-
Notifications
You must be signed in to change notification settings - Fork 8
/
Copy pathroadmap.html
766 lines (584 loc) · 41.1 KB
/
roadmap.html
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
<!DOCTYPE html>
<html lang="en" data-content_root="./" >
<head>
<meta charset="utf-8" />
<meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="viewport" content="width=device-width, initial-scale=1" />
<title>NumPy roadmap — NumPy Enhancement Proposals</title>
<script data-cfasync="false">
document.documentElement.dataset.mode = localStorage.getItem("mode") || "";
document.documentElement.dataset.theme = localStorage.getItem("theme") || "";
</script>
<!--
this give us a css class that will be invisible only if js is disabled
-->
<noscript>
<style>
.pst-js-only { display: none !important; }
</style>
</noscript>
<!-- Loaded before other Sphinx assets -->
<link href="_static/styles/theme.css?digest=8878045cc6db502f8baf" rel="stylesheet" />
<link href="_static/styles/pydata-sphinx-theme.css?digest=8878045cc6db502f8baf" rel="stylesheet" />
<link rel="stylesheet" type="text/css" href="_static/pygments.css?v=03e43079" />
<!-- So that users can add custom icons -->
<script src="_static/scripts/fontawesome.js?digest=8878045cc6db502f8baf"></script>
<!-- Pre-loaded scripts that we'll load fully later -->
<link rel="preload" as="script" href="_static/scripts/bootstrap.js?digest=8878045cc6db502f8baf" />
<link rel="preload" as="script" href="_static/scripts/pydata-sphinx-theme.js?digest=8878045cc6db502f8baf" />
<script src="_static/documentation_options.js?v=7f41d439"></script>
<script src="_static/doctools.js?v=888ff710"></script>
<script src="_static/sphinx_highlight.js?v=dc90522c"></script>
<script>DOCUMENTATION_OPTIONS.pagename = 'roadmap';</script>
<link rel="icon" href="_static/favicon.ico"/>
<link rel="index" title="Index" href="genindex.html" />
<link rel="search" title="Search" href="search.html" />
<link rel="next" title="Meta-NEPs (NEPs about NEPs or active Processes)" href="meta.html" />
<link rel="prev" title="Scope of NumPy" href="scope.html" />
<meta name="viewport" content="width=device-width, initial-scale=1"/>
<meta name="docsearch:language" content="en"/>
<meta name="docsearch:version" content="" />
<meta name="docbuild:last-update" content="Jan 31, 2025"/>
</head>
<body data-bs-spy="scroll" data-bs-target=".bd-toc-nav" data-offset="180" data-bs-root-margin="0px 0px -60%" data-default-mode="">
<div id="pst-skip-link" class="skip-link d-print-none"><a href="#main-content">Skip to main content</a></div>
<div id="pst-scroll-pixel-helper"></div>
<button type="button" class="btn rounded-pill" id="pst-back-to-top">
<i class="fa-solid fa-arrow-up"></i>Back to top</button>
<dialog id="pst-search-dialog">
<form class="bd-search d-flex align-items-center"
action="search.html"
method="get">
<i class="fa-solid fa-magnifying-glass"></i>
<input type="search"
class="form-control"
name="q"
placeholder="Search the docs ..."
aria-label="Search the docs ..."
autocomplete="off"
autocorrect="off"
autocapitalize="off"
spellcheck="false"/>
<span class="search-button__kbd-shortcut"><kbd class="kbd-shortcut__modifier">Ctrl</kbd>+<kbd>K</kbd></span>
</form>
</dialog>
<div class="pst-async-banner-revealer d-none">
<aside id="bd-header-version-warning" class="d-none d-print-none" aria-label="Version warning"></aside>
</div>
<header class="bd-header navbar navbar-expand-lg bd-navbar d-print-none">
<div class="bd-header__inner bd-page-width">
<button class="pst-navbar-icon sidebar-toggle primary-toggle" aria-label="Site navigation">
<span class="fa-solid fa-bars"></span>
</button>
<div class="col-lg-3 navbar-header-items__start">
<div class="navbar-item">
<a class="navbar-brand logo" href="content.html">
<img src="_static/numpylogo.svg" class="logo__image only-light" alt="NumPy Enhancement Proposals - Home"/>
<img src="_static/numpylogo_dark.svg" class="logo__image only-dark pst-js-only" alt="NumPy Enhancement Proposals - Home"/>
</a></div>
</div>
<div class="col-lg-9 navbar-header-items">
<div class="me-auto navbar-header-items__center">
<div class="navbar-item">
<nav>
<ul class="bd-navbar-elements navbar-nav">
<li class="nav-item current active">
<a class="nav-link nav-internal" href="index.html">
Index
</a>
</li>
<li class="nav-item ">
<a class="nav-link nav-internal" href="scope.html">
The Scope of NumPy
</a>
</li>
<li class="nav-item ">
<a class="nav-link nav-internal" href="#">
Current roadmap
</a>
</li>
<li class="nav-item ">
<a class="nav-link nav-external" href="https://github.com/numpy/numpy/issues?q=is%3Aopen+is%3Aissue+label%3A%2223+-+Wish+List%22">
Wishlist
</a>
</li>
</ul>
</nav></div>
</div>
<div class="navbar-header-items__end">
<div class="navbar-item navbar-persistent--container">
