{"id":3373,"date":"2022-08-08T01:22:05","date_gmt":"2022-08-07T22:22:05","guid":{"rendered":"https:\/\/demensdeum.com\/blog\/?p=3373"},"modified":"2024-12-16T22:32:17","modified_gmt":"2024-12-16T19:32:17","slug":"heapsort","status":"publish","type":"post","link":"https:\/\/demensdeum.com\/blog\/pt\/2022\/08\/08\/heapsort\/","title":{"rendered":"Heapsort"},"content":{"rendered":"<p>Heapsort \u2013 classifica\u00e7\u00e3o em pir\u00e2mide. Complexidade de tempo do algoritmo &#8211; O (n log n), r\u00e1pido, certo? Eu chamaria isso de classifica\u00e7\u00e3o de classifica\u00e7\u00e3o de pedras que caem. Parece-me que a maneira mais f\u00e1cil de explicar \u00e9 visualmente.<\/p>\n<p><iframe loading=\"lazy\" title=\"Cats Who Knock Things Over! (A compilation)\" width=\"620\" height=\"349\" src=\"https:\/\/www.youtube.com\/embed\/09CC-dYDNMQ?feature=oembed\" frameborder=\"0\" allow=\"accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share\" referrerpolicy=\"strict-origin-when-cross-origin\" allowfullscreen><\/iframe><\/p>\n<p>A entrada \u00e9 uma lista de n\u00fameros, por exemplo:<br \/>\n5, 0, 7, 2, 3, 9, 4<\/p>\n<p>Da esquerda para a direita, uma estrutura de dados \u00e9 criada &#8211; uma \u00e1rvore bin\u00e1ria, ou como eu chamo &#8211; pir\u00e2mide. Os elementos da pir\u00e2mide podem ter no m\u00e1ximo dois elementos filhos, mas apenas um elemento superior.<\/p>\n<p>Vamos fazer uma \u00e1rvore bin\u00e1ria:<br \/>\n\u2800\u28005<br \/>\n\u28000\u28007<br \/>\n2 3 9 4<\/p>\n<p>Se voc\u00ea olhar a pir\u00e2mide por muito tempo, ver\u00e1 que s\u00e3o apenas n\u00fameros de uma matriz, vindo um ap\u00f3s o outro, o n\u00famero de elementos em cada andar \u00e9 multiplicado por dois.<\/p>\n<p>A seguir, a divers\u00e3o come\u00e7a; vamos classificar a pir\u00e2mide de baixo para cima usando o m\u00e9todo das pedras caindo (heapify). A classifica\u00e7\u00e3o poderia ser iniciada a partir do \u00faltimo andar (2 3 9 4), mas n\u00e3o adianta porque n\u00e3o h\u00e1 piso abaixo onde voc\u00ea possa cair.<\/p>\n<p>Portanto, come\u00e7amos a descartar elementos do pen\u00faltimo andar (0 7)<br \/>\n\u2800\u28005<br \/>\n\u28000\u2800<strong>7<\/strong><br \/>\n2 3 9 4<\/p>\n<p>O primeiro elemento a cair \u00e9 selecionado da direita, no nosso caso \u00e9 7, ent\u00e3o olhamos o que est\u00e1 abaixo dele, e abaixo dele est\u00e3o 9 e 4, nove \u00e9 maior que quatro, e tamb\u00e9m nove \u00e9 maior que Sete! Colocamos 7 em 9 e colocamos 9 no lugar 7.<br \/>\n\u2800\u28005<br \/>\n\u28000\u28009<br \/>\n2 3 <strong>7<\/strong> 4<\/p>\n<p>A seguir, entendemos que o sete n\u00e3o tem onde cair, passamos para o n\u00famero 0, que est\u00e1 localizado no pen\u00faltimo andar \u00e0 esquerda:<br \/>\n\u2800\u28005<br \/>\n\u2800<strong>0<\/strong>\u28009<br \/>\n2 3 7 4<\/p>\n<p>Vamos ver o que h\u00e1 por baixo &#8211; 2 e 3, dois \u00e9 menor que tr\u00eas, tr\u00eas \u00e9 maior que zero, ent\u00e3o trocamos zero por tr\u00eas:<br \/>\n\u2800\u28005<br \/>\n\u28003\u28009<br \/>\n2 <strong>0<\/strong> 7 4<\/p>\n<p>Quando chegar ao final do andar, v\u00e1 para o andar de cima e largue tudo l\u00e1, se puder.