applied to reduce the result is not fully
    /// specified. So `op` should be [associative] or else the results
    /// will be non-deterministic. And of course `identity()` should
    /// produce a true identity.
    ///
    /// [associative]: https://en.wikipedia.org/wiki/Associative_property
    fn reduce<OP, ID>(self, identity: ID, op: OP) -> Self::Item
    where
        OP: Fn(Self::Item, Self::Item) -> Self::Item + Sync + Send,
        ID: Fn() -> Self::Item + Sync + Send,
    {
        reduce::reduce(self, identity, op)
    }

    /// Reduces the items in the iterator into one item using `op`.
    /// If the iterator is empty, `None` is returned; otherwise,
    /// `Some` is returned.
    ///
    /// This version of `reduce` is simple but somewhat less
    /// efficient. If possible, it is better to call `reduce()`, which
    /// requires an identity element.
    ///
    /// # Examples
    ///
    /// ```
    /// use rayon::prelude::*;
    /// let sums = [(0, 1), (5, 6), (16, 2), (8, 9)]
    ///            .par_iter()        // iterating over &(i32, i32)
    ///            .cloned()          // iterating over (i32, i32)
    ///            .reduce_with(|a, b| (a.0 + b.0, a.1 + b.1))
    ///            .unwrap();
    /// assert_eq!(sums, (0 + 5 + 16 + 8, 1 + 6 + 2 + 9));
    /// ```
    ///
    /// **Note:** unlike a sequential `fold` operation, the order in
    /// which `op` will be applied to reduce the result is not fully
    /// specified. So `op` should be [associative] or else the results
    /// will be non-deterministic.
    ///
    /// [associative]: https://en.wikipedia.org/wiki/Associative_property
    fn reduce_with<OP>(self, op: OP) -> Option<Self::Item>
    where
        OP: Fn(Self::Item, Self::Item) -> Self::Item + Sync + Send,
    {
        fn opt_fold<T>(op: impl Fn(T, T) -> T) -> impl Fn(Option<T>, T) -> Option<T> {
            move |opt_a, b| match opt_a {
                Some(a) => Some(op(a, b)),
                None => Some(b),
            }
        }

        fn opt_reduce<T>(op: impl Fn(T, T) -> T) -> impl Fn(Option<T>, Option<T>) -> Option<T> {
            move |opt_a, opt_b| match (opt_a, opt_b) {
                (Some(a), Some(b)) => Some(op(a, b)),
                (Some(v), None) | (None, Some(v)) => Some(v),
                (None, None) => None,
            }
        }

        self.fold(<_>::default, opt_fold(&op))
            .reduce(<_>::default, opt_reduce(&op))
    }

    /// Reduces the items in the iterator into one item using a fallible `op`.
    /// The `identity` argument is used the same way as in [`reduce()`].
    ///
    /// [`reduce()`]: #method.reduce
    ///
    /// If a `Result::Err` or `Option::None` item is found, or if `op` reduces
    /// to one, we will attempt to stop processing the rest of the items in the
    /// iterator as soon as possible, and we will return that terminating value.
    /// Otherwise, we will return the final reduced `Result::Ok(T)` or
    /// `Option::Some(T)`.  If there are multiple errors in parallel, it is not
    /// specified which will be returned.
    ///
    /// # Examples
    ///
    /// ```
    /// use rayon::prelude::*;
    ///
    /// // Compute the sum of squares, being careful about overflow.
    /// fn sum_squares<I: IntoParallelIterator<Item = i32>>(iter: I) -> Option<i32> {
    ///     iter.into_par_iter()
    ///         .map(|i| i.checked_mul(i))            // square each item,
    ///         .try_reduce(|| 0, i32::checked_add)   // and add them up!
    /// }
    /// assert_eq!(sum_squares(0..5), Some(0 + 1 + 4 + 9 + 16));
    ///
    /// // The sum might overflow
    /// assert_eq!(sum_squares(0..10_000), None);
    ///
    /// // Or the squares might overflow before it even reaches `try_reduce`
    /// assert_eq!(sum_squares(1_000_000..1_000_001), None);
    /// ```
    fn try_reduce<T, OP, ID>(self, identity: ID, op: OP) -> Self::Item
    where
        OP: Fn(T, T) -> Self::Item + Sync + Send,
        ID: Fn() -> T + Sync + Send,
        Self::Item: Try<Output = T>,
    {
        try_reduce::try_reduce(self, identity, op)
    }

    /// Reduces the items in the iterator into one item using a fallible `op`.
    ///
    /// Like [`reduce_with()`], if the iterator is empty, `None` is returned;
    /// otherwise, `Some` is returned.  Beyond that, it behaves like
    /// [`try_reduce()`] for handling `Err`/`None`.
    ///
    /// [`reduce_with()`]: #method.reduce_with
    /// [`try_reduce()`]: #method.try_reduce
    ///
    /// For instance, with `Option` items, the return value may be:
    /// - `None`, the iterator was empty
    /// - `Some(None)`, we stopped after encountering `None`.
    /// - `Some(Some(x))`, the entire iterator reduced to `x`.
    ///
    /// With `Result` items, the nesting is more obvious:
    /// - `None`, the iterator was empty
    /// - `Some(Err(e))`, we stopped after encountering an error `e`.
    /// - `Some(Ok(x))`, the entire iterator reduced to `x`.
    ///
    /// # Examples
    ///
    /// ```
    /// use rayon::prelude::*;
    ///
    /// let files = ["/dev/null", "/does/not/exist"];
    ///
    /// // Find the biggest file
    /// files.into_par_iter()
    ///     .map(|path| std::fs::metadata(path).map(|m| (path, m.len())))
    ///     .try_reduce_with(|a, b| {
    ///         Ok(if a.1 >= b.1 { a } else { b })
    ///     })
    ///     .expect("Some value, since the iterator is not empty")
    ///     .expect_err("not found");
    /// ```
    fn try_reduce_with<T, OP>(self, op: OP) -> Option<Self::Item>
    where
        OP: Fn(T, T) -> Self::Item + Sync + Send,
        Self::Item: Try<Output = T>,
    {
        try_reduce_with::try_reduce_with(self, op)
    }

    /// Parallel fold is similar to sequential fold except that the
    /// sequence of items may be subdivided before it is
    /// folded. Consider a list of numbers like `22 3 77 89 46`. If
    /// you used sequential fold to add them (`fold(0, |a,b| a+b)`,
    /// you would wind up first adding 0 + 22, then 22 + 3, then 25 +
    /// 77, and so forth. The **parallel fold** works similarly except
    /// that it first breaks up your list into sublists, and hence
    /// instead of yielding up a single sum at the end, it yields up
    /// multiple sums. The number of results is nondeterministic, as
    /// is the point where the breaks occur.
    ///
    /// So if did the same parallel fold (`fold(0, |a,b| a+b)`) on
    /// our example list, we might wind up with a sequence of two numbers,
    /// like so:
    ///
    /// ```notrust
    /// 22 3 77 89 46
    ///       |     |
    ///     102   135
    /// ```
    ///
    /// Or perhaps these three numbers:
    ///
    /// ```notrust
    /// 22 3 77 89 46
    ///       |  |  |
    ///     102 89 46
    /// ```
    ///
    /// In general, Rayon will attempt to find good breaking points
    /// that keep all of your cores busy.
    ///
    /// ### Fold versus reduce
    ///
    /// The `fold()` and `reduce()` methods each take an identity element
    /// and a combining function, but they operate rather differently.
    ///
    /// `reduce()` requires that the identity function has the same
    /// type as the things you are iterating over, and it fully
    /// reduces the list of items into a single item. So, for example,
    /// imagine we are iterating over a list of bytes `bytes: [128_u8,
    /// 64_u8, 64_u8]`. If we used `bytes.reduce(|| 0_u8, |a: u8, b:
    /// u8| a + b)`, we would get an overflow. This is because `0`,
    /// `a`, and `b` here are all bytes, just like the numbers in the
    /// list (I wrote the types explicitly above, but those are the
    /// only types you can use). To avoid the overflow, we would need
    /// to do something like `bytes.map(|b| b as u32).reduce(|| 0, |a,
    /// b| a + b)`, in which case our result would be `256`.
    ///
    /// In contrast, with `fold()`, the identity function does not
    /// have to have the same type as the things you are iterating
    /// over, and you potentially get back many results. So, if we
    /// continue with the `bytes` example from the previous paragraph,
    /// we could do `bytes.fold(|| 0_u32, |a, b| a + (b as u32))` to
    /// convert our bytes into `u32`. And of course we might not get
    /// back a single sum.
    ///
    /// There is a more subtle distinction as well, though it's
    /// actually implied by the above points. When you use `reduce()`,
    /// your reduction function is sometimes called with values that
    /// were never part of your original parallel iterator (for
    /// example, both the left and right might be a partial sum). With
    /// `fold()`, in contrast, the left value in the fold function is
    /// always the accumulator, and the right value is always from
    /// your original sequence.
    ///
    /// ### Fold vs Map/Reduce
    ///
    /// Fold makes sense if you have some operation where it is
    /// cheaper to create groups of elements at a time. For example,
    /// imagine collecting characters into a string. If you were going
    /// to use map/reduce, you might try this:
    ///
    /// ```
    /// use rayon::prelude::*;
    ///
    /// let s =
    ///     ['a', 'b', 'c', 'd', 'e']
    ///     .par_iter()
    ///     .map(|c: &char| format!("{}", c))
    ///     .reduce(|| String::new(),
    ///             |mut a: String, b: String| { a.push_str(&b); a });
    ///
    /// assert_eq!(s, "abcde");
    /// ```
    ///
    /// Because reduce produces the same type of element as its input,
    /// you have to first map each character into a string, and then
    /// you can reduce them. This means we create one string per
    /// element in our iterator -- not so great. Using `fold`, we can
    /// do this instead:
    ///
    /// ```
    /// use rayon::prelude::*;
    ///
    /// let s =
    ///     ['a', 'b', 'c', 'd', 'e']
    ///     .par_iter()
    ///     .fold(|| String::new(),
    ///             |mut s: String, c: &char| { s.push(*c); s })
    ///     .reduce(|| String::new(),
    ///             |mut a: String, b: String| { a.push_str(&b); a });
    ///
    /// assert_eq!(s, "abcde");
    /// ```
    ///
    /// Now `fold` will process groups of our characters at a time,
    /// and we only make one string per group. We should wind up with
    /// some small-ish number of strings roughly proportional to the
    /// number of CPUs you have (it will ultimately depend on how busy
    /// your processors are). Note that we still need to do a reduce
    /// afterwards to combine those groups of strings into a single
    /// string.
    ///
    /// You could use a similar trick to save partial results (e.g., a
    /// cache) or something similar.
    ///
    /// ### Combining fold with other operations
    ///
    /// You can combine `fold` with `reduce` if you want to produce a
    /// single value. This is then roughly equivalent to a map/reduce
    /// combination in effect:
    ///
    /// ```
    /// use rayon::prelude::*;
    ///
    /// let bytes = 0..22_u8;
    /// let sum = bytes.into_par_iter()
    ///                .fold(|| 0_u32, |a: u32, b: u8| a + (b as u32))
    ///                .sum::<u32>();
    ///
    /// assert_eq!(sum, (0..22).sum()); // compare to sequential
    /// ```
    fn fold<T, ID, F>(self, identity: ID, fold_op: F) -> Fold<Self, ID, F>
    where
        F: Fn(T, Self::Item) -> T + Sync + Send,
        ID: Fn() -> T + Sync + Send,
        T: Send,
    {
        Fold::new(self, identity, fold_op)
    }