<button class="btn search-button-field search-button__button pst-js-only" title="Search" aria-label="Search" data-bs-placement="bottom" data-bs-toggle="tooltip">
<i class="fa-solid fa-magnifying-glass"></i>
<span class="search-button__default-text">Search</span>
<span class="search-button__kbd-shortcut"><kbd class="kbd-shortcut__modifier">Ctrl</kbd>+<kbd class="kbd-shortcut__modifier">K</kbd></span>
</button>
</div>
<div class="navbar-item">
<button class="btn btn-sm nav-link pst-navbar-icon theme-switch-button pst-js-only" aria-label="Color mode" data-bs-title="Color mode" data-bs-placement="bottom" data-bs-toggle="tooltip">
<i class="theme-switch fa-solid fa-sun fa-lg" data-mode="light" title="Light"></i>
<i class="theme-switch fa-solid fa-moon fa-lg" data-mode="dark" title="Dark"></i>
<i class="theme-switch fa-solid fa-circle-half-stroke fa-lg" data-mode="auto" title="System Settings"></i>
</button></div>
<div class="navbar-item"><ul class="navbar-icon-links"
aria-label="Icon Links">
<li class="nav-item">
<a href="https://github.com/numpy/numpy" title="GitHub" class="nav-link pst-navbar-icon" rel="noopener" target="_blank" data-bs-toggle="tooltip" data-bs-placement="bottom"><i class="fa-brands fa-square-github fa-lg" aria-hidden="true"></i>
<span class="sr-only">GitHub</span></a>
</li>
</ul></div>
</div>
</div>
<div class="navbar-persistent--mobile">
<button class="btn search-button-field search-button__button pst-js-only" title="Search" aria-label="Search" data-bs-placement="bottom" data-bs-toggle="tooltip">
<i class="fa-solid fa-magnifying-glass"></i>
<span class="search-button__default-text">Search</span>
<span class="search-button__kbd-shortcut"><kbd class="kbd-shortcut__modifier">Ctrl</kbd>+<kbd class="kbd-shortcut__modifier">K</kbd></span>
</button>
</div>
<button class="pst-navbar-icon sidebar-toggle secondary-toggle" aria-label="On this page">
<span class="fa-solid fa-outdent"></span>
</button>
</div>
</header>
<div class="bd-container">
<div class="bd-container__inner bd-page-width">
<dialog id="pst-primary-sidebar-modal"></dialog>
<div id="pst-primary-sidebar" class="bd-sidebar-primary bd-sidebar">
<div class="sidebar-header-items sidebar-primary__section">
<div class="sidebar-header-items__center">
<div class="navbar-item">
<nav>
<ul class="bd-navbar-elements navbar-nav">
<li class="nav-item current active">
<a class="nav-link nav-internal" href="index.html">
Index
</a>
</li>
<li class="nav-item ">
<a class="nav-link nav-internal" href="scope.html">
The Scope of NumPy
</a>
</li>
<li class="nav-item ">
<a class="nav-link nav-internal" href="#">
Current roadmap
</a>
</li>
<li class="nav-item ">
<a class="nav-link nav-external" href="https://github.com/numpy/numpy/issues?q=is%3Aopen+is%3Aissue+label%3A%2223+-+Wish+List%22">
Wishlist
</a>
</li>
</ul>
</nav></div>
</div>
<div class="sidebar-header-items__end">
<div class="navbar-item">
<button class="btn btn-sm nav-link pst-navbar-icon theme-switch-button pst-js-only" aria-label="Color mode" data-bs-title="Color mode" data-bs-placement="bottom" data-bs-toggle="tooltip">
<i class="theme-switch fa-solid fa-sun fa-lg" data-mode="light" title="Light"></i>
<i class="theme-switch fa-solid fa-moon fa-lg" data-mode="dark" title="Dark"></i>
<i class="theme-switch fa-solid fa-circle-half-stroke fa-lg" data-mode="auto" title="System Settings"></i>
</button></div>
<div class="navbar-item"><ul class="navbar-icon-links"
aria-label="Icon Links">
<li class="nav-item">
<a href="https://github.com/numpy/numpy" title="GitHub" class="nav-link pst-navbar-icon" rel="noopener" target="_blank" data-bs-toggle="tooltip" data-bs-placement="bottom"><i class="fa-brands fa-square-github fa-lg" aria-hidden="true"></i>
<span class="sr-only">GitHub</span></a>
</li>
</ul></div>
</div>
</div>
<div class="sidebar-primary-items__start sidebar-primary__section">
<div class="sidebar-primary-item">
<nav class="bd-docs-nav bd-links"
aria-label="Section Navigation">
<p class="bd-links__title" role="heading" aria-level="1">Section Navigation</p>
<div class="bd-toc-item navbar-nav"><ul class="current nav bd-sidenav">
<li class="toctree-l1"><a class="reference internal" href="scope.html">The Scope of NumPy</a></li>
<li class="toctree-l1 current active"><a class="current reference internal" href="#">Current roadmap</a></li>
</ul>
<ul class="nav bd-sidenav">
<li class="toctree-l1 has-children"><a class="reference internal" href="meta.html">Meta-NEPs (NEPs about NEPs or active Processes)</a><details><summary><span class="toctree-toggle" role="presentation"><i class="fa-solid fa-chevron-down"></i></span></summary><ul>
<li class="toctree-l2"><a class="reference internal" href="nep-0000.html">NEP 0 — Purpose and process</a></li>
<li class="toctree-l2"><a class="reference internal" href="nep-0023-backwards-compatibility.html">NEP 23 — Backwards compatibility and deprecation policy</a></li>
