{"id":10367,"date":"2025-08-16T09:26:20","date_gmt":"2025-08-16T09:26:20","guid":{"rendered":"https:\/\/www.kaashivinfotech.com\/blog\/?p=10367"},"modified":"2025-08-16T09:26:20","modified_gmt":"2025-08-16T09:26:20","slug":"insertion-sort-time-complexity-guide","status":"publish","type":"post","link":"https:\/\/www.kaashivinfotech.com\/blog\/insertion-sort-time-complexity-guide\/","title":{"rendered":"Insertion Sort Time Complexity: Complete Guide for Beginners &#038; Pros"},"content":{"rendered":"<p>Sorting is fundamental to computer science. Whether you are sorting numbers, names, or database records, sorting algorithms are key. One of the simplest and most commonly taught algorithms is insertion sort.<\/p>\n<p>But in interviews or exams, or in real life, one question always comes up:<\/p>\n<p>\ud83d\udc49 What is insertion sort time complexity?<\/p>\n<p>In this article, we&#8217;ll discuss the best case, worst case, average case, and space complexity \u2014 and include examples, code snippets, and comparisons. By the end of this article, you&#8217;ll know where insertion sort is good and bad.<\/p>\n<h2>What is the Insertion Sorting Algorithm?<\/h2>\n<figure id=\"attachment_10372\" aria-describedby=\"caption-attachment-10372\" style=\"width: 690px\" class=\"wp-caption aligncenter\"><img fetchpriority=\"high\" decoding=\"async\" class=\"wp-image-10372\" src=\"https:\/\/www.kaashivinfotech.com\/blog\/wp-content\/uploads\/2025\/08\/Insertion-Sorting-Algorithm.webp\" alt=\"insertion sort time complexity\" width=\"690\" height=\"462\" srcset=\"https:\/\/www.kaashivinfotech.com\/blog\/wp-content\/uploads\/2025\/08\/Insertion-Sorting-Algorithm.webp 1705w, https:\/\/www.kaashivinfotech.com\/blog\/wp-content\/uploads\/2025\/08\/Insertion-Sorting-Algorithm-300x201.webp 300w, https:\/\/www.kaashivinfotech.com\/blog\/wp-content\/uploads\/2025\/08\/Insertion-Sorting-Algorithm-1024x685.webp 1024w, https:\/\/www.kaashivinfotech.com\/blog\/wp-content\/uploads\/2025\/08\/Insertion-Sorting-Algorithm-768x514.webp 768w, https:\/\/www.kaashivinfotech.com\/blog\/wp-content\/uploads\/2025\/08\/Insertion-Sorting-Algorithm-1536x1028.webp 1536w, https:\/\/www.kaashivinfotech.com\/blog\/wp-content\/uploads\/2025\/08\/Insertion-Sorting-Algorithm-380x254.webp 380w, https:\/\/www.kaashivinfotech.com\/blog\/wp-content\/uploads\/2025\/08\/Insertion-Sorting-Algorithm-800x535.webp 800w, https:\/\/www.kaashivinfotech.com\/blog\/wp-content\/uploads\/2025\/08\/Insertion-Sorting-Algorithm-1160x776.webp 1160w\" sizes=\"(max-width: 690px) 100vw, 690px\" \/><figcaption id=\"caption-attachment-10372\" class=\"wp-caption-text\">Insertion Sorting<\/figcaption><\/figure>\n<p data-start=\"2160\" data-end=\"2346\">The <strong>insertion sorting algorithm<\/strong> is similar to sorting a hand of cards. You have sorted cards and take the next card and insert it into the sorted cards into its proper position.<\/p>\n<p>The steps are:<\/p>\n<ol>\n<li>Start with the second element in the array.<\/li>\n<li>Compare it with all the elements before it.<\/li>\n<li>Insert it into its proper position.<\/li>\n<li>Repeat this process until all elements are sorted.<\/li>\n<\/ol>\n<p>\ud83d\udc49 This is why insertion sort is one of the most straightforward sorting methods.