{"id":1146315,"date":"2025-01-08T23:15:52","date_gmt":"2025-01-08T15:15:52","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1146315.html"},"modified":"2025-01-08T23:15:55","modified_gmt":"2025-01-08T15:15:55","slug":"python%e5%a6%82%e4%bd%95%e5%b0%86%e4%ba%8c%e7%bb%b4%e6%95%b0%e7%bb%84%e8%bd%ac%e5%8c%96%e4%b8%ba%e4%b8%89%e7%bb%b4%e6%95%b0%e7%bb%84","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/1146315.html","title":{"rendered":"python\u5982\u4f55\u5c06\u4e8c\u7ef4\u6570\u7ec4\u8f6c\u5316\u4e3a\u4e09\u7ef4\u6570\u7ec4"},"content":{"rendered":"<p style=\"text-align:center;\" ><img decoding=\"async\" src=\"https:\/\/cdn-kb.worktile.com\/kb\/wp-content\/uploads\/2024\/04\/24182441\/2e08ae95-d665-4b64-9f48-d67d6ef61d45.webp\" alt=\"python\u5982\u4f55\u5c06\u4e8c\u7ef4\u6570\u7ec4\u8f6c\u5316\u4e3a\u4e09\u7ef4\u6570\u7ec4\" \/><\/p>\n<p><p> <strong>Python\u5c06\u4e8c\u7ef4\u6570\u7ec4\u8f6c\u5316\u4e3a\u4e09\u7ef4\u6570\u7ec4\u7684\u65b9\u6cd5\u6709\u591a\u79cd\uff0c\u6700\u5e38\u7528\u7684\u6709\uff1a\u4f7f\u7528NumPy\u5e93\u3001\u624b\u52a8\u5b9e\u73b0\u5d4c\u5957\u5faa\u73af\u3001\u4ee5\u53ca\u4f7f\u7528\u5217\u8868\u89e3\u6790\u7b49\u65b9\u6cd5\u3002\u4e0b\u9762\u5c06\u8be6\u7ec6\u4ecb\u7ecd\u4f7f\u7528NumPy\u5e93\u7684\u65b9\u6cd5\u3002NumPy\u5e93\u662fPython\u5904\u7406\u591a\u7ef4\u6570\u7ec4\u7684\u5f3a\u5927\u5de5\u5177\uff0c\u53ef\u4ee5\u8f7b\u677e\u5b9e\u73b0\u4ece\u4e8c\u7ef4\u6570\u7ec4\u8f6c\u6362\u4e3a\u4e09\u7ef4\u6570\u7ec4\u3002<\/strong><\/p>\n<\/p>\n<p><h3>\u4e00\u3001\u4f7f\u7528NumPy\u5e93\u8fdb\u884c\u8f6c\u6362<\/h3>\n<\/p>\n<p><p>NumPy\u662fPython\u4e2d\u5904\u7406\u6570\u7ec4\u548c\u77e9\u9635\u7684\u57fa\u7840\u5e93\uff0c\u63d0\u4f9b\u4e86\u8bb8\u591a\u4fbf\u6377\u7684\u529f\u80fd\u6765\u5904\u7406\u591a\u7ef4\u6570\u7ec4\u3002\u5c06\u4e8c\u7ef4\u6570\u7ec4\u8f6c\u6362\u4e3a\u4e09\u7ef4\u6570\u7ec4\u53ef\u4ee5\u901a\u8fc7<code>reshape<\/code>\u51fd\u6570\u6765\u5b9e\u73b0\u3002<\/p>\n<\/p>\n<p><h4>1. NumPy\u5e93\u7b80\u4ecb<\/h4>\n<\/p>\n<p><p>NumPy\uff08Numerical Python\uff09\u662f\u4e00\u4e2a\u5f00\u6e90\u7684Python\u5e93\uff0c\u7528\u4e8e\u79d1\u5b66\u8ba1\u7b97\u3002NumPy\u7684\u4e3b\u8981\u5bf9\u8c61\u662f\u540c\u7c7b\u5143\u7d20\u7684\u591a\u7ef4\u6570\u7ec4\u3002\u5b83\u63d0\u4f9b\u4e86\u8bb8\u591a\u652f\u6301\u9ad8\u7ea7\u6570\u5b66\u8fd0\u7b97\u548c\u77e9\u9635\u64cd\u4f5c\u7684\u51fd\u6570\u3002<\/p>\n<\/p>\n<p><p>\u5b89\u88c5NumPy\u5e93\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u547d\u4ee4\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-bash\">pip install