<li class="toctree-l2"><a class="reference internal" href="nep-0036-fair-play.html">NEP 36 — Fair play</a></li>
<li class="toctree-l2"><a class="reference internal" href="nep-0045-c_style_guide.html">NEP 45 — C style guide</a></li>
<li class="toctree-l2"><a class="reference internal" href="nep-0046-sponsorship-guidelines.html">NEP 46 — NumPy sponsorship guidelines</a></li>
<li class="toctree-l2"><a class="reference internal" href="nep-0048-spending-project-funds.html">NEP 48 — Spending NumPy project funds</a></li>
<li class="toctree-l2"><a class="reference internal" href="nep-template.html">NEP X — Template and instructions</a></li>
</ul>
</details></li>
<li class="toctree-l1 has-children"><a class="reference internal" href="provisional.html">Provisional NEPs (provisionally accepted; interface may change)</a><details><summary><span class="toctree-toggle" role="presentation"><i class="fa-solid fa-chevron-down"></i></span></summary><ul class="simple">
</ul>
</details></li>
<li class="toctree-l1 has-children"><a class="reference internal" href="accepted.html">Accepted NEPs (implementation in progress)</a><details><summary><span class="toctree-toggle" role="presentation"><i class="fa-solid fa-chevron-down"></i></span></summary><ul>
<li class="toctree-l2"><a class="reference internal" href="nep-0041-improved-dtype-support.html">NEP 41 — First step towards a new datatype system</a></li>
<li class="toctree-l2"><a class="reference internal" href="nep-0042-new-dtypes.html">NEP 42 — New and extensible DTypes</a></li>
<li class="toctree-l2"><a class="reference internal" href="nep-0044-restructuring-numpy-docs.html">NEP 44 — Restructuring the NumPy documentation</a></li>
<li class="toctree-l2"><a class="reference internal" href="nep-0051-scalar-representation.html">NEP 51 — Changing the representation of NumPy scalars</a></li>
</ul>
</details></li>
<li class="toctree-l1 has-children"><a class="reference internal" href="open.html">Open NEPs (under consideration)</a><details><summary><span class="toctree-toggle" role="presentation"><i class="fa-solid fa-chevron-down"></i></span></summary><ul>
<li class="toctree-l2"><a class="reference internal" href="nep-0043-extensible-ufuncs.html">NEP 43 — Enhancing the extensibility of UFuncs</a></li>
<li class="toctree-l2"><a class="reference internal" href="nep-0053-c-abi-evolution.html">NEP 53 — Evolving the NumPy C-API for NumPy 2.0</a></li>
<li class="toctree-l2"><a class="reference internal" href="nep-0054-simd-cpp-highway.html">NEP 54 — SIMD infrastructure evolution: adopting Google Highway when moving to C++?</a></li>
</ul>
</details></li>
<li class="toctree-l1 has-children"><a class="reference internal" href="finished.html">Finished NEPs</a><details><summary><span class="toctree-toggle" role="presentation"><i class="fa-solid fa-chevron-down"></i></span></summary><ul>
<li class="toctree-l2"><a class="reference internal" href="nep-0001-npy-format.html">NEP 1 — A simple file format for NumPy arrays</a></li>
<li class="toctree-l2"><a class="reference internal" href="nep-0005-generalized-ufuncs.html">NEP 5 — Generalized universal functions</a></li>
<li class="toctree-l2"><a class="reference internal" href="nep-0007-datetime-proposal.html">NEP 7 — A proposal for implementing some date/time types in NumPy</a></li>
<li class="toctree-l2"><a class="reference internal" href="nep-0010-new-iterator-ufunc.html">NEP 10 — Optimizing iterator/UFunc performance</a></li>
<li class="toctree-l2"><a class="reference internal" href="nep-0013-ufunc-overrides.html">NEP 13 — A mechanism for overriding Ufuncs</a></li>
<li class="toctree-l2"><a class="reference internal" href="nep-0014-dropping-python2.7-proposal.html">NEP 14 — Plan for dropping Python 2.7 support</a></li>
<li class="toctree-l2"><a class="reference internal" href="nep-0015-merge-multiarray-umath.html">NEP 15 — Merging multiarray and umath</a></li>
<li class="toctree-l2"><a class="reference internal" href="nep-0018-array-function-protocol.html">NEP 18 — A dispatch mechanism for NumPy's high level array functions</a></li>
<li class="toctree-l2"><a class="reference internal" href="nep-0019-rng-policy.html">NEP 19 — Random number generator policy</a></li>
<li class="toctree-l2"><a class="reference internal" href="nep-0020-gufunc-signature-enhancement.html">NEP 20 — Expansion of generalized universal function signatures</a></li>
<li class="toctree-l2"><a class="reference internal" href="nep-0022-ndarray-duck-typing-overview.html">NEP 22 — Duck typing for NumPy arrays – high level overview</a></li>
<li class="toctree-l2"><a class="reference internal" href="nep-0027-zero-rank-arrarys.html">NEP 27 — Zero rank arrays</a></li>
<li class="toctree-l2"><a class="reference internal" href="nep-0028-website-redesign.html">NEP 28 — numpy.org website redesign</a></li>