<br \/>\nO resultado \u00e9 uma estrutura de dados &#8211; um heap, ou seja, max heap, porque no topo est\u00e1 o maior elemento:<br \/>\n\u2800\u2800<strong>9<\/strong><br \/>\n\u28003\u28007<br \/>\n2 0 5 4<\/p>\n<p>Se voc\u00ea retornar para uma representa\u00e7\u00e3o de array, voc\u00ea obter\u00e1 uma lista:<br \/>\n[<strong>9<\/strong>, 3, 7, 2, 0, 5, 4]<\/p>\n<p>A partir disso podemos concluir que ao trocar o primeiro e o \u00faltimo elemento, obtemos o primeiro n\u00famero na posi\u00e7\u00e3o final ordenada, ou seja, 9 deve estar no final da lista ordenada, troque de lugar:<br \/>\n[4, 3, 7, 2, 0, 5, <strong>9<\/strong>]<\/p>\n<p>Vejamos uma \u00e1rvore bin\u00e1ria:<br \/>\n\u2800\u28004<br \/>\n\u28003\u28007<br \/>\n2 0 5 9<\/p>\n<p>O resultado \u00e9 uma situa\u00e7\u00e3o em que a parte inferior da \u00e1rvore est\u00e1 ordenada, basta colocar 4 na posi\u00e7\u00e3o correta, repetir o algoritmo, mas n\u00e3o levar em considera\u00e7\u00e3o os n\u00fameros j\u00e1 ordenados, nomeadamente 9:<br \/>\n\u2800\u2800<strong>4<\/strong><br \/>\n\u28003\u28007<br \/>\n2 0 5 9<\/p>\n<p>\u2800\u28007<br \/>\n\u28003\u2800<strong>4<\/strong><br \/>\n2 0 5 9<\/p>\n<p>\u2800\u28007<br \/>\n\u28003\u28005<br \/>\n2 0 <strong>4<\/strong> 9<\/p>\n<p>Acontece que n\u00f3s, tendo perdido 4, aumentamos o pr\u00f3ximo maior n\u00famero depois de 9 &#8211; 7. Troque o \u00faltimo n\u00famero n\u00e3o classificado (4) e o maior n\u00famero (7)<br \/>\n\u2800\u28004<br \/>\n\u28003\u28005<br \/>\n2 0 7 9<\/p>\n<p>Acontece que agora temos dois n\u00fameros na posi\u00e7\u00e3o final correta:<br \/>\n4, 3, 5, 2, 0, <strong>7<\/strong>, <strong>9<\/strong><\/p>\n<p>Em seguida repetimos o algoritmo de classifica\u00e7\u00e3o, ignorando os j\u00e1 classificados, no final obtemos um <a href=\"https:\/\/www.youtube.com\/watch?v=nnun8y7r8_U\" target=\"_blank\" rel= \"noopener\">heap<\/ a> tipo:<br \/>\n\u2800\u28000<br \/>\n\u28002\u28003<br \/>\n4 5 7 9<\/p>\n<p>Ou como uma lista:<br \/>\n0, 2, 3, 4, 5, 7, 9<\/p>\n<h3>Implementa\u00e7\u00e3o<\/h3>\n<p>O algoritmo geralmente \u00e9 dividido em tr\u00eas fun\u00e7\u00f5es:<\/p>\n<ol>\n<li>Criando uma pilha<\/li>\n<li>Algoritmo de peneira\u00e7\u00e3o (heapify)<\/li>\n<li>Substituindo o \u00faltimo elemento n\u00e3o classificado e o primeiro<\/li>\n<\/ol>\n<p>O heap \u00e9 criado percorrendo a pen\u00faltima linha da \u00e1rvore bin\u00e1ria usando a fun\u00e7\u00e3o heapify, da direita para a esquerda, at\u00e9 o final do array. A seguir no ciclo, \u00e9 feita a primeira substitui\u00e7\u00e3o de n\u00fameros, ap\u00f3s a qual o primeiro elemento cai\/permanece no lugar, como resultado o elemento maior cai em primeiro lugar, o ciclo \u00e9 repetido com uma diminui\u00e7\u00e3o de participantes em um, porque ap\u00f3s cada passagem, os n\u00fameros classificados permanecem no final da lista.