    /// Applies `fold_op` to the given `init` value with each item of this
    /// iterator, finally producing the value for further use.
    ///
    /// This works essentially like `fold(|| init.clone(), fold_op)`, except
    /// it doesn't require the `init` type to be `Sync`, nor any other form
    /// of added synchronization.
    ///
    /// # Examples
    ///
    /// ```
    /// use rayon::prelude::*;
    ///
    /// let bytes = 0..22_u8;
    /// let sum = bytes.into_par_iter()
    ///                .fold_with(0_u32, |a: u32, b: u8| a + (b as u32))
    ///                .sum::<u32>();
    ///
    /// assert_eq!(sum, (0..22).sum()); // compare to sequential
    /// ```
    fn fold_with<F, T>(self, init: T, fold_op: F) -> FoldWith<Self, T, F>
    where
        F: Fn(T, Self::Item) -> T + Sync + Send,
        T: Send + Clone,
    {
        FoldWith::new(self, init, fold_op)
    }

    /// Performs a fallible parallel fold.
    ///
    /// This is a variation of [`fold()`] for operations which can fail with
    /// `Option::None` or `Result::Err`.  The first such failure stops
    /// processing the local set of items, without affecting other folds in the
    /// iterator's subdivisions.
    ///
    /// Often, `try_fold()` will be followed by [`try_reduce()`]
    /// for a final reduction and global short-circuiting effect.
    ///
    /// [`fold()`]: #method.fold
    /// [`try_reduce()`]: #method.try_reduce
    ///
    /// # Examples
    ///
    /// ```
    /// use rayon::prelude::*;
    ///
    /// let bytes = 0..22_u8;
    /// let sum = bytes.into_par_iter()
    ///                .try_fold(|| 0_u32, |a: u32, b: u8| a.checked_add(b as u32))
    ///                .try_reduce(|| 0, u32::checked_add);
    ///
    /// assert_eq!(sum, Some((0..22).sum())); // compare to sequential
    /// ```
    fn try_fold<T, R, ID, F>(self, identity: ID, fold_op: F) -> TryFold<Self, R, ID, F>
    where
        F: Fn(T, Self::Item) -> R + Sync + Send,
        ID: Fn() -> T + Sync + Send,
        R: Try<Output = T> + Send,
    {
        TryFold::new(self, identity, fold_op)
    }

    /// Performs a fallible parallel fold with a cloneable `init` value.
    ///
    /// This combines the `init` semantics of [`fold_with()`] and the failure
    /// semantics of [`try_fold()`].
    ///
    /// [`fold_with()`]: #method.fold_with
    /// [`try_fold()`]: #method.try_fold
    ///
    /// ```
    /// use rayon::prelude::*;
    ///
    /// let bytes = 0..22_u8;
    /// let sum = bytes.into_par_iter()
    ///                .try_fold_with(0_u32, |a: u32, b: u8| a.checked_add(b as u32))
    ///                .try_reduce(|| 0, u32::checked_add);
    ///
    /// assert_eq!(sum, Some((0..22).sum())); // compare to sequential
    /// ```
    fn try_fold_with<F, T, R>(self, init: T, fold_op: F) -> TryFoldWith<Self, R, F>
    where
        F: Fn(T, Self::Item) -> R + Sync + Send,
        R: Try<Output = T> + Send,
        T: Clone + Send,
    {
        TryFoldWith::new(self, init, fold_op)
    }

    /// Sums up the items in the iterator.
    ///
    /// Note that the order in items will be reduced is not specified,
    /// so if the `+` operator is not truly [associative] \(as is the
    /// case for floating point numbers), then the results are not
    /// fully deterministic.
    ///
    /// [associative]: https://en.wikipedia.org/wiki/Associative_property
    ///
    /// Basically equivalent to `self.reduce(|| 0, |a, b| a + b)`,
    /// except that the type of `0` and the `+` operation may vary
    /// depending on the type of value being produced.
    ///
    /// # Examples
    ///
    /// ```
    /// use rayon::prelude::*;
    ///
    /// let a = [1, 5, 7];
    ///
    /// let sum: i32 = a.par_iter().sum();
    ///
    /// assert_eq!(sum, 13);
    /// ```
    fn sum<S>(self) -> S
    where
        S: Send + Sum<Self::Item> + Sum<S>,
    {
        sum::sum(self)
    }

    /// Multiplies all the items in the iterator.
    ///
    /// Note that the order in items will be reduced is not specified,
    /// so if the `*` operator is not truly [associative] \(as is the
    /// case for floating point numbers), then the results are not
    /// fully deterministic.
    ///
    /// [associative]: https://en.wikipedia.org/wiki/Associative_property
    ///
    /// Basically equivalent to `self.reduce(|| 1, |a, b| a * b)`,
    /// except that the type of `1` and the `*` operation may vary
    /// depending on the type of value being produced.
    ///
    /// # Examples
    ///
    /// ```
    /// use rayon::prelude::*;
    ///
    /// fn factorial(n: u32) -> u32 {
    ///    (1..n+1).into_par_iter().product()
    /// }
    ///
    /// assert_eq!(factorial(0), 1);
    /// assert_eq!(factorial(1), 1);
    /// assert_eq!(factorial(5), 120);
    /// ```
    fn product<P>(self) -> P
    where
        P: Send + Product<Self::Item> + Product<P>,
    {
        product::product(self)
    }

    /// Computes the minimum of all the items in the iterator. If the
    /// iterator is empty, `None` is returned; otherwise, `Some(min)`
    /// is returned.
    ///
    /// Note that the order in which the items will be reduced is not
    /// specified, so if the `Ord` impl is not truly associative, then
    /// the results are not deterministic.
    ///
    /// Basically equivalent to `self.reduce_with(|a, b| cmp::min(a, b))`.
    ///
    /// # Examples
    ///
    /// ```
    /// use rayon::prelude::*;
    ///
    /// let a = [45, 74, 32];
    ///
    /// assert_eq!(a.par_iter().min(), Some(&32));
    ///
    /// let b: [i32; 0] = [];
    ///
    /// assert_eq!(b.par_iter().min(), None);
    /// ```
    fn min(self) -> Option<Self::Item>
    where
        Self::Item: Ord,
    {
        self.reduce_with(cmp::min)
    }

    /// Computes the minimum of all the items in the iterator with respect to
    /// the given comparison function. If the iterator is empty, `None` is
    /// returned; otherwise, `Some(min)` is returned.
    ///
    /// Note that the order in which the items will be reduced is not
    /// specified, so if the comparison function is not associative, then
    /// the results are not deterministic.
    ///
    /// # Examples
    ///
    /// ```
    /// use rayon::prelude::*;
    ///
    /// let a = [-3_i32, 77, 53, 240, -1];
    ///
    /// assert_eq!(a.par_iter().min_by(|x, y| x.cmp(y)), Some(&-3));
    /// ```
    fn min_by<F>(self, f: F) -> Option<Self::Item>
    where
        F: Sync + Send + Fn(&Self::Item, &Self::Item) -> Ordering,
    {
        fn min<T>(f: impl Fn(&T, &T) -> Ordering) -> impl Fn(T, T) -> T {
            move |a, b| match f(&a, &b) {
                Ordering::Greater => b,
                _ => a,
            }
        }

        self.reduce_with(min(f))
    }

    /// Computes the item that yields the minimum value for the given
    /// function. If the iterator is empty, `None` is returned;
    /// otherwise, `Some(item)` is returned.
    ///
    /// Note that the order in which the items will be reduced is not
    /// specified, so if the `Ord` impl is not truly associative, then
    /// the results are not deterministic.
    ///
    /// # Examples
    ///
    /// ```
    /// use rayon::prelude::*;
    ///
    /// let a = [-3_i32, 34, 2, 5, -10, -3, -23];
    ///
    /// assert_eq!(a.par_iter().min_by_key(|x| x.abs()), Some(&2));
    /// ```
    fn min_by_key<K, F>(self, f: F) -> Option<Self::Item>
    where
        K: Ord + Send,
        F: Sync + Send + Fn(&Self::Item) -> K,
    {
        fn key<T, K>(f: impl Fn(&T) -> K) -> impl Fn(T) -> (K, T) {
            move |x| (f(&x), x)
        }

        fn min_key<T, K: Ord>(a: (K, T), b: (K, T)) -> (K, T) {
            match (a.0).cmp(&b.0) {
                Ordering::Greater => b,
                _ => a,
            }
        }

        let (_, x) = self.map(key(f)).reduce_with(min_key)?;
        Some(x)
    }

    /// Computes the maximum of all the items in the iterator. If the
    /// iterator is empty, `None` is returned; otherwise, `Some(max)`
    /// is returned.
    ///
    /// Note that the order in which the items will be reduced is not
    /// specified, so if the `Ord` impl is not truly associative, then
    /// the results are not deterministic.
    ///
    /// Basically equivalent to `self.reduce_with(|a, b| cmp::max(a, b))`.
    ///
    /// # Examples
    ///
    /// ```
    /// use rayon::prelude::*;
    ///
    /// let a = [45, 74, 32];
    ///
    /// assert_eq!(a.par_iter().max(), Some(&74));
    ///
    /// let b: [i32; 0] = [];
    ///
    /// assert_eq!(b.par_iter().max(), None);
    /// ```
    fn max(self) -> Option<Self::Item>
    where
        Self::Item: Ord,
    {
        self.reduce_with(cmp::max)
    }

