{"id":1171421,"date":"2025-01-15T16:35:08","date_gmt":"2025-01-15T08:35:08","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1171421.html"},"modified":"2025-01-15T16:35:12","modified_gmt":"2025-01-15T08:35:12","slug":"python%e5%a6%82%e4%bd%95%e6%9f%a5%e7%9c%8b%e6%95%b0%e7%bb%84%e7%bb%b4%e6%95%b0","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/1171421.html","title":{"rendered":"python\u5982\u4f55\u67e5\u770b\u6570\u7ec4\u7ef4\u6570"},"content":{"rendered":"<p style=\"text-align:center;\" ><img decoding=\"async\" src=\"https:\/\/cdn-kb.worktile.com\/kb\/wp-content\/uploads\/2024\/04\/26073753\/8b00401c-113d-418d-92c8-babc94e3ab41.webp\" alt=\"python\u5982\u4f55\u67e5\u770b\u6570\u7ec4\u7ef4\u6570\" \/><\/p>\n<p><p> <strong>Python\u67e5\u770b\u6570\u7ec4\u7ef4\u6570\u7684\u65b9\u6cd5\u6709\u591a\u79cd\uff0c\u5982\u901a\u8fc7<code>ndim<\/code>\u5c5e\u6027\u3001<code>shape<\/code>\u5c5e\u6027\u3001<code>len<\/code>\u51fd\u6570\u3001<code>size<\/code>\u5c5e\u6027\u7b49\u3002<\/strong> \u5176\u4e2d\uff0c<code>ndim<\/code>\u5c5e\u6027\u6700\u4e3a\u76f4\u63a5\uff0c\u53ef\u4ee5\u5feb\u901f\u67e5\u770b\u6570\u7ec4\u7684\u7ef4\u6570\u3002\u4f8b\u5982\uff0c\u5bf9\u4e8e\u4e00\u4e2aNumPy\u6570\u7ec4\uff0c\u53ef\u4ee5\u901a\u8fc7\u8bbf\u95ee\u5176<code>ndim<\/code>\u5c5e\u6027\u6765\u83b7\u53d6\u7ef4\u6570\u3002\u4e0b\u9762\u5c06\u8be6\u7ec6\u4ecb\u7ecd\u8fd9\u4e9b\u65b9\u6cd5\uff0c\u5e76\u63d0\u4f9b\u5177\u4f53\u7684\u793a\u4f8b\u4ee3\u7801\u3002<\/p>\n<\/p>\n<p><h3>\u4e00\u3001\u4f7f\u7528NumPy\u5e93\u67e5\u770b\u6570\u7ec4\u7ef4\u6570<\/h3>\n<\/p>\n<p><h4>1\u3001<code>ndim<\/code>\u5c5e\u6027<\/h4>\n<\/p>\n<p><p>NumPy\u5e93\u4e2d\u7684\u6570\u7ec4\u5bf9\u8c61\uff08\u5373ndarray\uff09\u6709\u4e00\u4e2a\u5c5e\u6027\u53eb\u505a<code>ndim<\/code>\uff0c\u53ef\u4ee5\u76f4\u63a5\u8fd4\u56de\u6570\u7ec4\u7684\u7ef4\u6570\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u793a\u4f8b\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>array_2d = np.array([[1, 2, 3], [4, 5, 6]])<\/p>\n<h2><strong>\u67e5\u770b\u6570\u7ec4\u7684\u7ef4\u6570<\/strong><\/h2>\n<p>print(array_2d.ndim)  # \u8f93\u51fa\uff1a2<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u5728\u8fd9\u4e2a\u793a\u4f8b\u4e2d\uff0c<code>array_2d<\/code>\u662f\u4e00\u4e2a\u4e8c\u7ef4\u6570\u7ec4\uff0c\u8c03\u7528<code>array_2d.ndim<\/code>\u8fd4\u56de2\uff0c\u8868\u793a\u5b83\u662f\u4e00\u4e2a\u4e8c\u7ef4\u6570\u7ec4\u3002<\/p>\n<\/p>\n<p><h4>2\u3001<code>shape<\/code>\u5c5e\u6027<\/h4>\n<\/p>\n<p><p><code>shape<\/code>\u5c5e\u6027\u8fd4\u56de\u4e00\u4e2a\u5305\u542b\u6570\u7ec4\u5404\u7ef4\u5ea6\u5927\u5c0f\u7684\u5143\u7ec4\uff0c\u901a\u8fc7\u67e5\u770b\u5143\u7ec4\u7684\u957f\u5ea6\u4e5f\u53ef\u4ee5\u5f97\u77e5\u6570\u7ec4\u7684\u7ef4\u6570\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u67e5\u770b\u6570\u7ec4\u7684\u5f62\u72b6<\/p>\n<p>print(array_2d.shape)  # \u8f93\u51fa\uff1a(2, 3)<\/p>\n<h2><strong>\u8ba1\u7b97\u6570\u7ec4\u7684\u7ef4\u6570<\/strong><\/h2>\n<p>print(len(array_2d.shape))  # \u8f93\u51fa\uff1a2<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u5728\u8fd9\u4e2a\u793a\u4f8b\u4e2d\uff0c<code>array_2d.shape<\/code>\u8fd4\u56de(2, 3)\uff0c\u8868\u793a\u6570\u7ec4\u67092\u884c3\u5217\uff0c<code>len(array_2d.shape)<\/code>\u8fd4\u56de2\uff0c\u8868\u793a\u6570\u7ec4\u662f\u4e8c\u7ef4\u7684\u3002<\/p>\n<\/p>\n<p><h4>3\u3001<code>size<\/code>\u5c5e\u6027<\/h4>\n<\/p>\n<p><p>\u867d\u7136<code>size<\/code>\u5c5e\u6027\u4e3b\u8981\u7528\u4e8e\u83b7\u53d6\u6570\u7ec4\u4e2d\u5143\u7d20\u7684\u603b\u6570\uff0c\u4f46\u7ed3\u5408<code>shape<\/code>\u5c5e\u6027\uff0c\u53ef\u4ee5\u95f4\u63a5\u4e86\u89e3\u6570\u7ec4\u7684\u7ef4\u6570\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u67e5\u770b\u6570\u7ec4\u7684\u5143\u7d20\u603b\u6570<\/p>\n<p>print(array_2d.size)  # \u8f93\u51fa\uff1a6<\/p>\n<h2><strong>\u8ba1\u7b97\u6570\u7ec4\u7684\u7ef4\u6570<\/strong><\/h2>\n<p>print(len(array_2d.shape))  # \u8f93\u51fa\uff1a2<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u5728\u8fd9\u4e2a\u793a\u4f8b\u4e2d\uff0c<code>array_2d.size<\/code>\u8fd4\u56de6\uff0c\u8868\u793a\u6570\u7ec4\u4e2d\u67096\u4e2a\u5143\u7d20\uff0c\u7ed3\u5408<code>shape<\/code>\u5c5e\u6027\uff0c\u53ef\u4ee5\u5f97\u77e5\u6570\u7ec4\u662f\u4e8c\u7ef4\u7684\u3002<\/p>\n<\/p>\n<p><h3>\u4e8c\u3001\u4f7f\u7528\u5176\u4ed6\u65b9\u6cd5\u67e5\u770b\u6570\u7ec4\u7ef4\u6570<\/h3>\n<\/p>\n<p><h4>1\u3001<code>len<\/code>\u51fd\u6570<\/h4>\n<\/p>\n<p><p>\u5bf9\u4e8e\u5d4c\u5957\u5217\u8868\u5f62\u5f0f\u7684\u6570\u7ec4\uff0c\u53ef\u4ee5\u901a\u8fc7\u9012\u5f52\u7684\u65b9\u5f0f\u4f7f\u7528<code>len<\/code>\u51fd\u6570\u6765\u8ba1\u7b97\u7ef4\u6570\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">def get_array_dimension(arr):<\/p>\n<p>    if isinstance(arr, list):<\/p>\n<p>        return 1 + get_array_dimension(arr[0])<\/p>\n<p>    return 0<\/p>\n<h2><strong>\u521b\u5efa\u4e00\u4e2a\u5d4c\u5957\u5217\u8868<\/strong><\/h2>\n<p>nested_list = [[1, 2, 3], [4, 5, 6]]<\/p>\n<h2><strong>\u67e5\u770b\u5217\u8868\u7684\u7ef4\u6570<\/strong><\/h2>\n<p>print(get_array_dimension(nested_list))  # \u8f93\u51fa\uff1a2<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u5728\u8fd9\u4e2a\u793a\u4f8b\u4e2d\uff0c<code>nested_list<\/code>\u662f\u4e00\u4e2a\u4e8c\u7ef4\u5217\u8868\uff0c\u8c03\u7528<code>get_array_dimension<\/code>\u51fd\u6570\u8fd4\u56de2\uff0c\u8868\u793a\u5b83\u662f\u4e00\u4e2a\u4e8c\u7ef4\u6570\u7ec4\u3002<\/p>\n<\/p>\n<p><h4>2\u3001<code>tf.rank<\/code>\u51fd\u6570\uff08TensorFlow\uff09<\/h4>\n<\/p>\n<p><p>\u5bf9\u4e8eTensorFlow\u5e93\u4e2d\u7684\u5f20\u91cf\uff0c\u53ef\u4ee5\u4f7f\u7528<code>tf.rank<\/code>\u51fd\u6570\u6765\u83b7\u53d6\u5f20\u91cf\u7684\u7ef4\u6570\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import tensorflow as tf<\/p>\n<h2><strong>\u521b\u5efa\u4e00\u4e2a\u4e8c\u7ef4\u5f20\u91cf<\/strong><\/h2>\n<p>tensor_2d = tf.constant([[1, 2, 3], [4, 5, 6]])<\/p>\n<h2><strong>\u67e5\u770b\u5f20\u91cf\u7684\u7ef4\u6570<\/strong><\/h2>\n<p>print(tf.rank(tensor_2d).numpy())  # \u8f93\u51fa\uff1a2<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u5728\u8fd9\u4e2a\u793a\u4f8b\u4e2d\uff0c<code>tensor_2d<\/code>\u662f\u4e00\u4e2a\u4e8c\u7ef4\u5f20\u91cf\uff0c\u8c03\u7528<code>tf.rank<\/code>\u51fd\u6570\u8fd4\u56de2\uff0c\u8868\u793a\u5b83\u662f\u4e00\u4e2a\u4e8c\u7ef4\u5f20\u91cf\u3002<\/p>\n<\/p>\n<p><h3>\u4e09\u3001\u5177\u4f53\u5e94\u7528\u573a\u666f<\/h3>\n<\/p>\n<p><h4>1\u3001\u6570\u636e\u9884\u5904\u7406<\/h4>\n<\/p>\n<p><p>\u5728\u8fdb\u884c\u6570\u636e\u5206\u6790\u548c<a href=\"https:\/\/docs.pingcode.com\/ask\/59192.html\" target=\"_blank\">\u673a\u5668\u5b66\u4e60<\/a>\u65f6\uff0c\u7ecf\u5e38\u9700\u8981\u5bf9\u6570\u636e\u8fdb\u884c\u9884\u5904\u7406\u3002\u4e86\u89e3\u6570\u636e\u7684\u7ef4\u6570\u662f\u9884\u5904\u7406\u7684\u7b2c\u4e00\u6b65\uff0c\u53ef\u4ee5\u5e2e\u52a9\u6211\u4eec\u786e\u5b9a\u662f\u5426\u9700\u8981\u5bf9\u6570\u636e\u8fdb\u884c\u964d\u7ef4\u6216\u5176\u4ed6\u64cd\u4f5c\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u793a\u4f8b\uff1a\u6570\u636e\u9884\u5904\u7406<\/p>\n<p>data = np.random.rand(100, 5)  # \u751f\u6210\u4e00\u4e2a100\u884c5\u5217\u7684\u968f\u673a\u6570\u7ec4<\/p>\n<h2><strong>\u67e5\u770b\u6570\u636e\u7684\u7ef4\u6570<\/strong><\/h2>\n<p>print(data.ndim)  # \u8f93\u51fa\uff1a2<\/p>\n<h2><strong>\u5982\u679c\u6570\u636e\u7ef4\u6570\u5927\u4e8e2\uff0c\u5219\u8fdb\u884c\u964d\u7ef4\u5904\u7406<\/strong><\/h2>\n<p>if data.ndim &gt; 2:<\/p>\n<p>    data = data.reshape(-1, 2)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u5728\u8fd9\u4e2a\u793a\u4f8b\u4e2d\uff0c\u751f\u6210\u4e86\u4e00\u4e2a100\u884c5\u5217\u7684\u968f\u673a\u6570\u7ec4\uff0c\u901a\u8fc7\u67e5\u770b\u7ef4\u6570\u6765\u51b3\u5b9a\u662f\u5426\u9700\u8981\u8fdb\u884c\u964d\u7ef4\u5904\u7406\u3002<\/p>\n<\/p>\n<p><h4>2\u3001\u6a21\u578b\u8f93\u5165<\/h4>\n<\/p>\n<p><p>\u5728\u6df1\u5ea6\u5b66\u4e60\u4e2d\uff0c\u6a21\u578b\u7684\u8f93\u5165\u901a\u5e38\u662f\u9ad8\u7ef4\u6570\u636e\uff08\u5982\u56fe\u50cf\u6570\u636e\u662f\u56db\u7ef4\u7684\uff09\u3002\u4e86\u89e3\u8f93\u5165\u6570\u636e\u7684\u7ef4\u6570\u6709\u52a9\u4e8e\u6211\u4eec\u6b63\u786e\u8bbe\u8ba1\u548c\u8bad\u7ec3\u6a21\u578b\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import