{"id":102875,"date":"2022-01-06T09:37:14","date_gmt":"2022-01-06T07:37:14","guid":{"rendered":"https:\/\/prohoster.info\/blog\/novosti-interneta\/%d0%b2%d1%8b%d0%bf%d1%83%d1%81%d0%ba-python-%d0%b1%d0%b8%d0%b1%d0%bb%d0%b8%d0%be%d1%82%d0%b5%d0%ba%d0%b8-%d0%b4%d0%bb%d1%8f-%d0%bd%d0%b0%d1%83%d1%87%d0%bd%d1%8b%d1%85-%d0%b2%d1%8b%d1%87%d0%b8%d1%81"},"modified":"2022-01-06T09:37:14","modified_gmt":"2022-01-06T07:37:14","slug":"%d0%b2%d1%8b%d0%bf%d1%83%d1%81%d0%ba-python-%d0%b1%d0%b8%d0%b1%d0%bb%d0%b8%d0%be%d1%82%d0%b5%d0%ba%d0%b8-%d0%b4%d0%bb%d1%8f-%d0%bd%d0%b0%d1%83%d1%87%d0%bd%d1%8b%d1%85-%d0%b2%d1%8b%d1%87%d0%b8%d1%81","status":"publish","type":"post","link":"https:\/\/prohoster.info\/da\/blog\/news\/%d0%b2%d1%8b%d0%bf%d1%83%d1%81%d0%ba-python-%d0%b1%d0%b8%d0%b1%d0%bb%d0%b8%d0%be%d1%82%d0%b5%d0%ba%d0%b8-%d0%b4%d0%bb%d1%8f-%d0%bd%d0%b0%d1%83%d1%87%d0%bd%d1%8b%d1%85-%d0%b2%d1%8b%d1%87%d0%b8%d1%81","title":{"rendered":"Udgivelse af Python-biblioteket til videnskabelig beregning NumPy 1.22.0","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"<p>Udgaven af Python-biblioteket til videnskabelige beregninger NumPy 1.22 er tilg\u00e6ngelig; det er designet til at arbejde med multidimensionale arrays og matricer, samt tilbyder en stor samling af funktioner, der implementerer forskellige algoritmer relateret til brugen af matricer. NumPy er et af de mest anvendte biblioteker til videnskabelige beregninger. Projektets kode er skrevet i Python med optimeringer i C og distribueres under BSD-licensen.      <\/p>\n<p>I den nye version:  <\/p>\n<ul>\n<li class=\"l\"> Arbejdet med at definere annotationer for det prim\u00e6re navnerum er afsluttet.\n<li class=\"l\"> Et forel\u00f8bigt forslag til API Array, der overholder Python Array API-standardet og implementeres i et separat navnerum, er foresl\u00e5et. Det nye API er rettet mod at forberede standardfunktioner til arbejde med arrays, som ogs\u00e5 kan bruges i applikationer baseret p\u00e5 andre biblioteker som CuPy og JAX.\n<li class=\"l\"> En DLPack-backend er implementeret, der tilbyder st\u00f8tte til det samme format til udveksling af indhold mellem arrays (tensorer) mellem forskellige rammer.\n<li class=\"l\"> Et s\u00e6t metoder er tilf\u00f8jet med implementering af funktioner, der relaterer til begreberne kvantil og percentil.\n<li class=\"l\"> En ny brugerdefineret hukommelsesh\u00e5ndterer (numpy-allocator) er tilf\u00f8jet.\n<li class=\"l\"> Der er fortsat arbejde med at optimere funktioner og platforme ved hj\u00e6lp af SIMD-vektorordrer.\n<li class=\"l\"> St\u00f8tten til Python 3.7 er oph\u00f8rt; der kr\u00e6ves versioner af Python 3.8-3.10 for at arbejde.     <\/ul>\n<p>Kilde: <a content=\"nofollow\" rel=\"nofollow\" href=\"https:\/\/www.opennet.ru\/opennews\/art.shtml?num=56463\">opennet.ru<\/a> <\/p>","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"excerpt":{"rendered":"<p>\u0414\u043e\u0441\u0442\u0443\u043f\u0435\u043d \u0440\u0435\u043b\u0438\u0437 Python-\u0431\u0438\u0431\u043b\u0438\u043e\u0442\u0435\u043a\u0438 \u0434\u043b\u044f \u043d\u0430\u0443\u0447\u043d\u044b\u0445 \u0432\u044b\u0447\u0438\u0441\u043b\u0435\u043d\u0438\u0439 NumPy 1.22, \u043e\u0440\u0438\u0435\u043d\u0442\u0438\u0440\u043e\u0432\u0430\u043d\u043d\u043e\u0439 \u043d\u0430 \u0440\u0430\u0431\u043e\u0442\u0443 \u0441 \u043c\u043d\u043e\u0433\u043e\u043c\u0435\u0440\u043d\u044b\u043c\u0438 \u043c\u0430\u0441\u0441\u0438\u0432\u0430\u043c\u0438 \u0438 \u043c\u0430\u0442\u0440\u0438\u0446\u0430\u043c\u0438, \u0430 \u0442\u0430\u043a\u0436\u0435 \u043f\u0440\u0435\u0434\u043e\u0441\u0442\u0430\u0432\u043b\u044f\u044e\u0449\u0435\u0439 \u0431\u043e\u043b\u044c\u0448\u0443\u044e \u043a\u043e\u043b\u043b\u0435\u043a\u0446\u0438\u044e \u0444\u0443\u043d\u043a\u0446\u0438\u0439 \u0441 \u0440\u0435\u0430\u043b\u0438\u0437\u0430\u0446\u0438\u0435\u0439 \u0440\u0430\u0437\u043b\u0438\u0447\u043d\u044b\u0445 \u0430\u043b\u0433\u043e\u0440\u0438\u0442\u043c\u043e\u0432, \u0441\u0432\u044f\u0437\u0430\u043d\u043d\u044b\u0445 \u0441 \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u043d\u0438\u0435\u043c \u043c\u0430\u0442\u0440\u0438\u0446. NumPy \u044f\u0432\u043b\u044f\u0435\u0442\u0441\u044f \u043e\u0434\u043d\u043e\u0439 \u0438\u0437 \u043d\u0430\u0438\u0431\u043e\u043b\u0435\u0435 \u0432\u043e\u0441\u0442\u0440\u0435\u0431\u043e\u0432\u0430\u043d\u043d\u044b\u0445 \u0431\u0438\u0431\u043b\u0438\u043e\u0442\u0435\u043a, \u043f\u0440\u0438\u043c\u0435\u043d\u044f\u0435\u043c\u044b\u0445 \u0434\u043b\u044f \u043d\u0430\u0443\u0447\u043d\u044b\u0445 \u0440\u0430\u0441\u0447\u0451\u0442\u043e\u0432. \u041a\u043e\u0434 \u043f\u0440\u043e\u0435\u043a\u0442\u0430 \u043d\u0430\u043f\u0438\u0441\u0430\u043d \u043d\u0430 \u044f\u0437\u044b\u043a\u0435 Python \u0441 \u043f\u0440\u0438\u043c\u0435\u043d\u0435\u043d\u0438\u0435\u043c \u043e\u043f\u0442\u0438\u043c\u0438\u0437\u0430\u0446\u0438\u0439 \u043d\u0430 \u044f\u0437\u044b\u043a\u0435 \u0421\u0438 \u0438 \u0440\u0430\u0441\u043f\u0440\u043e\u0441\u0442\u0440\u0430\u043d\u044f\u0435\u0442\u0441\u044f [&hellip;]<\/p>\n","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[702],"tags":[],"class_list":["post-102875","post","type-post","status-publish","format-standard","hentry","category-news"],"aioseo_notices":[],"aioseo_head":"\n\t\t<!-- All in One SEO 5.0.3 - aioseo.com -->\n\t<meta name=\"description\" content=\"\u0414\u043e\u0441\u0442\u0443\u043f\u0435\u043d \u0440\u0435\u043b\u0438\u0437 Python-\u0431\u0438\u0431\u043b\u0438\u043e\u0442\u0435\u043a\u0438 \u0434\u043b\u044f \u043d\u0430\u0443\u0447\u043d\u044b\u0445 \u0432\u044b\u0447\u0438\u0441\u043b\u0435\u043d\u0438\u0439 NumPy 1.22, \u043e\u0440\u0438\u0435\u043d\u0442\u0438\u0440\u043e\u0432\u0430\u043d\u043d\u043e\u0439 \u043d\u0430 \u0440\u0430\u0431\u043e\u0442\u0443 \u0441 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