{"id":1089372,"date":"2025-01-08T13:52:54","date_gmt":"2025-01-08T05:52:54","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1089372.html"},"modified":"2025-01-08T13:52:56","modified_gmt":"2025-01-08T05:52:56","slug":"python%e5%a6%82%e4%bd%95%e8%af%bb%e5%85%a5csv%e6%95%b0%e6%8d%ae200w-2","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/1089372.html","title":{"rendered":"python\u5982\u4f55\u8bfb\u5165csv\u6570\u636e200w"},"content":{"rendered":"<p style=\"text-align:center;\" ><img decoding=\"async\" src=\"https:\/\/cdn-kb.worktile.com\/kb\/wp-content\/uploads\/2024\/04\/24202326\/96147c04-15a4-414a-ad65-4ec2175ef742.webp\" alt=\"python\u5982\u4f55\u8bfb\u5165csv\u6570\u636e200w\" \/><\/p>\n<p><p> <strong>Python\u8bfb\u5165CSV\u6570\u636e200W\u7684\u6838\u5fc3\u65b9\u6cd5\u6709\uff1a\u4f7f\u7528Pandas\u5e93\u3001\u4f7f\u7528Dask\u5e93\u3001\u4f7f\u7528csv\u6a21\u5757\u3002<\/strong> \u5728\u8fd9\u4e9b\u65b9\u6cd5\u4e2d\uff0c\u4f7f\u7528Pandas\u5e93\u662f\u6700\u5e38\u89c1\u548c\u65b9\u4fbf\u7684\u65b9\u6cd5\uff0c\u56e0\u4e3a\u5b83\u63d0\u4f9b\u4e86\u5f3a\u5927\u7684\u6570\u636e\u5904\u7406\u529f\u80fd\u3002\u4e0b\u9762\u8be6\u7ec6\u4ecb\u7ecd\u5982\u4f55\u4f7f\u7528Pandas\u5e93\u6765\u8bfb\u53d6\u548c\u5904\u7406\u5927\u89c4\u6a21\u7684CSV\u6570\u636e\u3002<\/p>\n<\/p>\n<p><h3>\u4e00\u3001\u4f7f\u7528Pandas\u5e93<\/h3>\n<\/p>\n<p><p>Pandas\u5e93\u662fPython\u4e2d\u6700\u5e38\u7528\u7684\u6570\u636e\u5206\u6790\u5de5\u5177\uff0c\u63d0\u4f9b\u4e86\u9ad8\u6548\u7684\u6570\u636e\u7ed3\u6784\u548c\u6570\u636e\u5206\u6790\u5de5\u5177\u3002\u8bfb\u53d6CSV\u6587\u4ef6\u65f6\uff0cPandas\u80fd\u591f\u81ea\u52a8\u8bc6\u522b\u6570\u636e\u7c7b\u578b\uff0c\u5e76\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u6570\u636e\u5904\u7406\u548c\u64cd\u4f5c\u65b9\u6cd5\u3002<\/p>\n<\/p>\n<p><h4>1\u3001\u5b89\u88c5Pandas\u5e93<\/h4>\n<\/p>\n<p><p>\u5982\u679c\u5c1a\u672a\u5b89\u88c5Pandas\u5e93\uff0c\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u547d\u4ee4\u8fdb\u884c\u5b89\u88c5\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">pip install pandas<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h4>2\u3001\u8bfb\u53d6CSV\u6587\u4ef6<\/h4>\n<\/p>\n<p><p>\u4f7f\u7528Pandas\u5e93\u8bfb\u53d6CSV\u6587\u4ef6\u975e\u5e38\u7b80\u5355\uff0c\u53ea\u9700\u4e00\u884c\u4ee3\u7801\u5373\u53ef\u5b9e\u73b0\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import pandas as pd<\/p>\n<p>df = pd.read_csv(&#39;large_file.csv&#39;)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h4>3\u3001\u5904\u7406\u5927\u6587\u4ef6<\/h4>\n<\/p>\n<p><p>\u5bf9\u4e8e\u5927\u6587\u4ef6\uff0c\u76f4\u63a5\u8bfb\u53d6\u53ef\u80fd\u4f1a\u5bfc\u81f4\u5185\u5b58\u4e0d\u8db3\u7684\u95ee\u9898\u3002\u53ef\u4ee5\u901a\u8fc7\u6307\u5b9a\u6570\u636e\u7c7b\u578b\u3001\u4f7f\u7528\u5206\u5757\u8bfb\u53d6\u7b49\u65b9\u6cd5\u6765\u4f18\u5316\u5185\u5b58\u4f7f\u7528\u3002<\/p>\n<\/p>\n<p><p><strong>\u6307\u5b9a\u6570\u636e\u7c7b\u578b\uff1a<\/strong><\/p>\n<\/p>\n<p><p>\u901a\u8fc7\u6307\u5b9a\u6bcf\u4e00\u5217\u7684\u6570\u636e\u7c7b\u578b\uff0c\u53ef\u4ee5\u51cf\u5c11\u5185\u5b58\u4f7f\u7528\u3002\u4f8b\u5982\uff0c\u5c06\u6574\u6570\u5217\u6307\u5b9a\u4e3a<code>int32<\/code>\u6216<code>int64<\/code>\uff0c\u5c06\u6d6e\u70b9\u6570\u5217\u6307\u5b9a\u4e3a<code>float32<\/code>\u6216<code>float64<\/code>\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">df = pd.read_csv(&#39;large_file.csv&#39;, dtype={&#39;column1&#39;: &#39;int32&#39;, &#39;column2&#39;: &#39;float32&#39;})<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p><strong>\u5206\u5757\u8bfb\u53d6\uff1a<\/strong><\/p>\n<\/p>\n<p><p>Pandas\u63d0\u4f9b\u4e86<code>chunksize<\/code>\u53c2\u6570\uff0c\u53ef\u4ee5\u5206\u5757\u8bfb\u53d6\u5927\u6587\u4ef6\u3002\u8fd9\u6837\u53ef\u4ee5\u9010\u5757\u5904\u7406\u6570\u636e\uff0c\u800c\u4e0d\u662f\u4e00\u6b21\u6027\u5c06\u6574\u4e2a\u6587\u4ef6\u8bfb\u5165\u5185\u5b58\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">chunk_size = 100000<\/p>\n<p>chunks = pd.read_csv(&#39;large_file.csv&#39;, chunksize=chunk_size)<\/p>\n<p>for chunk in chunks:<\/p>\n<p>    # \u5904\u7406\u6bcf\u4e2a\u5757\u7684\u6570\u636e<\/p>\n<p>    process(chunk)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>\u4e8c\u3001\u4f7f\u7528Dask\u5e93<\/h3>\n<\/p>\n<p><p>Dask\u5e93\u662f\u53e6\u4e00\u4e2a\u5904\u7406\u5927\u89c4\u6a21\u6570\u636e\u7684\u5de5\u5177\uff0c\u80fd\u591f\u5904\u7406\u8d85\u51fa\u5185\u5b58\u9650\u5236\u7684\u5927\u6570\u636e\u96c6\u3002Dask\u53ef\u4ee5\u770b\u4f5c\u662fPandas\u7684\u5ef6\u4f38\uff0c\u63d0\u4f9b\u4e86\u7c7b\u4f3c\u7684\u63a5\u53e3\uff0c\u4f46\u652f\u6301\u5e76\u884c\u8ba1\u7b97\u3002<\/p>\n<\/p>\n<p><h4>1\u3001\u5b89\u88c5Dask\u5e93<\/h4>\n<\/p>\n<p><p>\u4f7f\u7528\u4ee5\u4e0b\u547d\u4ee4\u5b89\u88c5Dask\u5e93\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">pip install dask<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h4>2\u3001\u8bfb\u53d6CSV\u6587\u4ef6<\/h4>\n<\/p>\n<p><p>\u4f7f\u7528Dask\u8bfb\u53d6CSV\u6587\u4ef6\u7684\u65b9\u6cd5\u4e0ePandas\u7c7b\u4f3c\uff0c\u4f46Dask\u4f1a\u5ef6\u8fdf\u8ba1\u7b97\uff0c\u76f4\u5230\u771f\u6b63\u9700\u8981\u6570\u636e\u65f6\u624d\u4f1a\u8fdb\u884c\u8ba1\u7b97\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import dask.dataframe as dd<\/p>\n<p>df = dd.read_csv(&#39;large_file.csv&#39;)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h4>3\u3001\u5904\u7406\u6570\u636e<\/h4>\n<\/p>\n<p><p>Dask\u63d0\u4f9b\u4e86\u4e0ePandas\u7c7b\u4f3c\u7684\u63a5\u53e3\uff0c\u53ef\u4ee5\u8fdb\u884c\u6570\u636e\u5904\u7406\u548c\u5206\u6790\u3002\u5f53\u9700\u8981\u8ba1\u7b97\u7ed3\u679c\u65f6\uff0c\u8c03\u7528<code>compute()<\/code>\u65b9\u6cd5\u5373\u53ef\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">result = df.groupby(&#39;column&#39;).sum().compute()<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>\u4e09\u3001\u4f7f\u7528csv\u6a21\u5757<\/h3>\n<\/p>\n<p><p>Python\u5185\u7f6e\u7684csv\u6a21\u5757\u4e5f\u53ef\u4ee5\u7528\u6765\u8bfb\u53d6CSV\u6587\u4ef6\uff0c\u4f46\u76f8\u5bf9\u6765\u8bf4\u66f4\u5e95\u5c42\uff0c\u9700\u8981\u624b\u52a8\u5904\u7406\u6570\u636e\u3002\u5982\u679c\u9700\u8981\u5904\u7406\u975e\u5e38\u5927\u7684\u6587\u4ef6\uff0c\u53ef\u4ee5\u7ed3\u5408<code>itertools<\/code>\u6a21\u5757\u5b9e\u73b0\u5206\u5757\u8bfb\u53d6\u3002<\/p>\n<\/p>\n<p><h4>1\u3001\u8bfb\u53d6CSV\u6587\u4ef6<\/h4>\n<\/p>\n<p><p>\u4f7f\u7528csv\u6a21\u5757\u8bfb\u53d6CSV\u6587\u4ef6\u7684\u65b9\u6cd5\u5982\u4e0b\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import csv<\/p>\n<p>with open(&#39;large_file.csv&#39;, mode=&#39;r&#39;) as file:<\/p>\n<p>    reader = csv.reader(file)<\/p>\n<p>    for row in reader:<\/p>\n<p>        # \u5904\u7406\u6bcf\u4e00\u884c\u7684\u6570\u636e<\/p>\n<p>        process(row)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h4>2\u3001\u5206\u5757\u8bfb\u53d6<\/h4>\n<\/p>\n<p><p>\u7ed3\u5408<code>itertools.islice<\/code>\u5b9e\u73b0\u5206\u5757\u8bfb\u53d6\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import csv<\/p>\n<p>import itertools<\/p>\n<p>chunk_size = 100000<\/p>\n<p>with open(&#39;large_file.csv&#39;, mode=&#39;r&#39;) as file:<\/p>\n<p>    reader = csv.reader(file)<\/p>\n<p>    while True:<\/p>\n<p>        chunk = list(itertools.islice(reader, chunk_size))<\/p>\n<p>        if not chunk:<\/p>\n<p>            break<\/p>\n<p>        # \u5904\u7406\u6bcf\u4e2a\u5757\u7684\u6570\u636e<\/p>\n<p>        process(chunk)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>\u56db\u3001\u4f18\u5316\u6280\u5de7<\/h3>\n<\/p>\n<p><h4>1\u3001\u4f7f\u7528\u5408\u9002\u7684\u6570\u636e\u7c7b\u578b<\/h4>\n<\/p>\n<p><p>\u5982\u524d\u6587\u6240\u8ff0\uff0c\u901a\u8fc7\u6307\u5b9a\u6570\u636e\u7c7b\u578b\u53ef\u4ee5\u51cf\u5c11\u5185\u5b58\u4f7f\u7528\u3002\u4f8b\u5982\uff0c\u5c06\u6574\u6570\u5217\u6307\u5b9a\u4e3a<code>int32<\/code>\u6216<code>int64<\/code>\uff0c\u5c06\u6d6e\u70b9\u6570\u5217\u6307\u5b9a\u4e3a<code>float32<\/code>\u6216<code>float64<\/code>\u3002<\/p>\n<\/p>\n<p><h4>2\u3001\u4f7f\u7528\u9002\u5f53\u7684\u7d22\u5f15<\/h4>\n<\/p>\n<p><p>\u5728\u8bfb\u53d6\u5927\u6570\u636e\u96c6\u65f6\uff0c\u53ef\u4ee5\u901a\u8fc7\u8bbe\u7f6e\u7d22\u5f15\u6765\u52a0\u901f\u6570\u636e\u5904\u7406\u3002\u4f8b\u5982\uff0c\u53ef\u4ee5\u5728\u8bfb\u53d6CSV\u6587\u4ef6\u65f6\u6307\u5b9a\u67d0\u5217\u4e3a\u7d22\u5f15\u5217\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">df = pd.read_csv(&#39;large_file.csv&#39;, index_col=&#39;id&#39;)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h4>3\u3001\u4f7f\u7528\u591a\u7ebf\u7a0b\u6216\u591a\u8fdb\u7a0b<\/h4>\n<\/p>\n<p><p>\u5728\u5904\u7406\u5927\u6570\u636e\u96c6\u65f6\uff0c\u53ef\u4ee5\u4f7f\u7528\u591a\u7ebf\u7a0b\u6216\u591a\u8fdb\u7a0b\u6765\u52a0\u901f\u6570\u636e\u5904\u7406\u3002\u4f8b\u5982\uff0c\u53ef\u4ee5\u4f7f\u7528<code>concurrent.futures<\/code>\u6a21\u5757\u5b9e\u73b0\u591a\u7ebf\u7a0b\u8bfb\u53d6\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import pandas as pd<\/p>\n<p>from concurrent.futures import ThreadPoolExecutor<\/p>\n<p>def read_chunk(start, end):<\/p>\n<p>    return pd.read_csv(&#39;large_file.csv&#39;, skiprows=start, nrows=end-start)<\/p>\n<p>chunk_size = 100000<\/p>\n<p>chunks = [(i, i + chunk_size) for i in range(0, 2000000, chunk_size)]<\/p>\n<p>with ThreadPoolExecutor() as executor:<\/p>\n<p>    results = executor.map(lambda args: read_chunk(*args), chunks)<\/p>\n<p>df = pd.concat(results)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h4>4\u3001\u4f7f\u7528\u5185\u5b58\u6620\u5c04\u6587\u4ef6<\/h4>\n<\/p>\n<p><p>\u5185\u5b58\u6620\u5c04\u6587\u4ef6\uff08memory-mapped file\uff09\u662f\u4e00\u79cd\u5c06\u6587\u4ef6\u5185\u5bb9\u6620\u5c04\u5230\u5185\u5b58\u7684\u6280\u672f\uff0c\u53ef\u4ee5\u6709\u6548\u51cf\u5c11\u5185\u5b58\u4f7f\u7528\u3002Pandas\u63d0\u4f9b\u4e86<code>read_csv<\/code>\u7684<code>memory_map<\/code>\u53c2\u6570\uff0c\u53ef\u4ee5\u542f\u7528\u5185\u5b58\u6620\u5c04\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">df = pd.read_csv(&#39;large_file.csv&#39;, memory_map=True)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>\u4e94\u3001\u603b\u7ed3<\/h3>\n<\/p>\n<p><p>\u901a\u8fc7\u4f7f\u7528Pandas\u5e93\u3001Dask\u5e93\u3001csv\u6a21\u5757\u7b49\u5de5\u5177\uff0c\u53ef\u4ee5\u9ad8\u6548\u5730\u8bfb\u53d6\u548c\u5904\u7406\u5927\u89c4\u6a21\u7684CSV\u6570\u636e\u3002<strong>\u5728\u5b9e\u9645\u5e94\u7528\u4e2d\uff0c\u6839\u636e\u6570\u636e\u89c4\u6a21\u548c\u5177\u4f53\u9700\u6c42\u9009\u62e9\u5408\u9002\u7684\u65b9\u6cd5\u548c\u4f18\u5316\u6280\u5de7\uff0c\u53ef\u4ee5\u663e\u8457\u63d0\u5347\u6570\u636e\u5904\u7406\u6548\u7387\u3002<\/strong><\/p>\n<\/p>\n<h2><strong>\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n<p> <strong>\u5982\u4f55\u5728Python\u4e2d\u9ad8\u6548\u8bfb\u53d6\u5927\u578bCSV\u6587\u4ef6\uff1f<\/strong><br \/>\u5728\u5904\u7406200\u4e07\u884c\u7684CSV\u6587\u4ef6\u65f6\uff0c\u53ef\u4ee5\u4f7f\u7528<code>pandas<\/code>\u5e93\u4e2d\u7684<code>read_csv()<\/code>\u51fd\u6570\u3002\u4e3a\u4e86\u63d0\u9ad8\u8bfb\u53d6\u6548\u7387\uff0c\u5efa\u8bae\u8bbe\u7f6e\u9002\u5f53\u7684\u53c2\u6570\uff0c\u4f8b\u5982<code>chunksize<\/code>\uff0c\u4ee5\u5206\u5757\u8bfb\u53d6\u6570\u636e\u3002\u6b64\u5916\uff0c\u53ef\u4ee5\u6307\u5b9a<code>usecols<\/code>\u53c2\u6570\u6765\u4ec5\u8bfb\u53d6\u6240\u9700\u7684\u5217\uff0c\u51cf\u5c11\u5185\u5b58\u5360\u7528\u3002<\/p>\n<p><strong>\u4f7f\u7528Python\u8bfb\u53d6CSV\u6587\u4ef6\u65f6\uff0c\u5982\u4f55\u5904\u7406\u5185\u5b58\u95ee\u9898\uff1f<\/strong><br \/>\u5904\u7406\u5927\u578bCSV\u6587\u4ef6\u65f6\uff0c\u5185\u5b58\u95ee\u9898\u53ef\u80fd\u4f1a\u5f71\u54cd\u6027\u80fd\u3002\u53ef\u4ee5\u901a\u8fc7\u4ee5\u4e0b\u65b9\u5f0f\u6765\u4f18\u5316\u5185\u5b58\u4f7f\u7528\uff1a\u4f7f\u7528<code>dtype<\/code>\u53c2\u6570\u9884\u8bbe\u6570\u636e\u7c7b\u578b\uff0c\u907f\u514d\u9ed8\u8ba4\u7684\u7c7b\u578b\u63a8\u65ad\uff1b\u5206\u5757\u8bfb\u53d6\u6570\u636e\uff0c\u4f7f\u7528<code>chunksize<\/code>\u53c2\u6570\u9010\u5757\u5904\u7406\uff1b\u6216\u8003\u8651\u5c06\u6570\u636e\u8f6c\u6362\u4e3a\u5176\u4ed6\u683c\u5f0f\uff08\u5982Parquet\uff09\uff0c\u4ee5\u51cf\u5c11\u5185\u5b58\u5360\u7528\u3002<\/p>\n<p><strong>\u8bfb\u53d6CSV\u6587\u4ef6\u540e\uff0c\u5982\u4f55\u5bf9\u6570\u636e\u8fdb\u884c\u57fa\u672c\u5206\u6790\uff1f<\/strong><br \/>\u5728\u4f7f\u7528<code>pandas<\/code>\u8bfb\u53d6CSV\u6587\u4ef6\u540e\uff0c\u53ef\u4ee5\u5229\u7528DataFrame\u7684\u591a\u79cd\u65b9\u6cd5\u8fdb\u884c\u57fa\u672c\u5206\u6790\u3002\u4f8b\u5982\uff0c\u53ef\u4ee5\u4f7f\u7528<code>df.describe()<\/code>\u83b7\u53d6\u6570\u636e\u7684\u7edf\u8ba1\u4fe1\u606f\uff0c<code>df.info()<\/code>\u67e5\u770b\u6570\u636e\u7c7b\u578b\u548c\u7f3a\u5931\u503c\u60c5\u51b5\uff0c<code>df.groupby()<\/code>\u8fdb\u884c\u5206\u7ec4\u6c47\u603b\u3002\u901a\u8fc7\u8fd9\u4e9b\u65b9\u6cd5\uff0c\u7528\u6237\u53ef\u4ee5\u5feb\u901f\u4e86\u89e3\u6570\u636e\u7279\u5f81\u5e76\u8fdb\u884c\u8fdb\u4e00\u6b65\u7684\u6570\u636e\u5904\u7406\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"Python\u8bfb\u5165CSV\u6570\u636e200W\u7684\u6838\u5fc3\u65b9\u6cd5\u6709\uff1a\u4f7f\u7528Pandas\u5e93\u3001\u4f7f\u7528Dask\u5e93\u3001\u4f7f\u7528csv\u6a21\u5757\u3002 \u5728\u8fd9\u4e9b\u65b9 [&hellip;]","protected":false},"author":3,"featured_media":1089376,"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\/1089372"}],"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=1089372"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1089372\/revisions"}],"predecessor-version":[{"id":1089378,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1089372\/revisions\/1089378"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/1089376"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=1089372"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=1089372"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=1089372"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}