{"id":1133059,"date":"2025-01-08T21:02:57","date_gmt":"2025-01-08T13:02:57","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1133059.html"},"modified":"2025-01-08T21:02:59","modified_gmt":"2025-01-08T13:02:59","slug":"python%e5%a6%82%e4%bd%95%e4%b8%80%e8%a1%8c%e4%b8%80%e8%a1%8c%e5%86%99%e5%85%a5csv","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/1133059.html","title":{"rendered":"python\u5982\u4f55\u4e00\u884c\u4e00\u884c\u5199\u5165csv"},"content":{"rendered":"

\"python\u5982\u4f55\u4e00\u884c\u4e00\u884c\u5199\u5165csv\"<\/p>\n

Python\u4e00\u884c\u4e00\u884c\u5199\u5165CSV\u7684\u65b9\u6cd5\u6709\u591a\u79cd\uff0c\u4e3b\u8981\u5305\u62ec\uff1a\u4f7f\u7528csv.writer\u3001DictWriter\u3001pandas\u5e93\u3002<\/strong> \u5728\u5177\u4f53\u64cd\u4f5c\u4e2d\uff0c\u6700\u5e38\u7528\u7684\u662f\u4f7f\u7528csv.writer\u6765\u9010\u884c\u5199\u5165CSV\u6587\u4ef6\u3002csv.writer\u529f\u80fd\u5f3a\u5927\uff0c\u63d0\u4f9b\u4e86\u7b80\u6d01\u7684\u63a5\u53e3\uff0c\u53ef\u4ee5\u65b9\u4fbf\u5730\u8fdb\u884c\u4e00\u884c\u4e00\u884c\u7684\u5199\u5165\u64cd\u4f5c\u3002<\/p>\n<\/p>\n

\u4e00\u3001\u4f7f\u7528csv.writer\u9010\u884c\u5199\u5165CSV<\/h3>\n<\/p>\n

\u4f7f\u7528csv.writer\u662f\u5199\u5165CSV\u6587\u4ef6\u7684\u6700\u57fa\u672c\u65b9\u5f0f\u4e4b\u4e00\u3002csv.writer\u63d0\u4f9b\u4e86\u4e00\u4e2awriterow<\/code>\u65b9\u6cd5\uff0c\u53ef\u4ee5\u5c06\u4e00\u884c\u6570\u636e\u5199\u5165CSV\u6587\u4ef6\u4e2d\u3002<\/p>\n<\/p>\n

1. \u5bfc\u5165CSV\u6a21\u5757<\/h4>\n<\/p>\n

\u5728\u5f00\u59cb\u5199\u5165CSV\u6587\u4ef6\u4e4b\u524d\uff0c\u9700\u8981\u5148\u5bfc\u5165Python\u5185\u7f6e\u7684csv\u6a21\u5757\u3002\u8fd9\u4e2a\u6a21\u5757\u63d0\u4f9b\u4e86\u5404\u79cd\u529f\u80fd\u6765\u5904\u7406CSV\u6587\u4ef6\u7684\u8bfb\u5199\u64cd\u4f5c\u3002<\/p>\n<\/p>\n