tensorflow as tf<\/p>\n<h2><strong>\u793a\u4f8b\uff1a\u6a21\u578b\u8f93\u5165<\/strong><\/h2>\n<p>input_data = tf.random.normal([32, 224, 224, 3])  # \u751f\u6210\u4e00\u4e2a32\u4e2a224x224x3\u7684\u968f\u673a\u5f20\u91cf<\/p>\n<h2><strong>\u67e5\u770b\u8f93\u5165\u6570\u636e\u7684\u7ef4\u6570<\/strong><\/h2>\n<p>print(tf.rank(input_data).numpy())  # \u8f93\u51fa\uff1a4<\/p>\n<h2><strong>\u5982\u679c\u8f93\u5165\u6570\u636e\u7ef4\u6570\u4e0d\u7b26\u5408\u6a21\u578b\u8981\u6c42\uff0c\u5219\u8fdb\u884c\u8c03\u6574<\/strong><\/h2>\n<p>if tf.rank(input_data).numpy() != 4:<\/p>\n<p>    input_data = tf.reshape(input_data, [-1, 224, 224, 3])<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u5728\u8fd9\u4e2a\u793a\u4f8b\u4e2d\uff0c\u751f\u6210\u4e86\u4e00\u4e2a\u56db\u7ef4\u7684\u968f\u673a\u5f20\u91cf\uff0c\u901a\u8fc7\u67e5\u770b\u7ef4\u6570\u6765\u51b3\u5b9a\u662f\u5426\u9700\u8981\u8c03\u6574\u8f93\u5165\u6570\u636e\u3002<\/p>\n<\/p>\n<p><h3>\u56db\u3001\u603b\u7ed3<\/h3>\n<\/p>\n<p><p>\u901a\u8fc7\u4e0a\u8ff0\u65b9\u6cd5\uff0c\u53ef\u4ee5\u65b9\u4fbf\u5730\u67e5\u770bPython\u4e2d\u6570\u7ec4\u7684\u7ef4\u6570\uff0c<strong>\u65e0\u8bba\u662f\u4f7f\u7528NumPy\u5e93\u4e2d\u7684<code>ndim<\/code>\u5c5e\u6027\u3001<code>shape<\/code>\u5c5e\u6027\uff0c\u8fd8\u662f\u4f7f\u7528\u5176\u4ed6\u65b9\u6cd5\uff08\u5982\u9012\u5f52\u8ba1\u7b97\u5d4c\u5957\u5217\u8868\u7684\u7ef4\u6570\u6216\u4f7f\u7528TensorFlow\u7684<code>tf.rank<\/code>\u51fd\u6570\uff09\uff0c\u90fd\u80fd\u6ee1\u8db3\u4e0d\u540c\u573a\u666f\u4e0b\u7684\u9700\u6c42\u3002<\/strong> \u4e86\u89e3\u6570\u7ec4\u7684\u7ef4\u6570\u5728\u6570\u636e\u9884\u5904\u7406\u3001\u6a21\u578b\u8f93\u5165\u7b49\u5e94\u7528\u4e2d\u81f3\u5173\u91cd\u8981\uff0c\u53ef\u4ee5\u5e2e\u52a9\u6211\u4eec\u66f4\u597d\u5730\u5904\u7406\u548c\u5206\u6790\u6570\u636e\u3002<\/p>\n<\/p>\n<h2><strong>\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n<p> <strong>\u5982\u4f55\u5728Python\u4e2d\u68c0\u67e5\u6570\u7ec4\u7684\u7ef4\u5ea6\uff1f<\/strong><br \/>\u5728Python\u4e2d\uff0c\u53ef\u4ee5\u4f7f\u7528NumPy\u5e93\u6765\u521b\u5efa\u548c\u64cd\u4f5c\u6570\u7ec4\u3002\u8981\u67e5\u770b\u6570\u7ec4\u7684\u7ef4\u5ea6\uff0c\u53ef\u4ee5\u4f7f\u7528\u6570\u7ec4\u5bf9\u8c61\u7684<code>ndim<\/code>\u5c5e\u6027\u3002\u4f8b\u5982\uff0c\u5047\u8bbe\u6211\u4eec\u6709\u4e00\u4e2aNumPy\u6570\u7ec4<code>arr<\/code>\uff0c\u53ef\u4ee5\u901a\u8fc7<code>arr.ndim<\/code>\u6765\u83b7\u53d6\u5176\u7ef4\u6570\u3002\u793a\u4f8b\u4ee3\u7801\u5982\u4e0b\uff1a<\/p>\n<pre><code class=\"language-python\">import numpy as np\n\narr = np.array([[1, 2, 3], [4, 5, 6]])\nprint(arr.ndim)  # \u8f93\u51fa\uff1a2\n<\/code><\/pre>\n<p><strong>\u5728Python\u4e2d\u521b\u5efa\u591a\u7ef4\u6570\u7ec4\u7684\u6700\u4f73\u65b9\u6cd5\u662f\u4ec0\u4e48\uff1f<\/strong><br \/>\u4f7f\u7528NumPy\u5e93\u662f\u521b\u5efa\u591a\u7ef4\u6570\u7ec4\u7684\u6700\u4f73\u9009\u62e9\u3002NumPy\u63d0\u4f9b\u4e86\u7075\u6d3b\u7684\u5de5\u5177\u6765\u521b\u5efa\u548c\u64cd\u4f5c\u6570\u7ec4\u3002\u53ef\u4ee5\u4f7f\u7528<code>np.array()<\/code>\u3001<code>np.zeros()<\/code>\u3001<code>np.ones()<\/code>\u6216<code>np.arange()<\/code>\u7b49\u51fd\u6570\u6765\u751f\u6210\u4e0d\u540c\u7ef4\u5ea6\u7684\u6570\u7ec4\uff0c\u9002\u5e94\u4e0d\u540c\u7684\u9700\u6c42\u3002\u4f8b\u5982\uff1a<\/p>\n<pre><code class=\"language-python\">import numpy as np\n\n# \u521b\u5efa\u4e00\u4e2a3\u7ef4\u6570\u7ec4\narr = np.zeros((2, 3, 4))\nprint(arr.shape)  # \u8f93\u51fa\uff1a (2, 3, 4)\n<\/code><\/pre>\n<p><strong>\u5982\u4f55\u83b7\u53d6\u591a\u7ef4\u6570\u7ec4\u7684\u5f62\u72b6\u4fe1\u606f\uff1f<\/strong><br \/>\u83b7\u53d6\u591a\u7ef4\u6570\u7ec4\u7684\u5f62\u72b6\u4fe1\u606f\u53ef\u4ee5\u901a\u8fc7\u4f7f\u7528<code>shape<\/code>\u5c5e\u6027\u6765\u5b9e\u73b0\u3002\u8be5\u5c5e\u6027\u8fd4\u56de\u4e00\u4e2a\u8868\u793a\u6570\u7ec4\u5728\u6bcf\u4e2a\u7ef4\u5ea6\u4e0a\u7684\u5927\u5c0f\u7684\u5143\u7ec4\u3002\u4f8b\u5982\uff0c\u5bf9\u4e8e\u4e00\u4e2a\u4e8c\u7ef4\u6570\u7ec4\uff0c\u53ef\u4ee5\u901a\u8fc7<code>arr.shape<\/code>\u6765\u67e5\u770b\u5176\u884c\u548c\u5217\u7684\u6570\u91cf\u3002\u793a\u4f8b\uff1a<\/p>\n<pre><code class=\"language-python\">import numpy as np\n\narr = np.array([[1, 2, 3], [4, 5, 6]])\nprint(arr.shape)  # \u8f93\u51fa\uff1a(2, 3)\uff0c\u8868\u793a\u67092\u884c3\u5217\n<\/code><\/pre>\n","protected":false},"excerpt":{"rendered":"Python\u67e5\u770b\u6570\u7ec4\u7ef4\u6570\u7684\u65b9\u6cd5\u6709\u591a\u79cd\uff0c\u5982\u901a\u8fc7ndim\u5c5e\u6027\u3001shape\u5c5e\u6027\u3001len\u51fd\u6570\u3001size\u5c5e\u6027\u7b49\u3002 \u5176\u4e2d\uff0c [&hellip;]","protected":false},"author":3,"featured_media":1171427,"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\/1171421"}],"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=1171421"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1171421\/revisions"}],"predecessor-version":[{"id":1171429,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1171421\/revisions\/1171429"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/1171427"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=1171421"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=1171421"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=1171421"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}