    /// Computes the maximum of all the items in the iterator with respect to
    /// the given comparison function. If the iterator is empty, `None` is
    /// returned; otherwise, `Some(min)` is returned.
    ///
    /// Note that the order in which the items will be reduced is not
    /// specified, so if the comparison function is not associative, then
    /// the results are not deterministic.
    ///
    /// # Examples
    ///
    /// ```
    /// use rayon::prelude::*;
    ///
    /// let a = [-3_i32, 77, 53, 240, -1];
    ///
    /// assert_eq!(a.par_iter().max_by(|x, y| x.abs().cmp(&y.abs())), Some(&240));
    /// ```
    fn max_by<F>(self, f: F) -> Option<Self::Item>
    where
        F: Sync + Send + Fn(&Self::Item, &Self::Item) -> Ordering,
    {
        fn max<T>(f: impl Fn(&T, &T) -> Ordering) -> impl Fn(T, T) -> T {
            move |a, b| match f(&a, &b) {
                Ordering::Greater => a,
                _ => b,
            }
        }

        self.reduce_with(max(f))
    }

    /// Computes the item that yields the maximum value for the given
    /// function. If the iterator is empty, `None` is returned;
    /// otherwise, `Some(item)` is returned.
    ///
    /// Note that the order in which the items will be reduced is not
    /// specified, so if the `Ord` impl is not truly associative, then
    /// the results are not deterministic.
    ///
    /// # Examples
    ///
    /// ```
    /// use rayon::prelude::*;
    ///
    /// let a = [-3_i32, 34, 2, 5, -10, -3, -23];
    ///
    /// assert_eq!(a.par_iter().max_by_key(|x| x.abs()), Some(&34));
    /// ```
    fn max_by_key<K, F>(self, f: F) -> Option<Self::Item>
    where
        K: Ord + Send,
        F: Sync + Send + Fn(&Self::Item) -> K,
    {
        fn key<T, K>(f: impl Fn(&T) -> K) -> impl Fn(T) -> (K, T) {
            move |x| (f(&x), x)
        }

        fn max_key<T, K: Ord>(a: (K, T), b: (K, T)) -> (K, T) {
            match (a.0).cmp(&b.0) {
                Ordering::Greater => a,
                _ => b,
            }
        }

        let (_, x) = self.map(key(f)).reduce_with(max_key)?;
        Some(x)
    }

    /// Takes two iterators and creates a new iterator over both.
    ///
    /// # Examples
    ///
    /// ```
    /// use rayon::prelude::*;
    ///
    /// let a = [0, 1, 2];
    /// let b = [9, 8, 7];
    ///
    /// let par_iter = a.par_iter().chain(b.par_iter());
    ///
    /// let chained: Vec<_> = par_iter.cloned().collect();
    ///
    /// assert_eq!(&chained[..], &[0, 1, 2, 9, 8, 7]);
    /// ```
    fn chain<C>(self, chain: C) -> Chain<Self, C::Iter>
    where
        C: IntoParallelIterator<Item = Self::Item>,
    {
        Chain::new(self, chain.into_par_iter())
    }

    /// Searches for **some** item in the parallel iterator that
    /// matches the given predicate and returns it. This operation
    /// is similar to [`find` on sequential iterators][find] but
    /// the item returned may not be the **first** one in the parallel
    /// sequence which matches, since we search the entire sequence in parallel.
    ///
    /// Once a match is found, we will attempt to stop processing
    /// the rest of the items in the iterator as soon as possible
    /// (just as `find` stops iterating once a match is found).
    ///
    /// [find]: https://doc.rust-lang.org/std/iter/trait.Iterator.html#method.find
    ///
    /// # Examples
    ///
    /// ```
    /// use rayon::prelude::*;
    ///
    /// let a = [1, 2, 3, 3];
    ///
    /// assert_eq!(a.par_iter().find_any(|&&x| x == 3), Some(&3));
    ///
    /// assert_eq!(a.par_iter().find_any(|&&x| x == 100), None);
    /// ```
    fn find_any<P>(self, predicate: P) -> Option<Self::Item>
    where
        P: Fn(&Self::Item) -> bool + Sync + Send,
    {
        find::find(self, predicate)
    }

    /// Searches for the sequentially **first** item in the parallel iterator
    /// that matches the given predicate and returns it.
    ///
    /// Once a match is found, all attempts to the right of the match
    /// will be stopped, while attempts to the left must continue in case
    /// an earlier match is found.
    ///
    /// Note that not all parallel iterators have a useful order, much like
    /// sequential `HashMap` iteration, so "first" may be nebulous.  If you
    /// just want the first match that discovered anywhere in the iterator,
    /// `find_any` is a better choice.
    ///
    /// # Examples
    ///
    /// ```
    /// use rayon::prelude::*;
    ///
    /// let a = [1, 2, 3, 3];
    ///
    /// assert_eq!(a.par_iter().find_first(|&&x| x == 3), Some(&3));
    ///
    /// assert_eq!(a.par_iter().find_first(|&&x| x == 100), None);
    /// ```
    fn find_first<P>(self, predicate: P) -> Option<Self::Item>
    where
        P: Fn(&Self::Item) -> bool + Sync + Send,
    {
        find_first_last::find_first(self, predicate)
    }

    /// Searches for the sequentially **last** item in the parallel iterator
    /// that matches the given predicate and returns it.
    ///
    /// Once a match is found, all attempts to the left of the match
    /// will be stopped, while attempts to the right must continue in case
    /// a later match is found.
    ///
    /// Note that not all parallel iterators have a useful order, much like
    /// sequential `HashMap` iteration, so "last" may be nebulous.  When the
    /// order doesn't actually matter to you, `find_any` is a better choice.
    ///
    /// # Examples
    ///
    /// ```
    /// use rayon::prelude::*;
    ///
    /// let a = [1, 2, 3, 3];
    ///
    /// assert_eq!(a.par_iter().find_last(|&&x| x == 3), Some(&3));
    ///
    /// assert_eq!(a.par_iter().find_last(|&&x| x == 100), None);
    /// ```
    fn find_last<P>(self, predicate: P) -> Option<Self::Item>
    where
        P: Fn(&Self::Item) -> bool + Sync + Send,
    {
        find_first_last::find_last(self, predicate)
    }

    /// Applies the given predicate to the items in the parallel iterator
    /// and returns **any** non-None result of the map operation.
    ///
    /// Once a non-None value is produced from the map operation, we will
    /// attempt to stop processing the rest of the items in the iterator
    /// as soon as possible.
    ///
    /// Note that this method only returns **some** item in the parallel
    /// iterator that is not None from the map predicate. The item returned
    /// may not be the **first** non-None value produced in the parallel
    /// sequence, since the entire sequence is mapped over in parallel.
    ///
    /// # Examples
    ///
    /// ```
    /// use rayon::prelude::*;
    ///
    /// let c = ["lol", "NaN", "5", "5"];
    ///
    /// let found_number = c.par_iter().find_map_any(|s| s.parse().ok());
    ///
    /// assert_eq!(found_number, Some(5));
    /// ```
    fn find_map_any<P, R>(self, predicate: P) -> Option<R>
    where
        P: Fn(Self::Item) -> Option<R> + Sync + Send,
        R: Send,
    {
        fn yes<T>(_: &T) -> bool {
            true
        }
        self.filter_map(predicate).find_any(yes)
    }

    /// Applies the given predicate to the items in the parallel iterator and
    /// returns the sequentially **first** non-None result of the map operation.
    ///
    /// Once a non-None value is produced from the map operation, all attempts
    /// to the right of the match will be stopped, while attempts to the left
    /// must continue in case an earlier match is found.
    ///
    /// Note that not all parallel iterators have a useful order, much like
    /// sequential `HashMap` iteration, so "first" may be nebulous. If you
    /// just want the first non-None value discovered anywhere in the iterator,
    /// `find_map_any` is a better choice.
    ///
    /// # Examples
    ///
    /// ```
    /// use rayon::prelude::*;
    ///
    /// let c = ["lol", "NaN", "2", "5"];
    ///
    /// let first_number = c.par_iter().find_map_first(|s| s.parse().ok());
    ///
    /// assert_eq!(first_number, Some(2));
    /// ```
    fn find_map_first<P, R>(self, predicate: P) -> Option<R>
    where
        P: Fn(Self::Item) -> Option<R> + Sync + Send,
        R: Send,
    {
        fn yes<T>(_: &T) -> bool {
            true
        }
        self.filter_map(predicate).find_first(yes)
    }

    /// Applies the given predicate to the items in the parallel iterator and
    /// returns the sequentially **last** non-None result of the map operation.
    ///
    /// Once a non-None value is produced from the map operation, all attempts
    /// to the left of the match will be stopped, while attempts to the right
    /// must continue in case a later match is found.
    ///
    /// Note that not all parallel iterators have a useful order, much like
    /// sequential `HashMap` iteration, so "first" may be nebulous. If you
    /// just want the first non-None value discovered anywhere in the iterator,
    /// `find_map_any` is a better choice.
    ///
    /// # Examples
    ///
    /// ```
    /// use rayon::prelude::*;
    ///
    /// let c = ["lol", "NaN", "2", "5"];
    ///
    /// let last_number = c.par_iter().find_map_last(|s| s.parse().ok());
    ///
    /// assert_eq!(last_number, Some(5));
    /// ```
    fn find_map_last<P, R>(self, predicate: P) -> Option<R>
    where
        P: Fn(Self::Item) -> Option<R> + Sync + Send,
        R: Send,
    {
        fn yes<T>(_: &T) -> bool {
            true
        }
        self.filter_map(predicate).find_last(yes)
    }