<\/p>\n<h2>Time Complexity of Insertion Sort<\/h2>\n<figure id=\"attachment_10373\" aria-describedby=\"caption-attachment-10373\" style=\"width: 714px\" class=\"wp-caption aligncenter\"><img decoding=\"async\" class=\"wp-image-10373\" src=\"https:\/\/www.kaashivinfotech.com\/blog\/wp-content\/uploads\/2025\/08\/Time-Complexity-of-Insertion-Sort.webp\" alt=\"insertion sort time complexity\" width=\"714\" height=\"722\" srcset=\"https:\/\/www.kaashivinfotech.com\/blog\/wp-content\/uploads\/2025\/08\/Time-Complexity-of-Insertion-Sort.webp 1308w, https:\/\/www.kaashivinfotech.com\/blog\/wp-content\/uploads\/2025\/08\/Time-Complexity-of-Insertion-Sort-297x300.webp 297w, https:\/\/www.kaashivinfotech.com\/blog\/wp-content\/uploads\/2025\/08\/Time-Complexity-of-Insertion-Sort-1013x1024.webp 1013w, https:\/\/www.kaashivinfotech.com\/blog\/wp-content\/uploads\/2025\/08\/Time-Complexity-of-Insertion-Sort-768x776.webp 768w, https:\/\/www.kaashivinfotech.com\/blog\/wp-content\/uploads\/2025\/08\/Time-Complexity-of-Insertion-Sort-80x80.webp 80w, https:\/\/www.kaashivinfotech.com\/blog\/wp-content\/uploads\/2025\/08\/Time-Complexity-of-Insertion-Sort-380x384.webp 380w, https:\/\/www.kaashivinfotech.com\/blog\/wp-content\/uploads\/2025\/08\/Time-Complexity-of-Insertion-Sort-800x809.webp 800w, https:\/\/www.kaashivinfotech.com\/blog\/wp-content\/uploads\/2025\/08\/Time-Complexity-of-Insertion-Sort-1160x1172.webp 1160w, https:\/\/www.kaashivinfotech.com\/blog\/wp-content\/uploads\/2025\/08\/Time-Complexity-of-Insertion-Sort-24x24.webp 24w, https:\/\/www.kaashivinfotech.com\/blog\/wp-content\/uploads\/2025\/08\/Time-Complexity-of-Insertion-Sort-48x48.webp 48w, https:\/\/www.kaashivinfotech.com\/blog\/wp-content\/uploads\/2025\/08\/Time-Complexity-of-Insertion-Sort-96x96.webp 96w\" sizes=\"(max-width: 714px) 100vw, 714px\" \/><figcaption id=\"caption-attachment-10373\" class=\"wp-caption-text\">Time Complexity of Insertion Sort<\/figcaption><\/figure>\n<p>When considering the time complexity of insertion sort we will look at:<\/p>\n<ul>\n<li>Best Case (sorted array)<\/li>\n<li>Worst Case (reverse sorted array)<\/li>\n<li>Average Case (random order)<\/li>\n<\/ul>\n<p>Let\u2019s take a closer look.<\/p>\n<h3>\u2705 Best Case Time Complexity of Insertion Sort: O(n)<\/h3>\n<ul>\n<li data-start=\"2984\" data-end=\"3069\">If the array is <strong data-start=\"3000\" data-end=\"3018\">already sorted<\/strong>, insertion sort only compares each element once.<\/li>\n<li data-start=\"3072\" data-end=\"3118\">No shifting is required, just a linear scan.<\/li>\n<\/ul>\n<p data-start=\"3120\" data-end=\"3184\">\ud83d\udc49 Example: [1, 2, 3, 4, 5]<br data-start=\"3149\" data-end=\"3152\" \/>Comparisons = n-1 \u2192 <strong data-start=\"3174\" data-end=\"3182\">O(n)<\/strong><\/p>\n<h3 data-start=\"3186\" data-end=\"3246\">\u26a0\ufe0f Worst Case Time Complexity of Insertion Sort: O(n\u00b2)<\/h3>\n<ul>\n<li data-start=\"3249\" data-end=\"3357\">If the array is sorted in <strong data-start=\"3275\" data-end=\"3292\">reverse order<\/strong>, each new element must be compared with all previous elements.<\/li>\n<li data-start=\"3360\" data-end=\"3393\">This leads to maximum shifting.