import csv<\/p>\n
<\/code><\/pre>\n<\/p>\n
2. \u6253\u5f00CSV\u6587\u4ef6<\/h4>\n<\/p>\n
\u4f7f\u7528open<\/code>\u51fd\u6570\u6253\u5f00\u4e00\u4e2aCSV\u6587\u4ef6\u3002\u5982\u679c\u6587\u4ef6\u4e0d\u5b58\u5728\uff0copen<\/code>\u51fd\u6570\u4f1a\u81ea\u52a8\u521b\u5efa\u4e00\u4e2a\u65b0\u6587\u4ef6\u3002\u9700\u8981\u6ce8\u610f\u7684\u662f\uff0copen<\/code>\u51fd\u6570\u7684\u7b2c\u4e8c\u4e2a\u53c2\u6570\u662f\u6587\u4ef6\u7684\u6253\u5f00\u6a21\u5f0f\u3002\u5bf9\u4e8e\u5199\u5165\u64cd\u4f5c\uff0c\u901a\u5e38\u4f7f\u7528'w'<\/code>\uff08\u5199\u5165\u6a21\u5f0f\uff09\u6216'a'<\/code>\uff08\u8ffd\u52a0\u6a21\u5f0f\uff09\u3002<\/p>\n<\/p>\n
with open('output.csv', mode='w', newline='') as file:<\/p>\n
    writer = csv.writer(file)<\/p>\n
<\/code><\/pre>\n<\/p>\n
3. \u5199\u5165\u8868\u5934<\/h4>\n<\/p>\n
\u5982\u679c\u9700\u8981\u5199\u5165\u8868\u5934\uff0c\u53ef\u4ee5\u901a\u8fc7writerow<\/code>\u65b9\u6cd5\u5c06\u8868\u5934\u5199\u5165CSV\u6587\u4ef6\u4e2d\u3002\u8868\u5934\u901a\u5e38\u662f\u4e00\u4e2a\u5305\u542b\u5217\u540d\u79f0\u7684\u5217\u8868\u3002<\/p>\n<\/p>\n
    header = ['Name', 'Age', 'City']<\/p>\n
    writer.writerow(header)<\/p>\n
<\/code><\/pre>\n<\/p>\n
4. \u5199\u5165\u6570\u636e\u884c<\/h4>\n<\/p>\n
\u63a5\u4e0b\u6765\uff0c\u53ef\u4ee5\u4f7f\u7528writerow<\/code>\u65b9\u6cd5\u9010\u884c\u5199\u5165\u6570\u636e\u3002\u6bcf\u884c\u6570\u636e\u901a\u5e38\u662f\u4e00\u4e2a\u5217\u8868\uff0c\u5217\u8868\u4e2d\u7684\u6bcf\u4e2a\u5143\u7d20\u5bf9\u5e94CSV\u6587\u4ef6\u4e2d\u7684\u4e00\u4e2a\u5b57\u6bb5\u3002<\/p>\n<\/p>\n
    data = [<\/p>\n
        ['Alice', 30, 'New York'],<\/p>\n
        ['Bob', 25, 'Los Angeles'],<\/p>\n
        ['Charlie', 35, 'Chicago']<\/p>\n
    ]<\/p>\n
    for row in data:<\/p>\n
        writer.writerow(row)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e8c\u3001\u4f7f\u7528DictWriter\u9010\u884c\u5199\u5165CSV<\/h3>\n<\/p>\n
\u9664\u4e86csv.writer\u4e4b\u5916\uff0ccsv\u6a21\u5757\u8fd8\u63d0\u4f9b\u4e86DictWriter\u7c7b\uff0c\u5b83\u5141\u8bb8\u4f7f\u7528\u5b57\u5178\u6765\u5199\u5165CSV\u6587\u4ef6\u3002DictWriter\u7c7b\u7684\u4f18\u52bf\u5728\u4e8e\u53ef\u4ee5\u66f4\u65b9\u4fbf\u5730\u5904\u7406\u5177\u6709\u590d\u6742\u7ed3\u6784\u7684\u6570\u636e\u3002<\/p>\n<\/p>\n
1. \u5bfc\u5165CSV\u6a21\u5757<\/h4>\n<\/p>\n
\u548c\u4f7f\u7528csv.writer\u4e00\u6837\uff0c\u9700\u8981\u5148\u5bfc\u5165csv\u6a21\u5757\u3002<\/p>\n<\/p>\n
import csv<\/p>\n
<\/code><\/pre>\n<\/p>\n
2. \u6253\u5f00CSV\u6587\u4ef6<\/h4>\n<\/p>\n
\u4f7f\u7528open<\/code>\u51fd\u6570\u6253\u5f00CSV\u6587\u4ef6\uff0c\u5e76\u521b\u5efaDictWriter\u5bf9\u8c61\u3002DictWriter\u5bf9\u8c61\u9700\u8981\u4e00\u4e2a\u5b57\u6bb5\u540d\u79f0\u5217\u8868\uff0c\u8fd9\u4e2a\u5217\u8868\u5c06\u7528\u4f5cCSV\u6587\u4ef6\u7684\u8868\u5934\u3002<\/p>\n<\/p>\n