    #[doc(hidden)]
    #[deprecated(note = "parallel `find` does not search in order -- use `find_any`, \\
                         `find_first`, or `find_last`")]
    fn find<P>(self, predicate: P) -> Option<Self::Item>
    where
        P: Fn(&Self::Item) -> bool + Sync + Send,
    {
        self.find_any(predicate)
    }

    /// Searches for **some** item in the parallel iterator that
    /// matches the given predicate, and if so returns true.  Once
    /// a match is found, we'll attempt to stop process the rest
    /// of the items.  Proving that there's no match, returning false,
    /// does require visiting every item.
    ///
    /// # Examples
    ///
    /// ```
    /// use rayon::prelude::*;
    ///
    /// let a = [0, 12, 3, 4, 0, 23, 0];
    ///
    /// let is_valid = a.par_iter().any(|&x| x > 10);
    ///
    /// assert!(is_valid);
    /// ```
    fn any<P>(self, predicate: P) -> bool
    where
        P: Fn(Self::Item) -> bool + Sync + Send,
    {
        self.map(predicate).find_any(bool::clone).is_some()
    }

    /// Tests that every item in the parallel iterator matches the given
    /// predicate, and if so returns true.  If a counter-example is found,
    /// we'll attempt to stop processing more items, then return false.
    ///
    /// # Examples
    ///
    /// ```
    /// use rayon::prelude::*;
    ///
    /// let a = [0, 12, 3, 4, 0, 23, 0];
    ///
    /// let is_valid = a.par_iter().all(|&x| x > 10);
    ///
    /// assert!(!is_valid);
    /// ```
    fn all<P>(self, predicate: P) -> bool
    where
        P: Fn(Self::Item) -> bool + Sync + Send,
    {
        #[inline]
        fn is_false(x: &bool) -> bool {
            !x
        }

        self.map(predicate).find_any(is_false).is_none()
    }

    /// Creates an iterator over the `Some` items of this iterator, halting
    /// as soon as any `None` is found.
    ///
    /// # Examples
    ///
    /// ```
    /// use rayon::prelude::*;
    /// use std::sync::atomic::{AtomicUsize, Ordering};
    ///
    /// let counter = AtomicUsize::new(0);
    /// let value = (0_i32..2048)
    ///     .into_par_iter()
    ///     .map(|x| {
    ///              counter.fetch_add(1, Ordering::SeqCst);
    ///              if x < 1024 { Some(x) } else { None }
    ///          })
    ///     .while_some()
    ///     .max();
    ///
    /// assert!(value < Some(1024));
    /// assert!(counter.load(Ordering::SeqCst) < 2048); // should not have visited every single one
    /// ```
    fn while_some<T>(self) -> WhileSome<Self>
    where
        Self: ParallelIterator<Item = Option<T>>,
        T: Send,
    {
        WhileSome::new(self)
    }

    /// Wraps an iterator with a fuse in case of panics, to halt all threads
    /// as soon as possible.
    ///
    /// Panics within parallel iterators are always propagated to the caller,
    /// but they don't always halt the rest of the iterator right away, due to
    /// the internal semantics of [`join`]. This adaptor makes a greater effort
    /// to stop processing other items sooner, with the cost of additional
    /// synchronization overhead, which may also inhibit some optimizations.
    ///
    /// [`join`]: ../fn.join.html#panics
    ///
    /// # Examples
    ///
    /// If this code didn't use `panic_fuse()`, it would continue processing
    /// many more items in other threads (with long sleep delays) before the
    /// panic is finally propagated.
    ///
    /// ```should_panic
    /// use rayon::prelude::*;
    /// use std::{thread, time};
    ///
    /// (0..1_000_000)
    ///     .into_par_iter()
    ///     .panic_fuse()
    ///     .for_each(|i| {
    ///         // simulate some work
    ///         thread::sleep(time::Duration::from_secs(1));
    ///         assert!(i > 0); // oops!
    ///     });
    /// ```
    fn panic_fuse(self) -> PanicFuse<Self> {
        PanicFuse::new(self)
    }

    /// Creates a fresh collection containing all the elements produced
    /// by this parallel iterator.
    ///
    /// You may prefer [`collect_into_vec()`] implemented on
    /// [`IndexedParallelIterator`], if your underlying iterator also implements
    /// it. [`collect_into_vec()`] allocates efficiently with precise knowledge
    /// of how many elements the iterator contains, and even allows you to reuse
    /// an existing vector's backing store rather than allocating a fresh vector.
    ///
    /// [`IndexedParallelIterator`]: trait.IndexedParallelIterator.html
    /// [`collect_into_vec()`]:
    ///     trait.IndexedParallelIterator.html#method.collect_into_vec
    ///
    /// # Examples
    ///
    /// ```
    /// use rayon::prelude::*;
    ///
    /// let sync_vec: Vec<_> = (0..100).into_iter().collect();
    ///
    /// let async_vec: Vec<_> = (0..100).into_par_iter().collect();
    ///
    /// assert_eq!(sync_vec, async_vec);
    /// ```
    ///
    /// You can collect a pair of collections like [`unzip`](#method.unzip)
    /// for paired items:
    ///
    /// ```
    /// use rayon::prelude::*;
    ///
    /// let a = [(0, 1), (1, 2), (2, 3), (3, 4)];
    /// let (first, second): (Vec<_>, Vec<_>) = a.into_par_iter().collect();
    ///
    /// assert_eq!(first, [0, 1, 2, 3]);
    /// assert_eq!(second, [1, 2, 3, 4]);
    /// ```
    ///
    /// Or like [`partition_map`](#method.partition_map) for `Either` items:
    ///
    /// ```
    /// use rayon::prelude::*;
    /// use rayon::iter::Either;
    ///
    /// let (left, right): (Vec<_>, Vec<_>) = (0..8).into_par_iter().map(|x| {
    ///     if x % 2 == 0 {
    ///         Either::Left(x * 4)
    ///     } else {
    ///         Either::Right(x * 3)
    ///     }
    /// }).collect();
    ///
    /// assert_eq!(left, [0, 8, 16, 24]);
    /// assert_eq!(right, [3, 9, 15, 21]);
    /// ```
    ///
    /// You can even collect an arbitrarily-nested combination of pairs and `Either`:
    ///
    /// ```
    /// use rayon::prelude::*;
    /// use rayon::iter::Either;
    ///
    /// let (first, (left, right)): (Vec<_>, (Vec<_>, Vec<_>))
    ///     = (0..8).into_par_iter().map(|x| {
    ///         if x % 2 == 0 {
    ///             (x, Either::Left(x * 4))
    ///         } else {
    ///             (-x, Either::Right(x * 3))
    ///         }
    ///     }).collect();
    ///
    /// assert_eq!(first, [0, -1, 2, -3, 4, -5, 6, -7]);
    /// assert_eq!(left, [0, 8, 16, 24]);
    /// assert_eq!(right, [3, 9, 15, 21]);
    /// ```
    ///
    /// All of that can _also_ be combined with short-circuiting collection of
    /// `Result` or `Option` types:
    ///
    /// ```
    /// use rayon::prelude::*;
    /// use rayon::iter::Either;
    ///
    /// let result: Result<(Vec<_>, (Vec<_>, Vec<_>)), _>
    ///     = (0..8).into_par_iter().map(|x| {
    ///         if x > 5 {
    ///             Err(x)
    ///         } else if x % 2 == 0 {
    ///             Ok((x, Either::Left(x * 4)))
    ///         } else {
    ///             Ok((-x, Either::Right(x * 3)))
    ///         }
    ///     }).collect();
    ///
    /// let error = result.unwrap_err();
    /// assert!(error == 6 || error == 7);
    /// ```
    fn collect<C>(self) -> C
    where
        C: FromParallelIterator<Self::Item>,
    {
        C::from_par_iter(self)
    }

    /// Unzips the items of a parallel iterator into a pair of arbitrary
    /// `ParallelExtend` containers.
    ///
    /// You may prefer to use `unzip_into_vecs()`, which allocates more
    /// efficiently with precise knowledge of how many elements the
    /// iterator contains, and even allows you to reuse existing
    /// vectors' backing stores rather than allocating fresh vectors.
    ///
    /// # Examples
    ///
    /// ```
    /// use rayon::prelude::*;
    ///
    /// let a = [(0, 1), (1, 2), (2, 3), (3, 4)];
    ///
    /// let (left, right): (Vec<_>, Vec<_>) = a.par_iter().cloned().unzip();
    ///
    /// assert_eq!(left, [0, 1, 2, 3]);
    /// assert_eq!(right, [1, 2, 3, 4]);
    /// ```
    ///
    /// Nested pairs can be unzipped too.
    ///
    /// ```
    /// use rayon::prelude::*;
    ///
    /// let (values, (squares, cubes)): (Vec<_>, (Vec<_>, Vec<_>)) = (0..4).into_par_iter()
    ///     .map(|i| (i, (i * i, i * i * i)))
    ///     .unzip();
    ///
    /// assert_eq!(values, [0, 1, 2, 3]);
    /// assert_eq!(squares, [0, 1, 4, 9]);
    /// assert_eq!(cubes, [0, 1, 8, 27]);
    /// ```
    fn unzip<A, B, FromA, FromB>(self) -> (FromA, FromB)
    where
        Self: ParallelIterator<Item = (A, B)>,
        FromA: Default + Send + ParallelExtend<A>,
        FromB: Default + Send + ParallelExtend<B>,
        A: Send,
        B: Send,
    {
        unzip::unzip(self)
    }

    /// Partitions the items of a parallel iterator into a pair of arbitrary
    /// `ParallelExtend` containers.  Items for which the `predicate` returns
    /// true go into the first container, and the rest go into the second.
    ///
    /// Note: unlike the standard `Iterator::partition`, this allows distinct
    /// collection types for the left and right items.  This is more flexible,
    /// but may require new type annotations when converting sequential code
    /// that used type inference assuming the two were the same.
    ///
    /// # Examples
    ///
    /// ```
    /// use rayon::prelude::*;
    ///
    /// let (left, right): (Vec<_>, Vec<_>) = (0..8).into_par_iter().partition(|x| x % 2 == 0);
    ///
    /// assert_eq!(left, [0, 2, 4, 6]);
    /// assert_eq!(right, [1, 3, 5, 7]);
    /// ```
    fn partition<A, B, P>(self, predicate: P) -> (A, B)
    where
        A: Default + Send + ParallelExtend<Self::Item>,
        B: Default + Send + ParallelExtend<Self::Item>,
        P: Fn(&Self::Item) -> bool + Sync + Send,
    {
        unzip::partition(self, predicate)
    }