numpy<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h4>2. \u4f7f\u7528reshape\u51fd\u6570<\/h4>\n<\/p>\n<p><p><code>reshape<\/code>\u51fd\u6570\u662fNumPy\u4e2d\u6700\u5e38\u7528\u7684\u6570\u7ec4\u53d8\u6362\u51fd\u6570\u4e4b\u4e00\u3002\u5b83\u53ef\u4ee5\u5c06\u6570\u7ec4\u7684\u5f62\u72b6\u6539\u53d8\u4e3a\u6307\u5b9a\u7684\u5f62\u72b6\u3002\u4e0b\u9762\u662f\u4e00\u4e2a\u5c06\u4e8c\u7ef4\u6570\u7ec4\u8f6c\u6362\u4e3a\u4e09\u7ef4\u6570\u7ec4\u7684\u4f8b\u5b50\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import numpy as np<\/p>\n<h2><strong>\u521b\u5efa\u4e00\u4e2a\u4e8c\u7ef4\u6570\u7ec4<\/strong><\/h2>\n<p>two_d_array = np.array([[1, 2, 3], [4, 5, 6]])<\/p>\n<h2><strong>\u5c06\u4e8c\u7ef4\u6570\u7ec4\u8f6c\u6362\u4e3a\u4e09\u7ef4\u6570\u7ec4<\/strong><\/h2>\n<p>three_d_array = two_d_array.reshape(2, 1, 3)<\/p>\n<p>print(three_d_array)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u4e0a\u9762\u7684\u4ee3\u7801\u5c06\u4e00\u4e2a2&#215;3\u7684\u4e8c\u7ef4\u6570\u7ec4\u8f6c\u6362\u4e3a\u4e86\u4e00\u4e2a2x1x3\u7684\u4e09\u7ef4\u6570\u7ec4\u3002<\/p>\n<\/p>\n<p><h3>\u4e8c\u3001\u624b\u52a8\u5b9e\u73b0\u5d4c\u5957\u5faa\u73af\u8f6c\u6362<\/h3>\n<\/p>\n<p><p>\u9664\u4e86\u4f7f\u7528NumPy\u5e93\u4e4b\u5916\uff0cPython\u4e5f\u53ef\u4ee5\u901a\u8fc7\u624b\u52a8\u5b9e\u73b0\u5d4c\u5957\u5faa\u73af\u7684\u65b9\u6cd5\u6765\u5c06\u4e8c\u7ef4\u6570\u7ec4\u8f6c\u6362\u4e3a\u4e09\u7ef4\u6570\u7ec4\u3002\u8fd9\u79cd\u65b9\u6cd5\u9002\u5408\u7406\u89e3\u6570\u7ec4\u7684\u57fa\u672c\u64cd\u4f5c\u548c\u7ed3\u6784\u3002<\/p>\n<\/p>\n<p><h4>1. \u5d4c\u5957\u5faa\u73af\u65b9\u6cd5\u7b80\u4ecb<\/h4>\n<\/p>\n<p><p>\u5d4c\u5957\u5faa\u73af\u662f\u6307\u5728\u4e00\u4e2a\u5faa\u73af\u4e2d\u5305\u542b\u53e6\u4e00\u4e2a\u5faa\u73af\u3002\u8fd9\u79cd\u65b9\u6cd5\u53ef\u4ee5\u904d\u5386\u548c\u5904\u7406\u591a\u7ef4\u6570\u7ec4\u7684\u6bcf\u4e00\u4e2a\u5143\u7d20\u3002<\/p>\n<\/p>\n<p><h4>2. \u5b9e\u73b0\u793a\u4f8b<\/h4>\n<\/p>\n<p><p>\u4e0b\u9762\u662f\u4e00\u4e2a\u624b\u52a8\u5b9e\u73b0\u4e8c\u7ef4\u6570\u7ec4\u8f6c\u6362\u4e3a\u4e09\u7ef4\u6570\u7ec4\u7684\u793a\u4f8b\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u521b\u5efa\u4e00\u4e2a\u4e8c\u7ef4\u6570\u7ec4<\/p>\n<p>two_d_array = [[1, 2, 3], [4, 5, 6]]<\/p>\n<h2><strong>\u5b9a\u4e49\u76ee\u6807\u4e09\u7ef4\u6570\u7ec4\u7684\u5c3a\u5bf8<\/strong><\/h2>\n<p>depth = 2<\/p>\n<p>rows = 1<\/p>\n<p>columns = 3<\/p>\n<h2><strong>\u521b\u5efa\u4e00\u4e2a\u7a7a\u7684\u4e09\u7ef4\u6570\u7ec4<\/strong><\/h2>\n<p>three_d_array = [[[0 for _ in range(columns)] for _ in range(rows)] for _ in range(depth)]<\/p>\n<h2><strong>\u586b\u5145\u4e09\u7ef4\u6570\u7ec4<\/strong><\/h2>\n<p>for i in range(depth):<\/p>\n<p>    