with open('output.csv', mode='w', newline='') as file:<\/p>\n
    fieldnames = ['Name', 'Age', 'City']<\/p>\n
    writer = csv.DictWriter(file, fieldnames=fieldnames)<\/p>\n
<\/code><\/pre>\n<\/p>\n
3. \u5199\u5165\u8868\u5934<\/h4>\n<\/p>\n
\u4f7f\u7528writeheader<\/code>\u65b9\u6cd5\u5c06\u5b57\u6bb5\u540d\u79f0\u5217\u8868\u5199\u5165CSV\u6587\u4ef6\u4e2d\uff0c\u4f5c\u4e3a\u8868\u5934\u3002<\/p>\n<\/p>\n
    writer.writeheader()<\/p>\n
<\/code><\/pre>\n<\/p>\n
4. \u5199\u5165\u6570\u636e\u884c<\/h4>\n<\/p>\n
\u63a5\u4e0b\u6765\uff0c\u53ef\u4ee5\u4f7f\u7528writerow<\/code>\u65b9\u6cd5\u9010\u884c\u5199\u5165\u6570\u636e\u3002\u6bcf\u884c\u6570\u636e\u662f\u4e00\u4e2a\u5b57\u5178\uff0c\u5b57\u5178\u7684\u952e\u5bf9\u5e94\u5b57\u6bb5\u540d\u79f0\u3002<\/p>\n<\/p>\n
    data = [<\/p>\n
        {'Name': 'Alice', 'Age': 30, 'City': 'New York'},<\/p>\n
        {'Name': 'Bob', 'Age': 25, 'City': 'Los Angeles'},<\/p>\n
        {'Name': 'Charlie', 'Age': 35, 'City': 'Chicago'}<\/p>\n
    ]<\/p>\n
    for row in data:<\/p>\n
        writer.writerow(row)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e09\u3001\u4f7f\u7528pandas\u9010\u884c\u5199\u5165CSV<\/h3>\n<\/p>\n
pandas\u662f\u4e00\u4e2a\u529f\u80fd\u5f3a\u5927\u7684\u6570\u636e\u5904\u7406\u5e93\uff0c\u5b83\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u529f\u80fd\u6765\u5904\u7406\u5404\u79cd\u6570\u636e\u64cd\u4f5c\u3002\u4f7f\u7528pandas\u53ef\u4ee5\u66f4\u65b9\u4fbf\u5730\u5904\u7406\u548c\u5199\u5165CSV\u6587\u4ef6\u3002<\/p>\n<\/p>\n
1. \u5bfc\u5165pandas\u6a21\u5757<\/h4>\n<\/p>\n
\u9996\u5148\uff0c\u9700\u8981\u5bfc\u5165pandas\u6a21\u5757\u3002\u5982\u679c\u6ca1\u6709\u5b89\u88c5pandas\uff0c\u53ef\u4ee5\u4f7f\u7528pip install pandas<\/code>\u547d\u4ee4\u8fdb\u884c\u5b89\u88c5\u3002<\/p>\n<\/p>\n
import pandas as pd<\/p>\n
<\/code><\/pre>\n<\/p>\n
2. \u521b\u5efaDataFrame\u5bf9\u8c61<\/h4>\n<\/p>\n
\u5c06\u6570\u636e\u8f6c\u6362\u4e3apandas\u7684DataFrame\u5bf9\u8c61\u3002DataFrame\u662fpandas\u4e2d\u6700\u5e38\u7528\u7684\u6570\u636e\u7ed3\u6784\u4e4b\u4e00\uff0c\u5b83\u7c7b\u4f3c\u4e8e\u8868\u683c\uff0c\u53ef\u4ee5\u65b9\u4fbf\u5730\u8fdb\u884c\u5404\u79cd\u6570\u636e\u64cd\u4f5c\u3002<\/p>\n<\/p>\n
data = {<\/p>\n
    'Name': ['Alice', 'Bob', 'Charlie'],<\/p>\n
    'Age': [30, 25, 35],<\/p>\n
    'City': ['New York', 'Los Angeles', 'Chicago']<\/p>\n
}<\/p>\n
df = pd.DataFrame(data)<\/p>\n
<\/code><\/pre>\n<\/p>\n
3. \u5199\u5165CSV\u6587\u4ef6<\/h4>\n<\/p>\n