<li class="toctree-l2"><a class="reference internal" href="nep-0029-deprecation_policy.html">NEP 29 — Recommend Python and NumPy version support as a community policy standard</a></li>
<li class="toctree-l2"><a class="reference internal" href="nep-0032-remove-financial-functions.html">NEP 32 — Remove the financial functions from NumPy</a></li>
<li class="toctree-l2"><a class="reference internal" href="nep-0034-infer-dtype-is-object.html">NEP 34 — Disallow inferring ``dtype=object`` from sequences</a></li>
<li class="toctree-l2"><a class="reference internal" href="nep-0035-array-creation-dispatch-with-array-function.html">NEP 35 — Array creation dispatching with __array_function__</a></li>
<li class="toctree-l2"><a class="reference internal" href="nep-0038-SIMD-optimizations.html">NEP 38 — Using SIMD optimization instructions for performance</a></li>
<li class="toctree-l2"><a class="reference internal" href="nep-0040-legacy-datatype-impl.html">NEP 40 — Legacy datatype implementation in NumPy</a></li>
<li class="toctree-l2"><a class="reference internal" href="nep-0049.html">NEP 49 — Data allocation strategies</a></li>
<li class="toctree-l2"><a class="reference internal" href="nep-0050-scalar-promotion.html">NEP 50 — Promotion rules for Python scalars</a></li>
<li class="toctree-l2"><a class="reference internal" href="nep-0052-python-api-cleanup.html">NEP 52 — Python API cleanup for NumPy 2.0</a></li>
<li class="toctree-l2"><a class="reference internal" href="nep-0055-string_dtype.html">NEP 55 — Add a UTF-8 variable-width string DType to NumPy</a></li>
<li class="toctree-l2"><a class="reference internal" href="nep-0056-array-api-main-namespace.html">NEP 56 — Array API standard support in NumPy's main namespace</a></li>
</ul>
</details></li>
<li class="toctree-l1 has-children"><a class="reference internal" href="deferred.html">Deferred and Superseded NEPs</a><details><summary><span class="toctree-toggle" role="presentation"><i class="fa-solid fa-chevron-down"></i></span></summary><ul>
<li class="toctree-l2"><a class="reference internal" href="nep-0002-warnfix.html">NEP 2 — A proposal to build numpy without warning with a big set of warning flags</a></li>
<li class="toctree-l2"><a class="reference internal" href="nep-0003-math_config_clean.html">NEP 3 — Cleaning the math configuration of numpy.core</a></li>
<li class="toctree-l2"><a class="reference internal" href="nep-0004-datetime-proposal3.html">NEP 4 — A (third) proposal for implementing some date/time types in NumPy</a></li>
<li class="toctree-l2"><a class="reference internal" href="nep-0006-newbugtracker.html">NEP 6 — Replacing Trac with a different bug tracker</a></li>
<li class="toctree-l2"><a class="reference internal" href="nep-0008-groupby_additions.html">NEP 8 — A proposal for adding groupby functionality to NumPy</a></li>
<li class="toctree-l2"><a class="reference internal" href="nep-0009-structured_array_extensions.html">NEP 9 — Structured array extensions</a></li>
<li class="toctree-l2"><a class="reference internal" href="nep-0011-deferred-ufunc-evaluation.html">NEP 11 — Deferred UFunc evaluation</a></li>
<li class="toctree-l2"><a class="reference internal" href="nep-0012-missing-data.html">NEP 12 — Missing data functionality in NumPy</a></li>
<li class="toctree-l2"><a class="reference internal" href="nep-0021-advanced-indexing.html">NEP 21 — Simplified and explicit advanced indexing</a></li>
<li class="toctree-l2"><a class="reference internal" href="nep-0024-missing-data-2.html">NEP 24 — Missing data functionality - alternative 1 to NEP 12</a></li>
<li class="toctree-l2"><a class="reference internal" href="nep-0025-missing-data-3.html">NEP 25 — NA support via special dtypes</a></li>
<li class="toctree-l2"><a class="reference internal" href="nep-0026-missing-data-summary.html">NEP 26 — Summary of missing data NEPs and discussion</a></li>
<li class="toctree-l2"><a class="reference internal" href="nep-0030-duck-array-protocol.html">NEP 30 — Duck typing for NumPy arrays - implementation</a></li>
<li class="toctree-l2"><a class="reference internal" href="nep-0031-uarray.html">NEP 31 — Context-local and global overrides of the NumPy API</a></li>
<li class="toctree-l2"><a class="reference internal" href="nep-0037-array-module.html">NEP 37 — A dispatch protocol for NumPy-like modules</a></li>
<li class="toctree-l2"><a class="reference internal" href="nep-0047-array-api-standard.html">NEP 47 — Adopting the array API standard</a></li>
</ul>
</details></li>
<li class="toctree-l1 has-children"><a class="reference internal" href="rejected.html">Rejected and Withdrawn NEPs</a><details><summary><span class="toctree-toggle" role="presentation"><i class="fa-solid fa-chevron-down"></i></span></summary><ul>
<li class="toctree-l2"><a class="reference internal" href="nep-0016-abstract-array.html">NEP 16 — An abstract base class for identifying "duck arrays"</a></li>