    /// Partitions and maps the items of a parallel iterator into a pair of
    /// arbitrary `ParallelExtend` containers.  `Either::Left` items go into
    /// the first container, and `Either::Right` items go into the second.
    ///
    /// # Examples
    ///
    /// ```
    /// use rayon::prelude::*;
    /// use rayon::iter::Either;
    ///
    /// let (left, right): (Vec<_>, Vec<_>) = (0..8).into_par_iter()
    ///     .partition_map(|x| {
    ///         if x % 2 == 0 {
    ///             Either::Left(x * 4)
    ///         } else {
    ///             Either::Right(x * 3)
    ///         }
    ///     });
    ///
    /// assert_eq!(left, [0, 8, 16, 24]);
    /// assert_eq!(right, [3, 9, 15, 21]);
    /// ```
    ///
    /// Nested `Either` enums can be split as well.
    ///
    /// ```
    /// use rayon::prelude::*;
    /// use rayon::iter::Either::*;
    ///
    /// let ((fizzbuzz, fizz), (buzz, other)): ((Vec<_>, Vec<_>), (Vec<_>, Vec<_>)) = (1..20)
    ///     .into_par_iter()
    ///     .partition_map(|x| match (x % 3, x % 5) {
    ///         (0, 0) => Left(Left(x)),
    ///         (0, _) => Left(Right(x)),
    ///         (_, 0) => Right(Left(x)),
    ///         (_, _) => Right(Right(x)),
    ///     });
    ///
    /// assert_eq!(fizzbuzz, [15]);
    /// assert_eq!(fizz, [3, 6, 9, 12, 18]);
    /// assert_eq!(buzz, [5, 10]);
    /// assert_eq!(other, [1, 2, 4, 7, 8, 11, 13, 14, 16, 17, 19]);
    /// ```
    fn partition_map<A, B, P, L, R>(self, predicate: P) -> (A, B)
    where
        A: Default + Send + ParallelExtend<L>,
        B: Default + Send + ParallelExtend<R>,
        P: Fn(Self::Item) -> Either<L, R> + Sync + Send,
        L: Send,
        R: Send,
    {
        unzip::partition_map(self, predicate)
    }

    /// Intersperses clones of an element between items of this iterator.
    ///
    /// # Examples
    ///
    /// ```
    /// use rayon::prelude::*;
    ///
    /// let x = vec![1, 2, 3];
    /// let r: Vec<_> = x.into_par_iter().intersperse(-1).collect();
    ///
    /// assert_eq!(r, vec![1, -1, 2, -1, 3]);
    /// ```
    fn intersperse(self, element: Self::Item) -> Intersperse<Self>
    where
        Self::Item: Clone,
    {
        Intersperse::new(self, element)
    }

    /// Internal method used to define the behavior of this parallel
    /// iterator. You should not need to call this directly.
    ///
    /// This method causes the iterator `self` to start producing
    /// items and to feed them to the consumer `consumer` one by one.
    /// It may split the consumer before doing so to create the
    /// opportunity to produce in parallel.
    ///
    /// See the [README] for more details on the internals of parallel
    /// iterators.
    ///
    /// [README]: https://github.com/rayon-rs/rayon/blob/master/src/iter/plumbing/README.md
    fn drive_unindexed<C>(self, consumer: C) -> C::Result
    where
        C: UnindexedConsumer<Self::Item>;

    /// Internal method used to define the behavior of this parallel
    /// iterator. You should not need to call this directly.
    ///
    /// Returns the number of items produced by this iterator, if known
    /// statically. This can be used by consumers to trigger special fast
    /// paths. Therefore, if `Some(_)` is returned, this iterator must only
    /// use the (indexed) `Consumer` methods when driving a consumer, such
    /// as `split_at()`. Calling `UnindexedConsumer::split_off_left()` or
    /// other `UnindexedConsumer` methods -- or returning an inaccurate
    /// value -- may result in panics.
    ///
    /// This method is currently used to optimize `collect` for want
    /// of true Rust specialization; it may be removed when
    /// specialization is stable.
    fn opt_len(&self) -> Option<usize> {
        None
    }
}

impl<T: ParallelIterator> IntoParallelIterator for T {
    type Iter = T;
    type Item = T::Item;

    fn into_par_iter(self) -> T {
        self
    }
}

/// An iterator that supports "random access" to its data, meaning
/// that you can split it at arbitrary indices and draw data from
/// those points.
///
/// **Note:** Not implemented for `u64`, `i64`, `u128`, or `i128` ranges
pub trait IndexedParallelIterator: ParallelIterator {
    /// Collects the results of the iterator into the specified
    /// vector. The vector is always truncated before execution
    /// begins. If possible, reusing the vector across calls can lead
    /// to better performance since it reuses the same backing buffer.
    ///
    /// # Examples
    ///
    /// ```
    /// use rayon::prelude::*;
    ///
    /// // any prior data will be truncated
    /// let mut vec = vec![-1, -2, -3];
    ///
    /// (0..5).into_par_iter()
    ///     .collect_into_vec(&mut vec);
    ///
    /// assert_eq!(vec, [0, 1, 2, 3, 4]);
    /// ```
    fn collect_into_vec(self, target: &mut Vec<Self::Item>) {
        collect::collect_into_vec(self, target);
    }

    /// Unzips the results of the iterator into the specified
    /// vectors. The vectors are always truncated before execution
    /// begins. If possible, reusing the vectors across calls can lead
    /// to better performance since they reuse the same backing buffer.
    ///
    /// # Examples
    ///
    /// ```
    /// use rayon::prelude::*;
    ///
    /// // any prior data will be truncated
    /// let mut left = vec![42; 10];
    /// let mut right = vec![-1; 10];
    ///
    /// (10..15).into_par_iter()
    ///     .enumerate()
    ///     .unzip_into_vecs(&mut left, &mut right);
    ///
    /// assert_eq!(left, [0, 1, 2, 3, 4]);
    /// assert_eq!(right, [10, 11, 12, 13, 14]);
    /// ```
    fn unzip_into_vecs<A, B>(self, left: &mut Vec<A>, right: &mut Vec<B>)
    where
        Self: IndexedParallelIterator<Item = (A, B)>,
        A: Send,
        B: Send,
    {
        collect::unzip_into_vecs(self, left, right);
    }

    /// Iterates over tuples `(A, B)`, where the items `A` are from
    /// this iterator and `B` are from the iterator given as argument.
    /// Like the `zip` method on ordinary iterators, if the two
    /// iterators are of unequal length, you only get the items they
    /// have in common.
    ///
    /// # Examples
    ///
    /// ```
    /// use rayon::prelude::*;
    ///
    /// let result: Vec<_> = (1..4)
    ///     .into_par_iter()
    ///     .zip(vec!['a', 'b', 'c'])
    ///     .collect();
    ///
    /// assert_eq!(result, [(1, 'a'), (2, 'b'), (3, 'c')]);
    /// ```
    fn zip<Z>(self, zip_op: Z) -> Zip<Self, Z::Iter>
    where
        Z: IntoParallelIterator,
        Z::Iter: IndexedParallelIterator,
    {
        Zip::new(self, zip_op.into_par_iter())
    }

    /// The same as `Zip`, but requires that both iterators have the same length.
    ///
    /// # Panics
    /// Will panic if `self` and `zip_op` are not the same length.
    ///
    /// ```should_panic
    /// use rayon::prelude::*;
    ///
    /// let one = [1u8];
    /// let two = [2u8, 2];
    /// let one_iter = one.par_iter();
    /// let two_iter = two.par_iter();
    ///
    /// // this will panic
    /// let zipped: Vec<(&u8, &u8)> = one_iter.zip_eq(two_iter).collect();
    ///
    /// // we should never get here
    /// assert_eq!(1, zipped.len());
    /// ```
    fn zip_eq<Z>(self, zip_op: Z) -> ZipEq<Self, Z::Iter>
    where
        Z: IntoParallelIterator,
        Z::Iter: IndexedParallelIterator,
    {
        let zip_op_iter = zip_op.into_par_iter();
        assert_eq!(self.len(), zip_op_iter.len());
        ZipEq::new(self, zip_op_iter)
    }

    /// Interleaves elements of this iterator and the other given
    /// iterator. Alternately yields elements from this iterator and
    /// the given iterator, until both are exhausted. If one iterator
    /// is exhausted before the other, the last elements are provided
    /// from the other.
    ///
    /// # Examples
    ///
    /// ```
    /// use rayon::prelude::*;
    /// let (x, y) = (vec![1, 2], vec![3, 4, 5, 6]);
    /// let r: Vec<i32> = x.into_par_iter().interleave(y).collect();
    /// assert_eq!(r, vec![1, 3, 2, 4, 5, 6]);
    /// ```
    fn interleave<I>(self, other: I) -> Interleave<Self, I::Iter>
    where
        I: IntoParallelIterator<Item = Self::Item>,
        I::Iter: IndexedParallelIterator<Item = Self::Item>,
    {
        Interleave::new(self, other.into_par_iter())
    }

    /// Interleaves elements of this iterator and the other given
    /// iterator, until one is exhausted.
    ///
    /// # Examples
    ///
    /// ```
    /// use rayon::prelude::*;
    /// let (x, y) = (vec![1, 2, 3, 4], vec![5, 6]);
    /// let r: Vec<i32> = x.into_par_iter().interleave_shortest(y).collect();
    /// assert_eq!(r, vec![1, 5, 2, 6, 3]);
    /// ```
    fn interleave_shortest<I>(self, other: I) -> InterleaveShortest<Self, I::Iter>
    where
        I: IntoParallelIterator<Item = Self::Item>,
        I::Iter: IndexedParallelIterator<Item = Self::Item>,
    {
        InterleaveShortest::new(self, other.into_par_iter())
    }