for j in range(rows):<\/p>\n<p>        for k in range(columns):<\/p>\n<p>            three_d_array[i][j][k] = two_d_array[i][k]<\/p>\n<p>print(three_d_array)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u8fd9\u4e2a\u4f8b\u5b50\u901a\u8fc7\u5d4c\u5957\u5faa\u73af\u904d\u5386\u4e8c\u7ef4\u6570\u7ec4\u7684\u6bcf\u4e00\u4e2a\u5143\u7d20\uff0c\u5e76\u5c06\u5176\u586b\u5145\u5230\u65b0\u7684\u4e09\u7ef4\u6570\u7ec4\u4e2d\u3002<\/p>\n<\/p>\n<p><h3>\u4e09\u3001\u4f7f\u7528\u5217\u8868\u89e3\u6790\u8fdb\u884c\u8f6c\u6362<\/h3>\n<\/p>\n<p><p>\u5217\u8868\u89e3\u6790\u662fPython\u4e2d\u7684\u4e00\u4e2a\u5f3a\u5927\u5de5\u5177\uff0c\u53ef\u4ee5\u7528\u6765\u521b\u5efa\u548c\u8f6c\u6362\u5217\u8868\u3002\u4f7f\u7528\u5217\u8868\u89e3\u6790\u53ef\u4ee5\u7b80\u5316\u4ee3\u7801\u5e76\u63d0\u9ad8\u53ef\u8bfb\u6027\u3002<\/p>\n<\/p>\n<p><h4>1. \u5217\u8868\u89e3\u6790\u7b80\u4ecb<\/h4>\n<\/p>\n<p><p>\u5217\u8868\u89e3\u6790\u662f\u4e00\u79cd\u7b80\u6d01\u7684\u65b9\u5f0f\u6765\u521b\u5efa\u5217\u8868\u3002\u5b83\u4f7f\u7528\u4e00\u4e2a\u8868\u8fbe\u5f0f\u6765\u5b9a\u4e49\u5217\u8868\u7684\u6bcf\u4e2a\u5143\u7d20\u3002<\/p>\n<\/p>\n<p><h4>2. \u5b9e\u73b0\u793a\u4f8b<\/h4>\n<\/p>\n<p><p>\u4e0b\u9762\u662f\u4e00\u4e2a\u4f7f\u7528\u5217\u8868\u89e3\u6790\u5c06\u4e8c\u7ef4\u6570\u7ec4\u8f6c\u6362\u4e3a\u4e09\u7ef4\u6570\u7ec4\u7684\u793a\u4f8b\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u521b\u5efa\u4e00\u4e2a\u4e8c\u7ef4\u6570\u7ec4<\/p>\n<p>two_d_array = [[1, 2, 3], [4, 5, 6]]<\/p>\n<h2><strong>\u4f7f\u7528\u5217\u8868\u89e3\u6790\u5c06\u4e8c\u7ef4\u6570\u7ec4\u8f6c\u6362\u4e3a\u4e09\u7ef4\u6570\u7ec4<\/strong><\/h2>\n<p>three_d_array = [[[item for item in row]] for row in two_d_array]<\/p>\n<p>print(three_d_array)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u8fd9\u4e2a\u4f8b\u5b50\u901a\u8fc7\u5217\u8868\u89e3\u6790\u5c06\u6bcf\u4e00\u884c\u7684\u5143\u7d20\u5305\u88c5\u5728\u4e00\u4e2a\u65b0\u7684\u5217\u8868\u4e2d\uff0c\u4ece\u800c\u5c06\u4e8c\u7ef4\u6570\u7ec4\u8f6c\u6362\u4e3a\u4e09\u7ef4\u6570\u7ec4\u3002<\/p>\n<\/p>\n<p><h3>\u56db\u3001\u603b\u7ed3<\/h3>\n<\/p>\n<p><p>Python\u63d0\u4f9b\u4e86\u591a\u79cd\u5c06\u4e8c\u7ef4\u6570\u7ec4\u8f6c\u6362\u4e3a\u4e09\u7ef4\u6570\u7ec4\u7684\u65b9\u6cd5\u3002\u5176\u4e2d\uff0c<strong>\u4f7f\u7528NumPy\u5e93\u662f\u6700\u5e38\u7528\u548c\u6700\u4fbf\u6377\u7684\u65b9\u6cd5<\/strong>\uff0c\u5b83\u63d0\u4f9b\u4e86\u5f3a\u5927\u7684\u6570\u7ec4\u64cd\u4f5c\u529f\u80fd\uff0c\u9002\u5408\u5904\u7406\u590d\u6742\u7684\u591a\u7ef4\u6570\u7ec4\u3002\u624b\u52a8\u5b9e\u73b0\u5d4c\u5957\u5faa\u73af\u7684\u65b9\u6cd5\u5219\u9002\u5408\u7406\u