<li class="toctree-l2"><a class="reference internal" href="nep-0017-split-out-maskedarray.html">NEP 17 — Split out masked arrays</a></li>
</ul>
</details></li>
</ul>
</div>
</nav></div>
</div>
<div class="sidebar-primary-items__end sidebar-primary__section">
<div class="sidebar-primary-item">
<div id="ethical-ad-placement"
class="flat"
data-ea-publisher="readthedocs"
data-ea-type="readthedocs-sidebar"
data-ea-manual="true">
</div></div>
</div>
</div>
<main id="main-content" class="bd-main" role="main">
<div class="bd-content">
<div class="bd-article-container">
<div class="bd-header-article d-print-none">
<div class="header-article-items header-article__inner">
<div class="header-article-items__start">
<div class="header-article-item">
<nav aria-label="Breadcrumb" class="d-print-none">
<ul class="bd-breadcrumbs">
<li class="breadcrumb-item breadcrumb-home">
<a href="content.html" class="nav-link" aria-label="Home">
<i class="fa-solid fa-home"></i>
</a>
</li>
<li class="breadcrumb-item"><a href="index.html" class="nav-link">Roadmap & NumPy enhancement proposals</a></li>
<li class="breadcrumb-item active" aria-current="page"><span class="ellipsis">NumPy roadmap</span></li>
</ul>
</nav>
</div>
</div>
</div>
</div>
<div id="searchbox"></div>
<article class="bd-article">
<section id="numpy-roadmap">
<h1>NumPy roadmap<a class="headerlink" href="#numpy-roadmap" title="Link to this heading">#</a></h1>
<p>This is a live snapshot of tasks and features we will be investing resources
in. It may be used to encourage and inspire developers and to search for
funding.</p>
<section id="interoperability">
<h2>Interoperability<a class="headerlink" href="#interoperability" title="Link to this heading">#</a></h2>
<p>We aim to make it easier to interoperate with NumPy. There are many NumPy-like
packages that add interesting new capabilities to the Python ecosystem, as well
as many libraries that extend NumPy’s model in various ways. Work in NumPy to
facilitate interoperability with all such packages, and the code that uses them,
may include (among other things) interoperability protocols, better duck typing
support and ndarray subclass handling.</p>
<p>The key goal is: <em>make it easy for code written for NumPy to also work with
other NumPy-like projects.</em> This will enable GPU support via, e.g, CuPy, JAX or PyTorch,
distributed array support via Dask, and writing special-purpose arrays (either
from scratch, or as a <code class="docutils literal notranslate"><span class="pre">numpy.ndarray</span></code> subclass) that work well with SciPy,
scikit-learn and other such packages. A large step forward in this area was
made in NumPy 2.0, with adoption of and compliance with the array API standard
(v2022.12, see <a class="reference internal" href="nep-0047-array-api-standard.html#nep47"><span class="std std-ref">NEP 47 — Adopting the array API standard</span></a>). Future work in this direction will include
support for newer versions of the array API standard, and adding features as
needed based on real-world experience and needs.</p>
<p>In addition, the <code class="docutils literal notranslate"><span class="pre">__array_ufunc__</span></code> and <code class="docutils literal notranslate"><span class="pre">__array_function__</span></code> protocols
fulfill a role here - they are stable and used by several downstream projects.</p>
</section>
<section id="performance">
<h2>Performance<a class="headerlink" href="#performance" title="Link to this heading">#</a></h2>
<p>Improvements to NumPy’s performance are important to many users. We have
focused this effort on Universal SIMD (see <a class="reference internal" href="nep-0038-SIMD-optimizations.html#nep38"><span class="std std-ref">NEP 38 — Using SIMD optimization instructions for performance</span></a>) intrinsics which
provide nice improvements across various hardware platforms via an abstraction
layer. The infrastructure is in place, and we welcome follow-on PRs to add
SIMD support across relevant NumPy functionality.</p>
<p>Transitioning from C to C++, both in the SIMD infrastructure and in NumPy
internals more widely, is in progress. We have also started to make use of
Google Highway (see <a class="reference internal" href="nep-0054-simd-cpp-highway.html#nep54"><span class="std std-ref">NEP 54 — SIMD infrastructure evolution: adopting Google Highway when moving to C++?</span></a>), and that usage is likely to expand. Work
towards support for newer SIMD instruction sets, like SVE on arm64, is ongoing.</p>
<p>Other performance improvement ideas include:</p>
<ul class="simple">
<li><p>A better story around parallel execution (related is support for free-threaded
CPython, see further down).</p></li>
<li><p>Enable the ability to allow NumPy to use faster, but less precise,
implementations for ufuncs.