<\/p>\n<p>Exemplo de Heapsort em Ruby:<\/p>\n<div class=\"hcb_wrap\">\n<div class=\"hcb_wrap\">\n<div class=\"hcb_wrap\">\n<pre class=\"prism line-numbers lang-unknown\" data-lang=\"unknown\"><code>\n\n\n\n\nmodule Colors\n\n\n\n    BLUE = \"\\033[94m\"\n\n\n\n    RED = \"\\033[31m\"\n\n\n\n    STOP = \"\\033[0m\"\n\n\n\nend\n\n\n\n\n\n\n\ndef heapsort(rawNumbers)\n\n\n\n    numbers = rawNumbers.dup\n\n\n\n\n\n\n\n    def swap(numbers, from, to)\n\n\n\n        temp = numbers[from]\n\n\n\n        numbers[from] = numbers[to]\n\n\n\n        numbers[to] = temp\n\n\n\n    end\n\n\n\n\n\n\n\n    def heapify(numbers)\n\n\n\n        count = numbers.length()\n\n\n\n        lastParentNode = (count - 2) \/ 2\n\n\n\n\n\n\n\n        for start in lastParentNode.downto(0)\n\n\n\n            siftDown(numbers, start, count - 1)\n\n\n\n            start -= 1 \n\n\n\n        end\n\n\n\n\n\n\n\n        if DEMO\n\n\n\n            puts \"--- heapify ends ---\"\n\n\n\n        end\n\n\n\n    end\n\n\n\n\n\n\n\n    def siftDown(numbers, start, rightBound)      \n\n\n\n        cursor = start\n\n\n\n        printBinaryHeap(numbers, cursor, rightBound)\n\n\n\n\n\n\n\n        def calculateLhsChildIndex(cursor)\n\n\n\n            return cursor * 2 + 1\n\n\n\n        end\n\n\n\n\n\n\n\n        def calculateRhsChildIndex(cursor)\n\n\n\n            return cursor * 2 + 2\n\n\n\n        end            \n\n\n\n\n\n\n\n        while calculateLhsChildIndex(cursor) <= rightBound\n\n\n\n            lhsChildIndex = calculateLhsChildIndex(cursor)\n\n\n\n            rhsChildIndex = calculateRhsChildIndex(cursor)\n\n\n\n\n\n\n\n            lhsNumber = numbers[lhsChildIndex]\n\n\n\n            biggerChildIndex = lhsChildIndex\n\n\n\n\n\n\n\n            if rhsChildIndex <= rightBound\n\n\n\n                rhsNumber = numbers[rhsChildIndex]\n\n\n\n                if lhsNumber < rhsNumber\n\n\n\n                    biggerChildIndex = rhsChildIndex\n\n\n\n                end\n\n\n\n            end\n\n\n\n\n\n\n\n            if numbers[cursor] < numbers[biggerChildIndex]\n\n\n\n                swap(numbers, cursor, biggerChildIndex)\n\n\n\n                cursor = biggerChildIndex\n\n\n\n            else\n\n\n\n                break\n\n\n\n            end\n\n\n\n            printBinaryHeap(numbers, cursor, rightBound)\n\n\n\n        end\n\n\n\n        printBinaryHeap(numbers, cursor, rightBound)\n\n\n\n    end\n\n\n\n\n\n\n\n    def printBinaryHeap(numbers, nodeIndex = -1, rightBound = -1)\n\n\n\n        if DEMO == false\n\n\n\n            return\n\n\n\n        end\n\n\n\n        perLineWidth = (numbers.length() * 4).to_i\n\n\n\n        linesCount = Math.log2(numbers.length()).ceil()\n\n\n\n        xPrinterCount = 1\n\n\n\n        cursor = 0\n\n\n\n        spacing = 3\n\n\n\n        for y in (0..linesCount)\n\n\n\n            line = perLineWidth.times.map { \" \" }\n\n\n\n            spacing = spacing == 3 ? 