    /// Splits an iterator up into fixed-size chunks.
    ///
    /// Returns an iterator that returns `Vec`s of the given number of elements.
    /// If the number of elements in the iterator is not divisible by `chunk_size`,
    /// the last chunk may be shorter than `chunk_size`.
    ///
    /// See also [`par_chunks()`] and [`par_chunks_mut()`] for similar behavior on
    /// slices, without having to allocate intermediate `Vec`s for the chunks.
    ///
    /// [`par_chunks()`]: ../slice/trait.ParallelSlice.html#method.par_chunks
    /// [`par_chunks_mut()`]: ../slice/trait.ParallelSliceMut.html#method.par_chunks_mut
    ///
    /// # Examples
    ///
    /// ```
    /// use rayon::prelude::*;
    /// let a = vec![1, 2, 3, 4, 5, 6, 7, 8, 9, 10];
    /// let r: Vec<Vec<i32>> = a.into_par_iter().chunks(3).collect();
    /// assert_eq!(r, vec![vec![1,2,3], vec![4,5,6], vec![7,8,9], vec![10]]);
    /// ```
    fn chunks(self, chunk_size: usize) -> Chunks<Self> {
        assert!(chunk_size != 0, "chunk_size must not be zero");
        Chunks::new(self, chunk_size)
    }

    /// Lexicographically compares the elements of this `ParallelIterator` with those of
    /// another.
    ///
    /// # Examples
    ///
    /// ```
    /// use rayon::prelude::*;
    /// use std::cmp::Ordering::*;
    ///
    /// let x = vec![1, 2, 3];
    /// assert_eq!(x.par_iter().cmp(&vec![1, 3, 0]), Less);
    /// assert_eq!(x.par_iter().cmp(&vec![1, 2, 3]), Equal);
    /// assert_eq!(x.par_iter().cmp(&vec![1, 2]), Greater);
    /// ```
    fn cmp<I>(self, other: I) -> Ordering
    where
        I: IntoParallelIterator<Item = Self::Item>,
        I::Iter: IndexedParallelIterator,
        Self::Item: Ord,
    {
        #[inline]
        fn ordering<T: Ord>((x, y): (T, T)) -> Ordering {
            Ord::cmp(&x, &y)
        }

        #[inline]
        fn inequal(&ord: &Ordering) -> bool {
            ord != Ordering::Equal
        }

        let other = other.into_par_iter();
        let ord_len = self.len().cmp(&other.len());
        self.zip(other)
            .map(ordering)
            .find_first(inequal)
            .unwrap_or(ord_len)
    }

    /// Lexicographically compares the elements of this `ParallelIterator` with those of
    /// another.
    ///
    /// # Examples
    ///
    /// ```
    /// use rayon::prelude::*;
    /// use std::cmp::Ordering::*;
    /// use std::f64::NAN;
    ///
    /// let x = vec![1.0, 2.0, 3.0];
    /// assert_eq!(x.par_iter().partial_cmp(&vec![1.0, 3.0, 0.0]), Some(Less));
    /// assert_eq!(x.par_iter().partial_cmp(&vec![1.0, 2.0, 3.0]), Some(Equal));
    /// assert_eq!(x.par_iter().partial_cmp(&vec![1.0, 2.0]), Some(Greater));
    /// assert_eq!(x.par_iter().partial_cmp(&vec![1.0, NAN]), None);
    /// ```
    fn partial_cmp<I>(self, other: I) -> Option<Ordering>
    where
        I: IntoParallelIterator,
        I::Iter: IndexedParallelIterator,
        Self::Item: PartialOrd<I::Item>,
    {
        #[inline]
        fn ordering<T: PartialOrd<U>, U>((x, y): (T, U)) -> Option<Ordering> {
            PartialOrd::partial_cmp(&x, &y)
        }

        #[inline]
        fn inequal(&ord: &Option<Ordering>) -> bool {
            ord != Some(Ordering::Equal)
        }

        let other = other.into_par_iter();
        let ord_len = self.len().cmp(&other.len());
        self.zip(other)
            .map(ordering)
            .find_first(inequal)
            .unwrap_or(Some(ord_len))
    }

    /// Determines if the elements of this `ParallelIterator`
    /// are equal to those of another
    fn eq<I>(self, other: I) -> bool
    where
        I: IntoParallelIterator,
        I::Iter: IndexedParallelIterator,
        Self::Item: PartialEq<I::Item>,
    {
        #[inline]
        fn eq<T: PartialEq<U>, U>((x, y): (T, U)) -> bool {
            PartialEq::eq(&x, &y)
        }

        let other = other.into_par_iter();
        self.len() == other.len() && self.zip(other).all(eq)
    }

    /// Determines if the elements of this `ParallelIterator`
    /// are unequal to those of another
    fn ne<I>(self, other: I) -> bool
    where
        I: IntoParallelIterator,
        I::Iter: IndexedParallelIterator,
        Self::Item: PartialEq<I::Item>,
    {
        !self.eq(other)
    }

    /// Determines if the elements of this `ParallelIterator`
    /// are lexicographically less than those of another.
    fn lt<I>(self, other: I) -> bool
    where
        I: IntoParallelIterator,
        I::Iter: IndexedParallelIterator,
        Self::Item: PartialOrd<I::Item>,
    {
        self.partial_cmp(other) == Some(Ordering::Less)
    }

    /// Determines if the elements of this `ParallelIterator`
    /// are less or equal to those of another.
    fn le<I>(self, other: I) -> bool
    where
        I: IntoParallelIterator,
        I::Iter: IndexedParallelIterator,
        Self::Item: PartialOrd<I::Item>,
    {
        let ord = self.partial_cmp(other);
        ord == Some(Ordering::Equal) || ord == Some(Ordering::Less)
    }

    /// Determines if the elements of this `ParallelIterator`
    /// are lexicographically greater than those of another.
    fn gt<I>(self, other: I) -> bool
    where
        I: IntoParallelIterator,
        I::Iter: IndexedParallelIterator,
        Self::Item: PartialOrd<I::Item>,
    {
        self.partial_cmp(other) == Some(Ordering::Greater)
    }

    /// Determines if the elements of this `ParallelIterator`
    /// are less or equal to those of another.
    fn ge<I>(self, other: I) -> bool
    where
        I: IntoParallelIterator,
        I::Iter: IndexedParallelIterator,
        Self::Item: PartialOrd<I::Item>,
    {
        let ord = self.partial_cmp(other);
        ord == Some(Ordering::Equal) || ord == Some(Ordering::Greater)
    }

    /// Yields an index along with each item.
    ///
    /// # Examples
    ///
    /// ```
    /// use rayon::prelude::*;
    ///
    /// let chars = vec!['a', 'b', 'c'];
    /// let result: Vec<_> = chars
    ///     .into_par_iter()
    ///     .enumerate()
    ///     .collect();
    ///
    /// assert_eq!(result, [(0, 'a'), (1, 'b'), (2, 'c')]);
    /// ```
    fn enumerate(self) -> Enumerate<Self> {
        Enumerate::new(self)
    }

    /// Creates an iterator that steps by the given amount
    ///
    /// # Examples
    ///
    /// ```
    ///use rayon::prelude::*;
    ///
    /// let range = (3..10);
    /// let result: Vec<i32> = range
    ///    .into_par_iter()
    ///    .step_by(3)
    ///    .collect();
    ///
    /// assert_eq!(result, [3, 6, 9])
    /// ```
    ///
    /// # Compatibility
    ///
    /// This method is only available on Rust 1.38 or greater.
    #[cfg(has_step_by_rev)]
    fn step_by(self, step: usize) -> StepBy<Self> {
        StepBy::new(self, step)
    }

    /// Creates an iterator that skips the first `n` elements.
    ///
    /// # Examples
    ///
    /// ```
    /// use rayon::prelude::*;
    ///
    /// let result: Vec<_> = (0..100)
    ///     .into_par_iter()
    ///     .skip(95)
    ///     .collect();
    ///
    /// assert_eq!(result, [95, 96, 97, 98, 99]);
    /// ```
    fn skip(self, n: usize) -> Skip<Self> {
        Skip::new(self, n)
    }

    /// Creates an iterator that yields the first `n` elements.
    ///
    /// # Examples
    ///
    /// ```
    /// use rayon::prelude::*;
    ///
    /// let result: Vec<_> = (0..100)
    ///     .into_par_iter()
    ///     .take(5)
    ///     .collect();
    ///
    /// assert_eq!(result, [0, 1, 2, 3, 4]);
    /// ```
    fn take(self, n: usize) -> Take<Self> {
        Take::new(self, n)
    }

    /// Searches for **some** item in the parallel iterator that
    /// matches the given predicate, and returns its index.  Like
    /// `ParallelIterator::find_any`, the parallel search will not
    /// necessarily find the **first** match, and once a match is
    /// found we'll attempt to stop processing any more.
    ///
    /// # Examples
    ///
    /// ```
    /// use rayon::prelude::*;
    ///
    /// let a = [1, 2, 3, 3];
    ///
    /// let i = a.par_iter().position_any(|&x| x == 3).expect("found");
    /// assert!(i == 2 || i == 3);
    ///
    /// assert_eq!(a.par_iter().position_any(|&x| x == 100), None);
    /// ```
    fn position_any<P>(self, predicate: P) -> Option<usize>
    where
        P: Fn(Self::Item) -> bool + Sync + Send,
    {
        #[inline]
        fn check(&(_, p): &(usize, bool)) -> bool {
            p
        }

        let (i, _) = self.map(predicate).enumerate().find_any(check)?;
        Some(i)
    }

    /// Searches for the sequentially **first** item in the parallel iterator
    /// that matches the given predicate, and returns its index.
    ///
    /// Like `ParallelIterator::find_first`, once a match is found,
    /// all attempts to the right of the match will be stopped, while
    /// attempts to the left must continue in case an earlier match
    /// is found.
    ///
    /// Note that not all parallel iterators have a useful order, much like
    /// sequential `HashMap` iteration, so "first" may be nebulous.  If you
    /// just want the first match that discovered anywhere in the iterator,
    /// `position_any` is a better choice.
    ///
    /// # Examples
    ///
    /// ```
    /// use rayon::prelude::*;
    ///
    /// let a = [1, 2, 3, 3];
    ///
    /// assert_eq!(a.par_iter().position_first(|&x| x == 3), Some(2));
    ///
    /// assert_eq!(a.par_iter().position_first(|&x| x == 100), None);
    /// ```
    fn position_first<P>(self, predicate: P) -> Option<usize>
    where
        P: Fn(Self::Item) -> bool + Sync + Send,
    {
        #[inline]
        fn check(&(_, p): &(usize, bool)) -> bool {
            p
        }

        let (i, _) = self.map(predicate).enumerate().find_first(check)?;
        Some(i)
    }