<\/li>\n<\/ul>\n<p data-start=\"3395\" data-end=\"3468\">\ud83d\udc49 Example: [5, 4, 3, 2, 1]<br data-start=\"3424\" data-end=\"3427\" \/>Comparisons \u2248 (n*(n-1))\/2 \u2192 <strong data-start=\"3457\" data-end=\"3466\">O(n\u00b2)<\/strong><\/p>\n<h3 data-start=\"3470\" data-end=\"3532\">\u2696\ufe0f Average Case Time Complexity of Insertion Sort: O(n\u00b2)<\/h3>\n<ul>\n<li data-start=\"3535\" data-end=\"3640\">For a <strong data-start=\"3541\" data-end=\"3557\">random array<\/strong>, on average, each element will be compared with half of the already sorted part.<\/li>\n<li data-start=\"3643\" data-end=\"3686\">So total comparisons \u2248 n\u00b2\/4 \u2192 <strong data-start=\"3675\" data-end=\"3684\">O(n\u00b2)<\/strong><\/li>\n<\/ul>\n<h3 data-start=\"3688\" data-end=\"3742\">\ud83d\udccc <strong data-start=\"3691\" data-end=\"3740\">Summary Table: Insertion Sort Time Complexity<\/strong><\/h3>\n<table style=\"height: 269px;\" width=\"323\" data-start=\"3744\" data-end=\"3909\">\n<thead data-start=\"3744\" data-end=\"3777\">\n<tr data-start=\"3744\" data-end=\"3777\">\n<td>\n<p style=\"text-align: center;\"><strong>Case<\/strong><\/p>\n<\/td>\n<td style=\"text-align: center;\"><strong>Time Complexity<\/strong><\/td>\n<\/tr>\n<\/thead>\n<tbody>\n<tr data-start=\"3811\" data-end=\"3843\">\n<td data-start=\"3811\" data-end=\"3825\" data-col-size=\"sm\">\n<p style=\"text-align: center;\">Best Case<\/p>\n<\/td>\n<td data-start=\"3825\" data-end=\"3843\" data-col-size=\"sm\">\n<p style=\"text-align: center;\">O(n)<\/p>\n<\/td>\n<\/tr>\n<tr data-start=\"3844\" data-end=\"3876\">\n<td data-start=\"3844\" data-end=\"3858\" data-col-size=\"sm\">\n<p style=\"text-align: center;\">Worst Case<\/p>\n<\/td>\n<td data-start=\"3858\" data-end=\"3876\" data-col-size=\"sm\">\n<p style=\"text-align: center;\">O(n\u00b2)<\/p>\n<\/td>\n<\/tr>\n<tr data-start=\"3877\" data-end=\"3909\">\n<td style=\"text-align: center;\" data-start=\"3877\" data-end=\"3891\" data-col-size=\"sm\">Average Case<\/td>\n<td data-col-size=\"sm\" data-start=\"3891\" data-end=\"3909\">\n<p style=\"text-align: center;\">O(n\u00b2)<\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<h2>Space Complexity of Insertion Sort<\/h2>\n<p data-start=\"3960\" data-end=\"4026\">One big advantage of insertion sort is its <strong data-start=\"4003\" data-end=\"4023\">space efficiency<\/strong>.<\/p>\n<ul>\n<li data-start=\"4030\" data-end=\"4058\"><strong data-start=\"4030\" data-end=\"4051\">Space Complexity:<\/strong> O(1)<\/li>\n<li data-start=\"4061\" data-end=\"4127\">Only a constant amount of extra memory is required for swapping.<\/li>\n<li data-start=\"4130\" data-end=\"4180\">This makes it an <strong data-start=\"4147\" data-end=\"4177\">in-place sorting algorithm<\/strong>.