4 : 3\n\n\n\n            printIndex = (perLineWidth \/ 2) - (spacing * xPrinterCount) \/ 2\n\n\n\n            for x in (0..xPrinterCount - 1)\n\n\n\n                if cursor >= numbers.length\n\n\n\n                    break\n\n\n\n                end\n\n\n\n                if nodeIndex != -1 && cursor == nodeIndex\n\n\n\n                    line[printIndex] = \"%s%s%s\" % [Colors::RED, numbers[cursor].to_s, Colors::STOP]\n\n\n\n                elsif rightBound != -1 && cursor > rightBound\n\n\n\n                    line[printIndex] = \"%s%s%s\" % [Colors::BLUE, numbers[cursor].to_s, Colors::STOP]\n\n\n\n                else\n\n\n\n                    line[printIndex] = numbers[cursor].to_s\n\n\n\n                end\n\n\n\n                cursor += 1\n\n\n\n                printIndex += spacing\n\n\n\n            end\n\n\n\n            print line.join()\n\n\n\n            xPrinterCount *= 2           \n\n\n\n            print \"\\n\"            \n\n\n\n        end\n\n\n\n    end\n\n\n\n\n\n\n\n    heapify(numbers)\n\n\n\n    rightBound = numbers.length() - 1\n\n\n\n\n\n\n\n    while rightBound > 0\n\n\n\n        swap(numbers, 0, rightBound)   \n\n\n\n        rightBound -= 1\n\n\n\n        siftDown(numbers, 0, rightBound)     \n\n\n\n    end\n\n\n\n\n\n\n\n    return numbers\n\n\n\nend\n\n\n\n\n\n\n\nnumbersCount = 14\n\n\n\nmaximalNumber = 10\n\n\n\nnumbers = numbersCount.times.map { Random.rand(maximalNumber) }\n\n\n\nprint numbers\n\n\n\nprint \"\\n---\\n\"\n\n\n\n\n\n\n\nstart = Time.now\n\n\n\nsortedNumbers = heapsort(numbers)\n\n\n\nfinish = Time.now\n\n\n\nheapSortTime = start - finish\n\n\n\n\n\n\n\nstart = Time.now\n\n\n\nreferenceSortedNumbers = numbers.sort()\n\n\n\nfinish = Time.now\n\n\n\nreferenceSortTime = start - finish\n\n\n\n\n\n\n\nprint \"Reference sort: \"\n\n\n\nprint referenceSortedNumbers\n\n\n\nprint \"\\n\"\n\n\n\nprint \"Reference sort time: %f\\n\" % referenceSortTime\n\n\n\nprint \"Heap sort:      \"\n\n\n\nprint sortedNumbers\n\n\n\nprint \"\\n\"\n\n\n\nif DEMO == false\n\n\n\n    print \"Heap sort time:      %f\\n\" % heapSortTime\n\n\n\nelse\n\n\n\n    print \"Disable DEMO for performance measure\\n\"\n\n\n\nend\n\n\n\n\n\n\n\nif sortedNumbers != referenceSortedNumbers\n\n\n\n    puts \"Validation failed\"\n\n\n\n    exit 1\n\n\n\nelse\n\n\n\n    puts \"Validation success\"\n\n\n\n    exit 0\n\n\n\nend\n\n\n\n<\/code><\/pre>\n<\/div>\n<\/div>\n<\/div>\n<p>Esse algoritmo n\u00e3o \u00e9 f\u00e1cil de entender sem visualiza\u00e7\u00e3o, ent\u00e3o a primeira coisa que recomendo \u00e9 escrever uma fun\u00e7\u00e3o que imprima a visualiza\u00e7\u00e3o atual da \u00e1rvore bin\u00e1ria.<\/p>\n<h3>Links<\/h3>\n<p><a href=\"https:\/\/gitlab.com\/demensdeum\/algorithms\/-\/blob\/master\/sortAlgorithms\/heapsort\/heapsort.rb\" target=\"_blank\" rel=\"noopener\">https:\/\/gitlab.com\/demensdeum\/algorithms\/-\/blob\/master\/sortAlgorithms\/heapsort\/heapsort.rb<\/a><\/p>\n<h3>Fontes<\/h3>\n<p><a href=\"http:\/\/rosettacode.org\/wiki\/Sorting_algorithms\/Heapsort\" target=\"_blank\" rel=\"noopener\">http:\/\/rosettacode.org\/wiki\/Sorting_algorithms\/Heapsort<\/a> <br \/>\n<a href=\"https:\/\/www.youtube.com\/watch?v=LbB357_RwlY\" target=\"_blank\" rel=\"noopener\">https:\/\/www.youtube.com\/watch?v=LbB357_RwlY<\/a><\/p>\n<p><a href=\"https:\/\/habr.com\/ru\/company\/otus\/blog\/460087\/\" target=\"_blank\" rel=\"noopener\">https:\/\/habr.com\/ru\/company\/ otus\/blog\/460087\/<\/a><\/p>\n<p><a href=\"https:\/\/ru.wikipedia.org\/wiki\/Pyramid_sort\" target=\"_blank\" rel=\"noopener\">https:\/\/ru.wikipedia.org\/wiki\/Pyramid_sort<\/a> <\/p>\n<p><a href=\"https:\/\/neerc.ifmo.ru\/wiki\/index.php?title=Heap_sorting\" target=\"_blank\" rel=\"noopener\">https:\/\/neerc.ifmo.ru\/wiki \/index.php?title=Heap_sort<\/a><\/p>\n<p><a href=\"https:\/\/wiki5.ru\/wiki\/Heapsort\" target=\"_blank\" rel=\"noopener\">https:\/\/wiki5.ru\/wiki\/Heapsort<\/a><\/p>\n<p><a href=\"https:\/\/wiki.c2.com\/?HeapSort\" target=\"_blank\" rel=\"noopener\">https:\/\/wiki.c2.com\/?HeapSort<\/a><\/ p><\/p>\n<p><a href=\"https:\/\/ru.wikipedia.org\/wiki\/%D0%94%D0%B5%D1%80%D0%B5%D0%B2%D0%BE_(%D1%81%D1 %82%D1%80%D1%83%D0%BA%D1%82%D1%83%D1%80%D0%B0_%D0%B4%D0%B0%D0%BD%D0%BD%D1%8B %D1%85)\" target=\"_blank\" rel=\"noopener\">https:\/\/ru.wikipedia.org\/wiki\/Tree (estrutura de dados)<\/a><\/p>\n<p><a href=\"https:\/\/ru.wikipedia.org\/wiki\/%D0%9A%D1%83%D1%87%D0%B0_(%D1%81%D1%82%D1 %80%D1%83%D0%BA%D1%82%D1%83%D1%80%D0%B0_%D0%B4%D0%B0%D0%BD%D0%BD%D1%8B%D1%85 )\" target=\"_blank\" rel=\"noopener\">https:\/\/ru.wikipedia.org\/wiki\/Heap (estrutura de dados)<\/a><\/p>\n<p><a href=\"https:\/\/www.youtube.com\/watch?v=2DmK_H7IdTo\" target=\"_blank\" rel=\"noopener\">https:\/\/www.youtube.com\/watch?v=2DmK_H7IdTo <\/a><\/p>\n<p><a href=\"https:\/\/www.youtube.com\/watch?v=kU4KBD4NFtw\" target=\"_blank\" rel=\"noopener\">https:\/\/www.youtube.com\/watch?v=kU4KBD4NFtw <\/a><\/p>\n<p><a href=\"https:\/\/www.youtube.com\/watch?v=DU1uG5310x0\" target=\"_blank\" rel=\"noopener\">https:\/\/www.youtube.com\/watch?v=DU1uG5310x0 <\/a><\/p>\n<p><a href=\"https:\/\/www.youtube.com\/watch?v=BzQGPA_v-vc\" target=\"_blank\" rel=\"noopener\">https:\/\/www.youtube.com\/watch?v =BzQGPA_v-vc<\/a><\/p>\n<p><a href=\"https:\/\/www.geeksforgeeks.org\/array-representation-of-binary-heap\/\" target=\"_blank\" rel=\"noopener\">https:\/\/www.geeksforgeeks.org\/ representa\u00e7\u00e3o de array de heap bin\u00e1rio\/<\/a><\/p>\n<p><a href=\"https:\/\/habr.com\/ru\/post\/112222\/\" target=\"_blank\" rel=\"noopener\">https:\/\/habr.com\/ru\/post\/112222\/<\/ a><\/p>\n<p><a href=\"https:\/\/www.cs.usfca.edu\/~galles\/visualization\/BST.html\" target=\"_blank\" rel=\"noopener\">https:\/\/www.cs.usfca. edu\/~galles\/visualization\/BST.html<\/a><\/p>\n<p><a href=\"https:\/\/www.youtube.com\/watch?v=EQzqHWtsKq4\" target=\"_blank\" rel=\"noopener\">https:\/\/www.youtube.com\/watch?v=EQzqHWtsKq4 <\/a><\/p>\n<p><a href=\"https:\/\/medium.com\/@dimko1\/%D0%B0%D0%BB%D0%B3%D0%BE%D1%80%D0%B8%D1%82%D0%BC%D1% 8B-%D1%81%D0%BE%D1%80%D1%82%D0%B8%D1%80%D0%BE%D0%B2%D0%BA%D0%B8-heapsort-796ba965018b\" alvo=\"_em