    /// Searches for the sequentially **last** item in the parallel iterator
    /// that matches the given predicate, and returns its index.
    ///
    /// Like `ParallelIterator::find_last`, once a match is found,
    /// all attempts to the left of the match will be stopped, while
    /// attempts to the right must continue in case a later match
    /// is found.
    ///
    /// Note that not all parallel iterators have a useful order, much like
    /// sequential `HashMap` iteration, so "last" may be nebulous.  When the
    /// order doesn't actually matter to you, `position_any` is a better
    /// choice.
    ///
    /// # Examples
    ///
    /// ```
    /// use rayon::prelude::*;
    ///
    /// let a = [1, 2, 3, 3];
    ///
    /// assert_eq!(a.par_iter().position_last(|&x| x == 3), Some(3));
    ///
    /// assert_eq!(a.par_iter().position_last(|&x| x == 100), None);
    /// ```
    fn position_last<P>(self, predicate: P) -> Option<usize>
    where
        P: Fn(Self::Item) -> bool + Sync + Send,
    {
        #[inline]
        fn check(&(_, p): &(usize, bool)) -> bool {
            p
        }

        let (i, _) = self.map(predicate).enumerate().find_last(check)?;
        Some(i)
    }

    #[doc(hidden)]
    #[deprecated(
        note = "parallel `position` does not search in order -- use `position_any`, \\
                `position_first`, or `position_last`"
    )]
    fn position<P>(self, predicate: P) -> Option<usize>
    where
        P: Fn(Self::Item) -> bool + Sync + Send,
    {
        self.position_any(predicate)
    }

    /// Searches for items in the parallel iterator that match the given
    /// predicate, and returns their indices.
    ///
    /// # Examples
    ///
    /// ```
    /// use rayon::prelude::*;
    ///
    /// let primes = vec![2, 3, 5, 7, 11, 13, 17, 19, 23, 29];
    ///
    /// // Find the positions of primes congruent to 1 modulo 6
    /// let p1mod6: Vec<_> = primes.par_iter().positions(|&p| p % 6 == 1).collect();
    /// assert_eq!(p1mod6, [3, 5, 7]); // primes 7, 13, and 19
    ///
    /// // Find the positions of primes congruent to 5 modulo 6
    /// let p5mod6: Vec<_> = primes.par_iter().positions(|&p| p % 6 == 5).collect();
    /// assert_eq!(p5mod6, [2, 4, 6, 8, 9]); // primes 5, 11, 17, 23, and 29
    /// ```
    fn positions<P>(self, predicate: P) -> Positions<Self, P>
    where
        P: Fn(Self::Item) -> bool + Sync + Send,
    {
        Positions::new(self, predicate)
    }

    /// Produces a new iterator with the elements of this iterator in
    /// reverse order.
    ///
    /// # Examples
    ///
    /// ```
    /// use rayon::prelude::*;
    ///
    /// let result: Vec<_> = (0..5)
    ///     .into_par_iter()
    ///     .rev()
    ///     .collect();
    ///
    /// assert_eq!(result, [4, 3, 2, 1, 0]);
    /// ```
    fn rev(self) -> Rev<Self> {
        Rev::new(self)
    }

    /// Sets the minimum length of iterators desired to process in each
    /// rayon job.  Rayon will not split any smaller than this length, but
    /// of course an iterator could already be smaller to begin with.
    ///
    /// Producers like `zip` and `interleave` will use greater of the two
    /// minimums.
    /// Chained iterators and iterators inside `flat_map` may each use
    /// their own minimum length.
    ///
    /// # Examples
    ///
    /// ```
    /// use rayon::prelude::*;
    ///
    /// let min = (0..1_000_000)
    ///     .into_par_iter()
    ///     .with_min_len(1234)
    ///     .fold(|| 0, |acc, _| acc + 1) // count how many are in this segment
    ///     .min().unwrap();
    ///
    /// assert!(min >= 1234);
    /// ```
    fn with_min_len(self, min: usize) -> MinLen<Self> {
        MinLen::new(self, min)
    }

    /// Sets the maximum length of iterators desired to process in each
    /// rayon job.  Rayon will try to split at least below this length,
    /// unless that would put it below the length from `with_min_len()`.
    /// For example, given min=10 and max=15, a length of 16 will not be
    /// split any further.
    ///
    /// Producers like `zip` and `interleave` will use lesser of the two
    /// maximums.
    /// Chained iterators and iterators inside `flat_map` may each use
    /// their own maximum length.
    ///
    /// # Examples
    ///
    /// ```
    /// use rayon::prelude::*;
    ///
    /// let max = (0..1_000_000)
    ///     .into_par_iter()
    ///     .with_max_len(1234)
    ///     .fold(|| 0, |acc, _| acc + 1) // count how many are in this segment
    ///     .max().unwrap();
    ///
    /// assert!(max <= 1234);
    /// ```
    fn with_max_len(self, max: usize) -> MaxLen<Self> {
        MaxLen::new(self, max)
    }

    /// Produces an exact count of how many items this iterator will
    /// produce, presuming no panic occurs.
    ///
    /// # Examples
    ///
    /// ```
    /// use rayon::prelude::*;
    ///
    /// let par_iter = (0..100).into_par_iter().zip(vec![0; 10]);
    /// assert_eq!(par_iter.len(), 10);
    ///
    /// let vec: Vec<_> = par_iter.collect();
    /// assert_eq!(vec.len(), 10);
    /// ```
    fn len(&self) -> usize;

    /// Internal method used to define the behavior of this parallel
    /// iterator. You should not need to call this directly.
    ///
    /// This method causes the iterator `self` to start producing
    /// items and to feed them to the consumer `consumer` one by one.
    /// It may split the consumer before doing so to create the
    /// opportunity to produce in parallel. If a split does happen, it
    /// will inform the consumer of the index where the split should
    /// occur (unlike `ParallelIterator::drive_unindexed()`).
    ///
    /// See the [README] for more details on the internals of parallel
    /// iterators.
    ///
    /// [README]: https://github.com/rayon-rs/rayon/blob/master/src/iter/plumbing/README.md
    fn drive<C: Consumer<Self::Item>>(self, consumer: C) -> C::Result;

    /// Internal method used to define the behavior of this parallel
    /// iterator. You should not need to call this directly.
    ///
    /// This method converts the iterator into a producer P and then
    /// invokes `callback.callback()` with P. Note that the type of
    /// this producer is not defined as part of the API, since
    /// `callback` must be defined generically for all producers. This
    /// allows the producer type to contain references; it also means
    /// that parallel iterators can adjust that type without causing a
    /// breaking change.
    ///
    /// See the [README] for more details on the internals of parallel
    /// iterators.
    ///
    /// [README]: https://github.com/rayon-rs/rayon/blob/master/src/iter/plumbing/README.md
    fn with_producer<CB: ProducerCallback<Self::Item>>(self, callback: CB) -> CB::Output;
}

/// `FromParallelIterator` implements the creation of a collection
/// from a [`ParallelIterator`]. By implementing
/// `FromParallelIterator` for a given type, you define how it will be
/// created from an iterator.
///
/// `FromParallelIterator` is used through [`ParallelIterator`]'s [`collect()`] method.
///
/// [`ParallelIterator`]: trait.ParallelIterator.html
/// [`collect()`]: trait.ParallelIterator.html#method.collect
///
/// # Examples
///
/// Implementing `FromParallelIterator` for your type:
///
/// ```
/// use rayon::prelude::*;
/// use std::mem;
///
/// struct BlackHole {
///     mass: usize,
/// }
///
/// impl<T: Send> FromParallelIterator<T> for BlackHole {
///     fn from_par_iter<I>(par_iter: I) -> Self
///         where I: IntoParallelIterator<Item = T>
///     {
///         let par_iter = par_iter.into_par_iter();
///         BlackHole {
///             mass: par_iter.count() * mem::size_of::<T>(),
///         }
///     }
/// }
///
/// let bh: BlackHole = (0i32..1000).into_par_iter().collect();
/// assert_eq!(bh.mass, 4000);
/// ```
pub trait FromParallelIterator<T>
where
    T: Send,
{
    /// Creates an instance of the collection from the parallel iterator `par_iter`.
    ///
    /// If your collection is not naturally parallel, the easiest (and
    /// fastest) way to do this is often to collect `par_iter` into a
    /// [`LinkedList`] or other intermediate data structure and then
    /// sequentially extend your collection. However, a more 'native'
    /// technique is to use the [`par_iter.fold`] or
    /// [`par_iter.fold_with`] methods to create the collection.
    /// Alternatively, if your collection is 'natively' parallel, you
    /// can use `par_iter.for_each` to process each element in turn.
    ///
    /// [`LinkedList`]: https://doc.rust-lang.org/std/collections/struct.LinkedList.html
    /// [`par_iter.fold`]: trait.ParallelIterator.html#method.fold
    /// [`par_iter.fold_with`]: trait.ParallelIterator.html#method.fold_with
    /// [`par_iter.for_each`]: trait.ParallelIterator.html#method.for_each
    fn from_par_iter<I>(par_iter: I) -> Self
    where
        I: IntoParallelIterator<Item = T>;
}