Until now, the only state modifying ufunc behavior has been <code class="docutils literal notranslate"><span class="pre">np.errstate</span></code>.
But, with NumPy 2.0 improvements in the <code class="docutils literal notranslate"><span class="pre">np.errstate</span></code> and the ufunc C
implementation make this type of addition easier.</p></li>
<li><p>Optimizations in individual functions.</p></li>
</ul>
<p>Furthermore we would like to improve the benchmarking system, in terms of coverage,
easy of use, and publication of the results. Benchmarking PRs/branches compared
to the <cite>main</cite> branch is a primary purpose, and required for PRs that are
performance-focused (e.g., adding SIMD acceleration to a function). In
addition, we’d like a performance overview like the one we had <a class="reference external" href="https://pv.github.io/numpy-bench">here</a>, set up in a way that is more
maintainable long-term.</p>
</section>
<section id="documentation-and-website">
<h2>Documentation and website<a class="headerlink" href="#documentation-and-website" title="Link to this heading">#</a></h2>
<p>The NumPy <a class="reference external" href="https://www.numpy.org/devdocs">documentation</a> is of varying
quality. The API documentation is in good shape; tutorials and high-level
documentation on many topics are missing or outdated. See <a class="reference internal" href="nep-0044-restructuring-numpy-docs.html#nep44"><span class="std std-ref">NEP 44 — Restructuring the NumPy documentation</span></a> for
planned improvements. Adding more tutorials is underway in the
<a class="reference external" href="https://github.com/numpy/numpy-tutorials">numpy-tutorials repo</a>.</p>
<p>We also intend to make all the example code in our documentation interactive -
work is underway to do so via <code class="docutils literal notranslate"><span class="pre">jupyterlite-sphinx</span></code> and Pyodide. NumPy 2.3.0
provides interactive documentation for examples as a pilot for this effort.</p>
<p>Our website (<a class="reference external" href="https://numpy.org">https://numpy.org</a>) is in good shape. Further work on expanding the
number of languages that the website is translated in is desirable. As are
improvements to the interactive notebook widget, through JupyterLite.</p>
</section>
<section id="extensibility">
<h2>Extensibility<a class="headerlink" href="#extensibility" title="Link to this heading">#</a></h2>
<p>We aim to continue making it easier to extend NumPy. The primary topic here is to
improve the dtype system - see for example <a class="reference internal" href="nep-0041-improved-dtype-support.html#nep41"><span class="std std-ref">NEP 41 — First step towards a new datatype system</span></a> and related NEPs linked
from it. In NumPy 2.0, a <a class="reference external" href="https://numpy.org/devdocs/reference/c-api/array.html#custom-data-types">new C API for user-defined dtypes</a>
was made public. We aim to encourage its usage and improve this API further,
including support for writing a dtype in Python.</p>
<p>Ideas for new dtypes that may be developed outside of the main NumPy repository
first, and that could potentially be upstreamed into NumPy later, include:</p>
<ul class="simple">
<li><p>A quad-precision (128-bit) dtype</p></li>
<li><p>A <code class="docutils literal notranslate"><span class="pre">bfloat16</span></code> dtype</p></li>
<li><p>A fixed-width string dtype which supports encodings (e.g., <code class="docutils literal notranslate"><span class="pre">utf8</span></code> or
<code class="docutils literal notranslate"><span class="pre">latin1</span></code>)</p></li>
<li><p>A unit dtype</p></li>
</ul>
<p>We further plan to extend the ufunc C API as needs arise.