<\/li>\n<\/ul>\n<h2>Insertion Sort Algorithm (Code Examples)<\/h2>\n<h3 data-start=\"4237\" data-end=\"4264\">Python Implementation<\/h3>\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"python\">def insertion_sort(arr):\r\n    for i in range(1, len(arr)):\r\n        key = arr[i]\r\n        j = i - 1\r\n        while j &gt;= 0 and key &lt; arr[j]:\r\n            arr[j+1] = arr[j]\r\n            j -= 1\r\n        arr[j+1] = key\r\n    return arr\r\n\r\nprint(insertion_sort([5, 2, 9, 1, 5, 6]))<\/pre>\n<h3 data-start=\"4547\" data-end=\"4572\">Java Implementation<\/h3>\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"java\">public class InsertionSort {\r\n    public static void insertionSort(int arr[]) {\r\n        for (int i = 1; i &lt; arr.length; i++) {\r\n            int key = arr[i];\r\n            int j = i - 1;\r\n            while (j &gt;= 0 &amp;&amp; arr[j] &gt; key) {\r\n                arr[j+1] = arr[j];\r\n                j = j - 1;\r\n            }\r\n            arr[j+1] = key;\r\n        }\r\n    }\r\n    \r\n    public static void main(String args[]) {\r\n        int arr[] = {5, 2, 9, 1, 5, 6};\r\n        insertionSort(arr);\r\n        for (int i : arr) {\r\n            System.out.print(i + \" \");\r\n        }\r\n    }\r\n}<\/pre>\n<h2>Real-Life Analogy of Insertion Sorting Algorithm<\/h2>\n<p>Think of inserting cards into your hand:<\/p>\n<ul>\n<li>You take a card one at a time.<\/li>\n<li>You place it in the right order.<\/li>\n<li>You keep doing that until there are no more cards to place in your hand.<\/li>\n<\/ul>\n<p>That is how insertion sort works\u2014easy for a human to comprehend but not fast.<\/p>\n<h2>Insertion Sort vs Other Sorting Algorithms<\/h2>\n<p data-start=\"5529\" data-end=\"5554\">\ud83d\udcca <strong data-start=\"5532\" data-end=\"5552\">Comparison Table<\/strong><\/p>\n<table style=\"height: 413px;\" width=\"708\" data-start=\"5556\" data-end=\"6108\">\n<thead data-start=\"5556\" data-end=\"5634\">\n<tr data-start=\"5556\" data-end=\"5634\">\n<td><strong>Algorithm<\/strong><\/td>\n<td><strong>Best Case<\/strong><\/td>\n<td><strong>Average Case<\/strong><\/td>\n<td><strong>Worst Case<\/strong><\/td>\n<td><strong>Space Complexity<\/strong><\/td>\n<\/tr>\n<\/thead>\n<tbody>\n<tr data-start=\"5714\" data-end=\"5792\">\n<td data-start=\"5714\" data-end=\"5732\" data-col-size=\"sm\">Insertion Sort<\/td>\n<td data-col-size=\"sm\" data-start=\"5732\" data-end=\"5744\">O(n)<\/td>\n<td data-col-size=\"sm\" data-start=\"5744\" data-end=\"5759\">O(n\u00b2)<\/td>\n<td data-col-size=\"sm\" data-start=\"5759\" data-end=\"5772\">O(n\u00b2)<\/td>\n<td data-col-size=\"sm\" data-start=\"5772\" data-end=\"5792\">O(1)<\/td>\n<\/tr>\n<tr data-start=\"5793\" data-end=\"5871\">\n<td data-start=\"5793\" data-end=\"5811\" data-col-size=\"sm\">Bubble Sort<\/td>\n<td data-col-size=\"sm\" data-start=\"5811\" data-end=\"5823\">O(n)<\/td>\n<td data-col-size=\"sm\" data-start=\"5823\" data-end=\"5838\">O(n\u00b2)<\/td>\n<td data-col-size=\"sm\" data-start=\"5838\" data-end=\"5851\">O(n\u00b2)<\/td>\n<td data-col-size=\"sm\" data-start=\"5851\" data-end=\"5871\">O(1)<\/td>\n<\/tr>\n<tr data-start=\"5872\" data-end=\"5950\">\n<td data-start=\"5872\" data-end=\"5890\" data-col-size=\"sm\">Selection Sort<\/td>\n<td data-col-size=\"sm\" data-start=\"5890\" data-end=\"5902\">O(n\u00b2)<\/td>\n<td data-col-size=\"sm\" data-start=\"5902\" data-end=\"5917\">O(n\u00b2)<\/td>\n<td data-col-size=\"sm\" data-start=\"5917\" data-end=\"5930\">O(n\u00b2)<\/td>\n<td data-col-size=\"sm\" data-start=\"5930\" data-end=\"5950\">O(1)<\/td>\n<\/tr>\n<tr data-start=\"5951\" data-end=\"6029\">\n<td