/// `ParallelExtend` extends an existing collection with items from a [`ParallelIterator`].
///
/// [`ParallelIterator`]: trait.ParallelIterator.html
///
/// # Examples
///
/// Implementing `ParallelExtend` for your type:
///
/// ```
/// use rayon::prelude::*;
/// use std::mem;
///
/// struct BlackHole {
///     mass: usize,
/// }
///
/// impl<T: Send> ParallelExtend<T> for BlackHole {
///     fn par_extend<I>(&mut self, par_iter: I)
///         where I: IntoParallelIterator<Item = T>
///     {
///         let par_iter = par_iter.into_par_iter();
///         self.mass += par_iter.count() * mem::size_of::<T>();
///     }
/// }
///
/// let mut bh = BlackHole { mass: 0 };
/// bh.par_extend(0i32..1000);
/// assert_eq!(bh.mass, 4000);
/// bh.par_extend(0i64..10);
/// assert_eq!(bh.mass, 4080);
/// ```
pub trait ParallelExtend<T>
where
    T: Send,
{
    /// Extends an instance of the collection with the elements drawn
    /// from the parallel iterator `par_iter`.
    ///
    /// # Examples
    ///
    /// ```
    /// use rayon::prelude::*;
    ///
    /// let mut vec = vec![];
    /// vec.par_extend(0..5);
    /// vec.par_extend((0..5).into_par_iter().map(|i| i * i));
    /// assert_eq!(vec, [0, 1, 2, 3, 4, 0, 1, 4, 9, 16]);
    /// ```
    fn par_extend<I>(&mut self, par_iter: I)
    where
        I: IntoParallelIterator<Item = T>;
}

/// `ParallelDrainFull` creates a parallel iterator that moves all items
/// from a collection while retaining the original capacity.
///
/// Types which are indexable typically implement [`ParallelDrainRange`]
/// instead, where you can drain fully with `par_drain(..)`.
///
/// [`ParallelDrainRange`]: trait.ParallelDrainRange.html
pub trait ParallelDrainFull {
    /// The draining parallel iterator type that will be created.
    type Iter: ParallelIterator<Item = Self::Item>;

    /// The type of item that the parallel iterator will produce.
    /// This is usually the same as `IntoParallelIterator::Item`.
    type Item: Send;

    /// Returns a draining parallel iterator over an entire collection.
    ///
    /// When the iterator is dropped, all items are removed, even if the
    /// iterator was not fully consumed. If the iterator is leaked, for example
    /// using `std::mem::forget`, it is unspecified how many items are removed.
    ///
    /// # Examples
    ///
    /// ```
    /// use rayon::prelude::*;
    /// use std::collections::{BinaryHeap, HashSet};
    ///
    /// let squares: HashSet<i32> = (0..10).map(|x| x * x).collect();
    ///
    /// let mut heap: BinaryHeap<_> = squares.iter().copied().collect();
    /// assert_eq!(
    ///     // heaps are drained in arbitrary order
    ///     heap.par_drain()
    ///         .inspect(|x| assert!(squares.contains(x)))
    ///         .count(),
    ///     squares.len(),
    /// );
    /// assert!(heap.is_empty());
    /// assert!(heap.capacity() >= squares.len());
    /// ```
    fn par_drain(self) -> Self::Iter;
}

/// `ParallelDrainRange` creates a parallel iterator that moves a range of items
/// from a collection while retaining the original capacity.
///
/// Types which are not indexable may implement [`ParallelDrainFull`] instead.
///
/// [`ParallelDrainFull`]: trait.ParallelDrainFull.html
pub trait ParallelDrainRange<Idx = usize> {
    /// The draining parallel iterator type that will be created.
    type Iter: ParallelIterator<Item = Self::Item>;

    /// The type of item that the parallel iterator will produce.
    /// This is usually the same as `IntoParallelIterator::Item`.
    type Item: Send;

    /// Returns a draining parallel iterator over a range of the collection.
    ///
    /// When the iterator is dropped, all items in the range are removed, even
    /// if the iterator was not fully consumed. If the iterator is leaked, for
    /// example using `std::mem::forget`, it is unspecified how many items are
    /// removed.
    ///
    /// # Examples
    ///
    /// ```
    /// use rayon::prelude::*;
    ///
    /// let squares: Vec<i32> = (0..10).map(|x| x * x).collect();
    ///
    /// println!("RangeFull");
    /// let mut vec = squares.clone();
    /// assert!(vec.par_drain(..)
    ///            .eq(squares.par_iter().copied()));
    /// assert!(vec.is_empty());
    /// assert!(vec.capacity() >= squares.len());
    ///
    /// println!("RangeFrom");
    /// let mut vec = squares.clone();
    /// assert!(vec.par_drain(5..)
    ///            .eq(squares[5..].par_iter().copied()));
    /// assert_eq!(&vec[..], &squares[..5]);
    /// assert!(vec.capacity() >= squares.len());
    ///
    /// println!("RangeTo");
    /// let mut vec = squares.clone();
    /// assert!(vec.par_drain(..5)
    ///            .eq(squares[..5].par_iter().copied()));
    /// assert_eq!(&vec[..], &squares[5..]);
    /// assert!(vec.capacity() >= squares.len());
    ///
    /// println!("RangeToInclusive");
    /// let mut vec = squares.clone();
    /// assert!(vec.par_drain(..=5)
    ///            .eq(squares[..=5].par_iter().copied()));
    /// assert_eq!(&vec[..], &squares[6..]);
    /// assert!(vec.capacity() >= squares.len());
    ///
    /// println!("Range");
    /// let mut vec = squares.clone();
    /// assert!(vec.par_drain(3..7)
    ///            .eq(squares[3..7].par_iter().copied()));
    /// assert_eq!(&vec[..3], &squares[..3]);
    /// assert_eq!(&vec[3..], &squares[7..]);
    /// assert!(vec.capacity() >= squares.len());
    ///
    /// println!("RangeInclusive");
    /// let mut vec = squares.clone();
    /// assert!(vec.par_drain(3..=7)
    ///            .eq(squares[3..=7].par_iter().copied()));
    /// assert_eq!(&vec[..3], &squares[..3]);
    /// assert_eq!(&vec[3..], &squares[8..]);
    /// assert!(vec.capacity() >= squares.len());
    /// ```
    fn par_drain<R: RangeBounds<Idx>>(self, range: R) -> Self::Iter;
}

/// We hide the `Try` trait in a private module, as it's only meant to be a
/// stable clone of the standard library's `Try` trait, as yet unstable.
mod private {
    use std::convert::Infallible;
    use std::task::Poll;

    #[cfg(has_control_flow)]
    pub(crate) use std::ops::ControlFlow;

    #[cfg(not(has_control_flow))]
    #[allow(missing_debug_implementations)]
    pub enum ControlFlow<B, C = ()> {
        Continue(C),
        Break(B),
    }

    use self::ControlFlow::{Break, Continue};

    /// Clone of `std::ops::Try`.
    ///
    /// Implementing this trait is not permitted outside of `rayon`.
    pub trait Try {
        private_decl! {}

        type Output;
        type Residual;

        fn from_output(output: Self::Output) -> Self;

        fn from_residual(residual: Self::Residual) -> Self;

        fn branch(self) -> ControlFlow<Self::Residual, Self::Output>;
    }

    #[cfg(has_control_flow)]
    impl<B, C> Try for ControlFlow<B, C> {
        private_impl! {}

        type Output = C;
        type Residual = ControlFlow<B, Infallible>;

        fn from_output(output: Self::Output) -> Self {
            Continue(output)
        }

        fn from_residual(residual: Self::Residual) -> Self {
            match residual {
                Break(b) => Break(b),
                Continue(_) => unreachable!(),
            }
        }

        fn branch(self) -> ControlFlow<Self::Residual, Self::Output> {
            match self {
                Continue(c) => Continue(c),
                Break(b) => Break(Break(b)),
            }
        }
    }

    impl<T> Try for Option<T> {
        private_impl! {}

        type Output = T;
        type Residual = Option<Infallible>;

        fn from_output(output: Self::Output) -> Self {
            Some(output)
        }

        fn from_residual(residual: Self::Residual) -> Self {
            match residual {
                None => None,
                Some(_) => unreachable!(),
            }
        }

        fn branch(self) -> ControlFlow<Self::Residual, Self::Output> {
            match self {
                Some(c) => Continue(c),
                None => Break(None),
            }
        }
    }

    impl<T, E> Try for Result<T, E> {
        private_impl! {}

        type Output = T;
        type Residual = Result<Infallible, E>;

        fn from_output(output: Self::Output) -> Self {
            Ok(output)
        }

        fn from_residual(residual: Self::Residual) -> Self {
            match residual {
                Err(e) => Err(e),
                Ok(_) => unreachable!(),
            }
        }

        fn branch(self) -> ControlFlow<Self::Residual, Self::Output> {
            match self {
                Ok(c) => Continue(c),
                Err(e) => Break(Err(e)),
            }
        }
    }

    impl<T, E> Try for Poll<Result<T, E>> {
        private_impl! {}

        type Output = Poll<T>;
        type Residual = Result<Infallible, E>;

        fn from_output(output: Self::Output) -> Self {
            output.map(Ok)
        }

        fn from_residual(residual: Self::Residual) -> Self {
            match residual {
                Err(e) => Poll::Ready(Err(e)),
                Ok(_) => unreachable!(),
            }
        }

        fn branch(self) -> ControlFlow<Self::Residual, Self::Output> {
            match self {
                Poll::Pending => Continue(Poll::Pending),
                Poll::Ready(Ok(c)) => Continue(Poll::Ready(c)),
                Poll::Ready(Err(e)) => Break(Err(e)),
            }
        }
    }

    impl<T, E> Try for Poll<Option<Result<T, E>>> {
        private_impl! {}

        type Output = Poll<Option<T>>;
        type Residual = Result<Infallible, E>;

        fn from_output(output: Self::Output) -> Self {
            match output {
                Poll::Ready(o) => Poll::Ready(o.map(Ok)),
                Poll::Pending => Poll::Pending,
            }
        }

        fn from_residual(residual: Self::Residual) -> Self {
            match residual {
                Err(e) => Poll::Ready(Some(Err(e))),
                Ok(_) => unreachable!(),
            }
        }

        fn branch(self) -> ControlFlow<Self::Residual, Self::Output> {
            match self {
                Poll::Pending => Continue(Poll::Pending),
                Poll::Ready(None) => Continue(Poll::Ready(None)),
                Poll::Ready(Some(Ok(c))) => Continue(Poll::Ready(Some(c))),
                Poll::Ready(Some(Err(e))) => Break(Err(e)),
            }
        }
    }
}