89e3\u6570\u7ec4\u7684\u57fa\u672c\u64cd\u4f5c\u548c\u7ed3\u6784\uff0c\u800c<strong>\u5217\u8868\u89e3\u6790\u65b9\u6cd5\u5219\u63d0\u4f9b\u4e86\u4e00\u79cd\u7b80\u6d01\u7684\u4ee3\u7801\u5b9e\u73b0\u65b9\u5f0f<\/strong>\u3002<\/p>\n<\/p>\n<p><p>\u65e0\u8bba\u91c7\u7528\u54ea\u79cd\u65b9\u6cd5\uff0c\u90fd\u9700\u8981\u6839\u636e\u5177\u4f53\u7684\u9700\u6c42\u548c\u6570\u636e\u7ed3\u6784\u9009\u62e9\u5408\u9002\u7684\u5b9e\u73b0\u65b9\u5f0f\u3002\u5728\u5b9e\u9645\u5e94\u7528\u4e2d\uff0cNumPy\u5e93\u5f80\u5f80\u662f\u9996\u9009\uff0c\u56e0\u4e3a\u5b83\u4e0d\u4ec5\u7b80\u5316\u4e86\u4ee3\u7801\uff0c\u8fd8\u63d0\u9ad8\u4e86\u8ba1\u7b97\u6548\u7387\u3002<\/p>\n<\/p>\n<h2><strong>\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n<p> <strong>\u5728Python\u4e2d\uff0c\u5982\u4f55\u5c06\u4e00\u4e2a\u4e8c\u7ef4\u6570\u7ec4\u8f6c\u6362\u4e3a\u4e09\u7ef4\u6570\u7ec4\uff1f<\/strong><br \/>\u8981\u5c06\u4e8c\u7ef4\u6570\u7ec4\u8f6c\u6362\u4e3a\u4e09\u7ef4\u6570\u7ec4\uff0c\u53ef\u4ee5\u4f7f\u7528NumPy\u5e93\u3002\u9996\u5148\uff0c\u786e\u4fdd\u5df2\u5b89\u88c5NumPy\u3002\u7136\u540e\uff0c\u53ef\u4ee5\u5229\u7528<code>reshape<\/code>\u51fd\u6570\u6765\u6539\u53d8\u6570\u7ec4\u7684\u5f62\u72b6\u3002\u4f8b\u5982\uff0c\u53ef\u4ee5\u5c06\u4e00\u4e2a\u5f62\u72b6\u4e3a(3, 4)\u7684\u4e8c\u7ef4\u6570\u7ec4\u8f6c\u6362\u4e3a\u5f62\u72b6\u4e3a(3, 2, 2)\u7684\u4e09\u7ef4\u6570\u7ec4\u3002\u5177\u4f53\u4ee3\u7801\u5982\u4e0b\uff1a  <\/p>\n<pre><code class=\"language-python\">import numpy as np\n\n# \u521b\u5efa\u4e00\u4e2a\u4e8c\u7ef4\u6570\u7ec4\narray_2d = np.array([[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 11, 12]])\n\n# \u4f7f\u7528reshape\u8f6c\u6362\u4e3a\u4e09\u7ef4\u6570\u7ec4\narray_3d = array_2d.reshape((3, 2, 2))\nprint(array_3d)\n<\/code><\/pre>\n<p><strong>\u5982\u4f55\u5904\u7406\u8f6c\u6362\u8fc7\u7a0b\u4e2d\u53ef\u80fd\u51fa\u73b0\u7684\u9519\u8bef\uff1f<\/strong><br \/>\u5728\u8fdb\u884c\u7ef4\u5ea6\u8f6c\u6362\u65f6\uff0c\u5982\u679c\u76ee\u6807\u5f62\u72b6\u7684\u5143\u7d20\u603b\u6570\u4e0e\u6e90\u6570\u7ec4\u7684\u5143\u7d20\u603b\u6570\u4e0d\u5339\u914d\uff0c\u5c06\u4f1a\u5f15\u53d1\u9519\u8bef\u3002\u53ef\u4ee5\u901a\u8fc7\u68c0\u67e5\u6e90\u6570\u7ec4\u7684\u5143\u7d20\u6570\u91cf\u548c\u76ee\u6807\u5f62\u72b6\u7684\u5143\u7d20\u6570\u91cf\u662f\u5426\u76f8\u7b49\u6765\u907f\u514d\u8fd9\u79cd\u60c5\u51b5\u3002\u4f7f\u7528<code>np.size()<\/code>\u51fd\u6570\u6765\u83b7\u53d6\u5143\u7d20\u6570\u91cf\uff0c\u786e\u4fdd\u5b83\u4eec\u4e00\u81f4\u3002<\/p>\n<p><strong>\u662f\u5426\u53ef\u4ee5\u4f7f\u7528\u5176\u4ed6\u5e93\u5b9e\u73b0\u7c7b\u4f3c\u7684\u529f\u80fd\uff1f<\/strong><br \/>\u9664\u4e86NumPy\uff0c\u5176\u4ed6\u5e93\u5982TensorFlow\u548cPyTorch\u4e5f\u652f\u6301\u6570\u7ec4\u5f62\u72b6\u7684\u8f6c\u6362\u3002\u8fd9\u4e9b\u5e93\u901a\u5e38\u7528\u4e8e\u5904\u7406\u66f4\u590d\u6742\u7684\u6df1\u5ea6\u5b66\u4e60\u4efb\u52a1\uff0c\u4f46\u5b83\u4eec\u4e5f\u53ef\u4ee5\u7528\u6765\u8fdb\u884c\u57fa\u672c\u7684\u6570\u7ec4\u64cd\u4f5c\u3002\u4f8b\u5982\uff0c\u5728TensorFlow\u4e2d\u53ef\u4ee5\u4f7f\u7528<code>tf.reshape()<\/code>\u51fd\u6570\u5b8c\u6210\u7c7b\u4f3c\u7684\u4efb\u52a1\u3002\u5b9e\u73b0\u65b9\u6cd5\u7c7b\u4f3c\uff0c\u7528\u6237\u53ef\u4ee5\u6839\u636e\u81ea\u5df1\u7684\u9700\u6c42\u9009\u62e9\u5408\u9002\u7684\u5e93\u3002<\/p>\n<p><strong>\u5728\u8f6c\u6362\u8fc7\u7a0b\u4e2d\uff0c\u5982\u4f55\u786e\u4fdd\u6570\u636e\u7684\u987a\u5e8f\u4e0d\u53d8\uff1f<\/strong><br \/>\u5728\u8fdb\u884c\u6570\u7ec4\u7ef4\u5ea6\u8f6c\u6362\u65f6\uff0c\u53ef\u4ee5\u901a\u8fc7\u6307\u5b9a<code>order<\/code>\u53c2\u6570\u6765\u786e\u4fdd\u6570\u636e\u987a\u5e8f\u4e0d\u53d8\u3002<code>order<\/code>\u53c2\u6570\u53ef\u4ee5\u8bbe\u7f6e\u4e3a&#39;F&#39;\uff08\u5217\u4f18\u5148\uff09\u6216&#39;C&#39;\uff08\u884c\u4f18\u5148\uff09\uff0c\u9ed8\u8ba4\u662f&#39;C&#39;\u3002\u901a\u8fc7\u8c03\u6574\u8fd9\u4e2a\u53c2\u6570\uff0c\u53ef\u4ee5\u63a7\u5236\u6570\u636e\u5728\u5185\u5b58\u4e2d\u7684\u5b58\u50a8\u987a\u5e8f\uff0c\u4ece\u800c\u4fdd\u6301\u8f6c\u6362\u540e\u7684\u6570\u636e\u987a\u5e8f\u4e0e\u539f\u6570\u636e\u4e00\u81f4\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"Python\u5c06\u4e8c\u7ef4\u6570\u7ec4\u8f6c\u5316\u4e3a\u4e09\u7ef4\u6570\u7ec4\u7684\u65b9\u6cd5\u6709\u591a\u79cd\uff0c\u6700\u5e38\u7528\u7684\u6709\uff1a\u4f7f\u7528NumPy\u5e93\u3001\u624b\u52a8\u5b9e\u73b0\u5d4c\u5957\u5faa\u73af\u3001\u4ee5\u53ca\u4f7f\u7528\u5217\u8868 [&hellip;]","protected":false},"author":3,"featured_media":1146322,"comment_status":"closed","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[37],"tags":[],"acf":[],"_links":{"self":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1146315"}],"collection":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/comments?post=1146315"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1146315\/revisions"}],"predecessor-version":[{"id":1146325,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1146315\/revisions\/1146325"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/1146322"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=1146315"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=1146315"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=1146315"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}