data-start=\"5951\" data-end=\"5969\" data-col-size=\"sm\">Merge Sort<\/td>\n<td data-col-size=\"sm\" data-start=\"5969\" data-end=\"5981\">O(n log n)<\/td>\n<td data-col-size=\"sm\" data-start=\"5981\" data-end=\"5996\">O(n log n)<\/td>\n<td data-col-size=\"sm\" data-start=\"5996\" data-end=\"6009\">O(n log n)<\/td>\n<td data-col-size=\"sm\" data-start=\"6009\" data-end=\"6029\">O(n)<\/td>\n<\/tr>\n<tr data-start=\"6030\" data-end=\"6108\">\n<td data-start=\"6030\" data-end=\"6048\" data-col-size=\"sm\">Quick Sort<\/td>\n<td data-start=\"6048\" data-end=\"6060\" data-col-size=\"sm\">O(n log n)<\/td>\n<td data-col-size=\"sm\" data-start=\"6060\" data-end=\"6075\">O(n log n)<\/td>\n<td data-col-size=\"sm\" data-start=\"6075\" data-end=\"6088\">O(n\u00b2)<\/td>\n<td data-col-size=\"sm\" data-start=\"6088\" data-end=\"6108\">O(log n)<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p data-start=\"6110\" data-end=\"6128\"><strong>\ud83d\udc49 Key Takeaway:<\/strong><\/p>\n<ul>\n<li>Insertion sort is useful for small datasets and arrays that are almost sorted.<\/li>\n<li>For large datasets algorithms like Merge Sort or Quick Sort should be used.<\/li>\n<\/ul>\n<h2>Applications of Insertion Sorting Algorithm<\/h2>\n<figure id=\"attachment_10374\" aria-describedby=\"caption-attachment-10374\" style=\"width: 600px\" class=\"wp-caption aligncenter\"><img decoding=\"async\" class=\"wp-image-10374\" src=\"https:\/\/www.kaashivinfotech.com\/blog\/wp-content\/uploads\/2025\/08\/Applications-of-Insertion-Sorting-Algorithm.webp\" alt=\"insertion sort time complexity\" width=\"600\" height=\"354\" srcset=\"https:\/\/www.kaashivinfotech.com\/blog\/wp-content\/uploads\/2025\/08\/Applications-of-Insertion-Sorting-Algorithm.webp 1332w, https:\/\/www.kaashivinfotech.com\/blog\/wp-content\/uploads\/2025\/08\/Applications-of-Insertion-Sorting-Algorithm-300x177.webp 300w, https:\/\/www.kaashivinfotech.com\/blog\/wp-content\/uploads\/2025\/08\/Applications-of-Insertion-Sorting-Algorithm-1024x604.webp 1024w, https:\/\/www.kaashivinfotech.com\/blog\/wp-content\/uploads\/2025\/08\/Applications-of-Insertion-Sorting-Algorithm-768x453.webp 768w, https:\/\/www.kaashivinfotech.com\/blog\/wp-content\/uploads\/2025\/08\/Applications-of-Insertion-Sorting-Algorithm-380x224.webp 380w, https:\/\/www.kaashivinfotech.com\/blog\/wp-content\/uploads\/2025\/08\/Applications-of-Insertion-Sorting-Algorithm-800x472.webp 800w, https:\/\/www.kaashivinfotech.com\/blog\/wp-content\/uploads\/2025\/08\/Applications-of-Insertion-Sorting-Algorithm-1160x685.webp 1160w\" sizes=\"(max-width: 600px) 100vw, 600px\" \/><figcaption id=\"caption-attachment-10374\" class=\"wp-caption-text\">Applications of Insertion Sorting Algorithm<\/figcaption><\/figure>\n<ul>\n<li>Sorting small playing cards or small arrays in embedded systems.<\/li>\n<li>Used in hybrid sorting algorithms (e.g., Timsort in Python, which uses insertion sort for small partitions).<\/li>\n<li>Excellent for cases when, the data is already partially sorted.<\/li>\n<\/ul>\n<h2>Final Thoughts<\/h2>\n<p data-start=\"6650\" data-end=\"6784\">The <strong>insertion sorting algorithm<\/strong> is incredibly simple but powerful for its intended purpose. Insertion sort&#8217;s time complexity varies as follows:<\/p>\n<ul>\n<li>O(n) for the best case,<\/li>\n<li>O(n\u00b2) for average and worst case.