One possibility here is creating a new, more powerful, API to allow hooking
into existing NumPy ufunc implementations.</p>
</section>
<section id="user-experience">
<h2>User experience<a class="headerlink" href="#user-experience" title="Link to this heading">#</a></h2>
<section id="type-annotations">
<h3>Type annotations<a class="headerlink" href="#type-annotations" title="Link to this heading">#</a></h3>
<p>Type annotations for most NumPy functionality is complete (although some
submodules like <code class="docutils literal notranslate"><span class="pre">numpy.ma</span></code> are missing return types), so users can use tools
like <a class="reference external" href="https://mypy.readthedocs.io">mypy</a> to type check their code and IDEs can improve their support
for NumPy. Improving those type annotations, for example to support annotating
array shapes (see <a class="reference external" href="https://github.com/numpy/numpy/issues/16544">gh-16544</a>),
is ongoing.</p>
</section>
<section id="platform-support">
<h3>Platform support<a class="headerlink" href="#platform-support" title="Link to this heading">#</a></h3>
<p>We aim to increase our support for different hardware architectures. This
includes adding CI coverage when CI services are available, providing wheels on
PyPI for platforms that are in high enough demand (e.g., we added <code class="docutils literal notranslate"><span class="pre">musllinux</span></code>
ones for NumPy 2.0), and resolving build issues on platforms that we don’t test
in CI (e.g., AIX).</p>
<p>We intend to write a NEP covering the support levels we provide and what is
required for a platform to move to a higher tier of support, similar to
<a class="reference external" href="https://peps.python.org/pep-0011/">PEP 11</a>.</p>
</section>
<section id="further-consistency-fixes-to-promotion-and-scalar-logic">
<h3>Further consistency fixes to promotion and scalar logic<a class="headerlink" href="#further-consistency-fixes-to-promotion-and-scalar-logic" title="Link to this heading">#</a></h3>
<p>NumPy 2.0 fixed many issues around promotion especially with respect to scalars.
We plan to continue fixing remaining inconsistencies.
For example, NumPy converts 0-D objects to scalars, and some promotions
still allowed by NumPy are problematic.</p>
</section>
<section id="support-for-free-threaded-cpython">
<h3>Support for free-threaded CPython<a class="headerlink" href="#support-for-free-threaded-cpython" title="Link to this heading">#</a></h3>
<p>CPython 3.13 will be the first release to offer a free-threaded build (i.e.,
a CPython build with the GIL disabled). Work is in progress to support this
well in NumPy. After that is stable and complete, there may be opportunities to
actually make use of the potential for performance improvements from
free-threaded CPython, or make it easier to do so for NumPy’s users.</p>
</section>
<section id="binary-size-reduction">
<h3>Binary size reduction<a class="headerlink" href="#binary-size-reduction" title="Link to this heading">#</a></h3>
<p>The number of downloads of NumPy from PyPI and other platforms continues to
increase - as of May 2024 we’re at >200 million downloads/month from PyPI
alone. Reducing the size of an installed NumPy package has many benefits:
faster installs, lower disk space usage, smaller load on PyPI, less
environmental impact, easier to fit more packages on top of NumPy in
resource-constrained environments and platforms like AWS Lambda, lower latency
for Pyodide users, and so on. We aim for significant reductions, as well as
making it easier for end users and packagers to produce smaller custom builds
(e.g., we added support for stripping tests before 2.1.0). See
<a class="reference external" href="https://github.com/numpy/numpy/issues/25737">gh-25737</a> for details.</p>
</section>
<section id="support-use-of-cpython-s-limited-c-api">
<h3>Support use of CPython’s limited C API<a class="headerlink" href="#support-use-of-cpython-s-limited-c-api" title="Link to this heading">#</a></h3>
<p>Use of the CPython limited C API, allowing producing <code class="docutils literal notranslate"><span class="pre">abi3</span></code> wheels that use
the stable ABI and are hence independent of CPython feature releases, has
benefits for both downstream packages that use NumPy’s C API and for NumPy
itself. In NumPy 2.0, work was done to enable using the limited C API with
the Cython support in NumPy (see <a class="reference external" href="https://github.com/numpy/numpy/pull/25531">gh-25531</a>).
More work and testing is needed to ensure full support for downstream packages.</p>
<p>We also want to explore what is needed for NumPy itself to use the limited
C API - this would make testing new CPython dev and pre-release versions across
the ecosystem easier, and significantly reduce the maintenance effort for CI
jobs in NumPy itself.</p>
</section>
<section id="create-a-header-only-package-for-numpy">
<h3>Create a header-only package for NumPy<a class="headerlink" href="#create-a-header-only-package-for-numpy" title="Link to this heading">#</a></h3>
<p>We have reduced the platform-dependent content in the public NumPy headers to
almost nothing. It is now feasible to create a separate package with only
NumPy headers and a discovery mechanism for them, in order to enable downstream
packages to build against the NumPy C API without having NumPy installed.