branco\" rel=\"noopener\">https:\/\/medium.com\/@dimko1\/%D0%B0%D0%BB%D0%B3%D0%BE%D1%80%D0%B8%D1%82%D0%BC% D1 %8B-%D1%81%D0%BE%D1%80%D1%82%D0%B8%D1%80%D0%BE%D0%B2%D0%BA%D0%B8-heapsort-796ba965018b<\/a <\/p>\n<p><a href=\"https:\/\/ru.wikibrief.org\/wiki\/Heapsort\" target=\"_blank\" rel=\"noopener\">https:\/\/ru.wikibrief.org\/wiki\/Heapsort<\/a> <\/p>\n<p><a href=\"https:\/\/www.youtube.com\/watch?v=GUUpmrTnNbw\" target=\"_blank\" rel=\"noopener\">https:\/\/www.youtube.com\/watch?v=GUUpmrTnNbw <\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Heapsort \u2013 classifica\u00e7\u00e3o em pir\u00e2mide. Complexidade de tempo do algoritmo &#8211; O (n log n), r\u00e1pido, certo? Eu chamaria isso de classifica\u00e7\u00e3o de classifica\u00e7\u00e3o de pedras que caem. Parece-me que a maneira mais f\u00e1cil de explicar \u00e9 visualmente. A entrada \u00e9 uma lista de n\u00fameros, por exemplo: 5, 0, 7, 2, 3, 9, 4 Da<a class=\"more-link\" href=\"https:\/\/demensdeum.com\/blog\/pt\/2022\/08\/08\/heapsort\/\">Continue reading <span class=\"screen-reader-text\">&#8220;Heapsort&#8221;<\/span><\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[61,52],"tags":[131,204,190],"class_list":["post-3373","post","type-post","status-publish","format-standard","hentry","category-techie","category-tutorials","tag-algorithms","tag-heapsort","tag-sorting","entry"],"translation":{"provider":"WPGlobus","version":"3.0.2","language":"pt","enabled_languages":["en","ru","zh","de","fr","ja","pt","hi"],"languages":{"en":{"title":true,"content":true,"excerpt":false},"ru":{"title":true,"content":true,"excerpt":false},"zh":{"title":true,"content":true,"excerpt":false},"de":{"title":true,"content":true,"excerpt":false},"fr":{"title":true,"content":true,"excerpt":false},"ja":{"title":true,"content":true,"excerpt":false},"pt":{"title":true,"content":true,"excerpt":false},"hi":{"title":false,"content":false,"excerpt":false}}},"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/demensdeum.com\/blog\/pt\/wp-json\/wp\/v2\/posts\/3373","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/demensdeum.com\/blog\/pt\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/demensdeum.com\/blog\/pt\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/demensdeum.com\/blog\/pt\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/demensdeum.com\/blog\/pt\/wp-json\/wp\/v2\/comments?post=3373"}],"version-history":[{"count":22,"href":"https:\/\/demensdeum.com\/blog\/pt\/wp-json\/wp\/v2\/posts\/3373\/revisions"}],"predecessor-version":[{"id":3866,"href":"https:\/\/demensdeum.com\/blog\/pt\/wp-json\/wp\/v2\/posts\/3373\/revisions\/3866"}],"wp:attachment":[{"href":"https:\/\/demensdeum.com\/blog\/pt\/wp-json\/wp\/v2\/media?parent=3373"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/demensdeum.com\/blog\/pt\/wp-json\/wp\/v2\/categories?post=3373"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/demensdeum.com\/blog\/pt\/wp-json\/wp\/v2\/tags?post=3373"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}