<\/li>\n<\/ul>\n<p>It is not the best algorithm for processing large data sets, but for small arrays, that are almost sorted, it is hard to beat.<\/p>\n<p>\ud83d\udc49 Understanding insertion sort&#8217;s <strong>time complexity<\/strong> is not just about memorizing big-O values, it is also about knowing where and when it is acceptable to use insertion sort.<\/p>\n<p>if you are studying for coding interviews or an exam on algorithms, you should know that insertion sort is one of the best algorithm to start with.<\/p>\n<h2>Related Links<\/h2>\n<ul>\n<li><a href=\"https:\/\/www.kaashivinfotech.com\/blog\/data-structure-and-algorithm-guide\/\">Data Structures and Algorithms: From Basics to Advanced<\/a><\/li>\n<li><a href=\"https:\/\/www.kaashivinfotech.com\/blog\/10-best-data-structures-and-algorithms-books\/\">10 Best Data Structures and Algorithms Books<\/a><\/li>\n<li><a href=\"https:\/\/www.wikitechy.com\/trees-in-data-structures-ultimate-cheat-sheet\/\" target=\"_blank\" rel=\"noopener\">Trees in Data Structures Explained : 5 Must-Know Types<\/a><\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"<p>Sorting is fundamental to computer science. Whether you are sorting numbers, names, or database records, sorting algorithms are key. One of the simplest and most commonly taught algorithms is insertion sort. But in interviews or exams, or in real life, one question always comes up: \ud83d\udc49 What is insertion sort time complexity? In this article, [&hellip;]<\/p>\n","protected":false},"author":9,"featured_media":10376,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[3203],"tags":[8365,8363,8359,8362,8364,8361,8366,8367,8360],"class_list":["post-10367","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-programming","tag-insertion-sort-average-case","tag-insertion-sort-best-case","tag-insertion-sort-time-complexity","tag-insertion-sort-vs-bubble-sort","tag-insertion-sort-worst-case","tag-insertion-sorting-algorithm","tag-sorting-algorithms","tag-space-complexity-insertion-sort","tag-time-complexity-of-insertion-sort"],"_links":{"self":[{"href":"https:\/\/www.kaashivinfotech.com\/blog\/wp-json\/wp\/v2\/posts\/10367","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.kaashivinfotech.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.kaashivinfotech.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.kaashivinfotech.com\/blog\/wp-json\/wp\/v2\/users\/9"}],"replies":[{"embeddable":true,"href":"https:\/\/www.kaashivinfotech.com\/blog\/wp-json\/wp\/v2\/comments?post=10367"}],"version-history":[{"count":0,"href":"https:\/\/www.kaashivinfotech.com\/blog\/wp-json\/wp\/v2\/posts\/10367\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.kaashivinfotech.com\/blog\/wp-json\/wp\/v2\/media\/10376"}],"wp:attachment":[{"href":"https:\/\/www.kaashivinfotech.com\/blog\/wp-json\/wp\/v2\/media?parent=10367"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.kaashivinfotech.com\/blog\/wp-json\/wp\/v2\/categories?post=10367"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.kaashivinfotech.com\/blog\/wp-json\/wp\/v2\/tags?post=10367"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}