This will make it easier/cheaper to use NumPy’s C API, especially on more
niche platforms for which we don’t provide wheels.</p>
</section>
</section>
<section id="numpy-2-0-stabilization-downstream-usage">
<h2>NumPy 2.0 stabilization & downstream usage<a class="headerlink" href="#numpy-2-0-stabilization-downstream-usage" title="Link to this heading">#</a></h2>
<p>We made a very large amount of changes (and improvements!) in NumPy 2.0. The
release process has taken a very long time, and part of the ecosystem is still
catching up. We may need to slow down for a while, and possibly help the rest
of the ecosystem with adapting to the ABI and API changes.</p>
<p>We will need to assess the costs and benefits to NumPy itself,
downstream package authors, and end users. Based on that assessment, we need to
come to a conclusion on whether it’s realistic to do another ABI-breaking
release again in the future or not. This will also inform the future evolution
of our C API.</p>
</section>
<section id="security">
<h2>Security<a class="headerlink" href="#security" title="Link to this heading">#</a></h2>
<p>NumPy is quite secure - we get only a limited number of reports about potential
vulnerabilities, and most of those are incorrect. We have made strides with a
documented security policy, a private disclosure method, and maintaining an
OpenSSF scorecard (with a high score). However, we have not changed much in how
we approach supply chain security in quite a while. We aim to make improvements
here, for example achieving fully reproducible builds for all the build
artifacts we publish - and providing full provenance information for them.</p>
</section>
<section id="maintenance">
<h2>Maintenance<a class="headerlink" href="#maintenance" title="Link to this heading">#</a></h2>
<ul class="simple">
<li><p><code class="docutils literal notranslate"><span class="pre">numpy.ma</span></code> is still in poor shape and under-maintained. It needs to be
improved, ideas include:</p>
<ul>
<li><p>Rewrite masked arrays to not be a ndarray subclass – maybe in a separate project?</p></li>
<li><p>MaskedArray as a duck-array type, and/or</p></li>
<li><p>dtypes that support missing values</p></li>
</ul>
</li>
<li><p>Write a strategy on how to deal with overlap between NumPy and SciPy for <code class="docutils literal notranslate"><span class="pre">linalg</span></code>.</p></li>
<li><p>Deprecate <code class="docutils literal notranslate"><span class="pre">np.matrix</span></code> (very slowly) - this is feasible once the switch-over
from sparse matrices to sparse arrays in SciPy is complete.</p></li>
<li><p>Add new indexing modes for “vectorized indexing” and “outer indexing” (see <a class="reference internal" href="nep-0021-advanced-indexing.html#nep21"><span class="std std-ref">NEP 21 — Simplified and explicit advanced indexing</span></a>).</p></li>
<li><p>Make the polynomial API easier to use.</p></li>
</ul>
</section>
</section>
</article>
</div>
<dialog id="pst-secondary-sidebar-modal"></dialog>
<div id="pst-secondary-sidebar" class="bd-sidebar-secondary bd-toc"><div class="sidebar-secondary-items sidebar-secondary__inner">
<div class="sidebar-secondary-item">
<div
id="pst-page-navigation-heading-2"
class="page-toc tocsection onthispage">
<i class="fa-solid fa-list"></i> On this page
</div>
<nav class="bd-toc-nav page-toc" aria-labelledby="pst-page-navigation-heading-2">
<ul class="visible nav section-nav flex-column">
<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#interoperability">Interoperability</a></li>
<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#performance">Performance</a></li>
<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#documentation-and-website">Documentation and website</a></li>
<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#extensibility">Extensibility</a></li>
<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#user-experience">User experience</a><ul class="nav section-nav flex-column">
<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#type-annotations">Type annotations</a></li>
<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#platform-support">Platform support</a></li>
<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#further-consistency-fixes-to-promotion-and-scalar-logic">Further consistency fixes to promotion and scalar logic</a></li>
<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#support-for-free-threaded-cpython">Support for free-threaded CPython</a></li>
<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#binary-size-reduction">Binary size reduction</a></li>
<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#support-use-of-cpython-s-limited-c-api">Support use of CPython’s limited C API</a></li>
<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#create-a-header-only-package-for-numpy">Create a header-only package for NumPy</a></li>
</ul>
</li>
<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#numpy-2-0-stabilization-downstream-usage">NumPy 2.0 stabilization & downstream usage</a></li>
<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#security">Security</a></li>
<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#maintenance">Maintenance</a></li>
</ul>
</nav></div>
</div></div>
</div>
<footer class="bd-footer-content">
</footer>
</main>
</div>
</div>
<!-- Scripts loaded after <body> so the DOM is not blocked -->
<script defer src="_static/scripts/bootstrap.js?digest=8878045cc6db502f8baf"></script>
<script defer src="_static/scripts/pydata-sphinx-theme.js?digest=8878045cc6db502f8baf"></script>
<footer class="bd-footer">
<div class="bd-footer__inner bd-page-width">
<div class="footer-items__start">
<div class="footer-item">
<p class="copyright">
© Copyright 2017-2025, NumPy Developers.
<br/>
</p>
</div>
<div class="footer-item">
<p class="sphinx-version">
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 7.2.6.
<br/>
</p>
</div>
</div>
<div class="footer-items__end">
<div class="footer-item">
<p class="theme-version">
<!-- # L10n: Setting the PST URL as an argument as this does not need to be localized -->
Built with the <a href="https://pydata-sphinx-theme.readthedocs.io/en/stable/index.html">PyData Sphinx Theme</a> 0.16.1.
</p></div>
</div>
</div>
</footer>
</body>
</html>