\u4f7f\u7528DataFrame\u5bf9\u8c61\u7684to_csv<\/code>\u65b9\u6cd5\u5c06\u6570\u636e\u5199\u5165CSV\u6587\u4ef6\u3002\u9700\u8981\u6ce8\u610f\u7684\u662f\uff0cto_csv<\/code>\u65b9\u6cd5\u7684\u9ed8\u8ba4\u884c\u4e3a\u662f\u8986\u76d6\u539f\u6709\u6587\u4ef6\uff0c\u5982\u679c\u9700\u8981\u8ffd\u52a0\u6570\u636e\uff0c\u53ef\u4ee5\u4f7f\u7528mode='a'<\/code>\u53c2\u6570\u3002<\/p>\n<\/p>\n
df.to_csv('output.csv', index=False)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u56db\u3001\u5904\u7406\u7279\u6b8a\u60c5\u51b5<\/h3>\n<\/p>\n
\u5728\u5b9e\u9645\u64cd\u4f5c\u4e2d\uff0c\u53ef\u80fd\u4f1a\u9047\u5230\u4e00\u4e9b\u7279\u6b8a\u60c5\u51b5\uff0c\u4f8b\u5982\u5904\u7406\u5927\u6570\u636e\u96c6\u3001\u5904\u7406\u7279\u6b8a\u5b57\u7b26\u3001\u5904\u7406\u7a7a\u503c\u7b49\u3002\u4e0b\u9762\u5c06\u4ecb\u7ecd\u4e00\u4e9b\u5e38\u89c1\u7684\u5904\u7406\u65b9\u6cd5\u3002<\/p>\n<\/p>\n
1. \u5904\u7406\u5927\u6570\u636e\u96c6<\/h4>\n<\/p>\n
\u5bf9\u4e8e\u5927\u6570\u636e\u96c6\uff0c\u53ef\u4ee5\u4f7f\u7528\u5206\u5757\u5199\u5165\u7684\u65b9\u6cd5\u3002\u5206\u5757\u5199\u5165\u53ef\u4ee5\u907f\u514d\u4e00\u6b21\u6027\u52a0\u8f7d\u5927\u91cf\u6570\u636e\u5230\u5185\u5b58\u4e2d\uff0c\u4ece\u800c\u63d0\u9ad8\u5904\u7406\u6548\u7387\u3002<\/p>\n<\/p>\n
import pandas as pd<\/p>\n
chunksize = 1000  # \u6bcf\u6b21\u5904\u74061000\u884c\u6570\u636e<\/p>\n
for chunk in pd.read_csv('input.csv', chunksize=chunksize):<\/p>\n
    chunk.to_csv('output.csv', mode='a', index=False, header=False)<\/p>\n
<\/code><\/pre>\n<\/p>\n
2. \u5904\u7406\u7279\u6b8a\u5b57\u7b26<\/h4>\n<\/p>\n
\u5bf9\u4e8e\u5305\u542b\u7279\u6b8a\u5b57\u7b26\u7684\u6570\u636e\uff0c\u53ef\u4ee5\u4f7f\u7528quotechar<\/code>\u53c2\u6570\u6765\u6307\u5b9a\u5f15\u7528\u5b57\u7b26\uff0c\u4ece\u800c\u907f\u514d\u7279\u6b8a\u5b57\u7b26\u5bfc\u81f4\u7684\u89e3\u6790\u9519\u8bef\u3002<\/p>\n<\/p>\n
import csv<\/p>\n
with open('output.csv', mode='w', newline='') as file:<\/p>\n
    writer = csv.writer(file, quotechar='"', quoting=csv.QUOTE_MINIMAL)<\/p>\n
    writer.writerow(['Name', 'Age', 'City'])<\/p>\n
    writer.writerow(['Alice', 30, 'New York'])<\/p>\n
    writer.writerow(['Bob', 25, 'Los Angeles'])<\/p>\n
    writer.writerow(['Charlie', 35, 'Chicago'])<\/p>\n
<\/code><\/pre>\n<\/p>\n
3. \u5904\u7406\u7a7a\u503c<\/h4>\n<\/p>\n
\u5bf9\u4e8e\u5305\u542b\u7a7a\u503c\u7684\u6570\u636e\uff0c\u53ef\u4ee5\u4f7f\u7528na_rep<\/code>\u53c2\u6570\u6765\u6307\u5b9a\u7a7a\u503c\u7684\u8868\u793a\u65b9\u5f0f\u3002<\/p>\n<\/p>\n
import pandas as pd<\/p>\n
data = {<\/p>\n
    'Name': ['Alice', 'Bob', None],<\/p>\n
    'Age': [30, None, 35],<\/p>\n
    'City': ['New York', 'Los Angeles', 'Chicago']<\/p>\n
}<\/p>\n
df = pd.DataFrame(data)<\/p>\n
df.to_csv('output.csv', index=False, na_rep='NULL')<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e94\u3001\u603b\u7ed3<\/h3>\n<\/p>\n
Python\u63d0\u4f9b\u4e86\u591a\u79cd\u65b9\u6cd5\u6765\u9010\u884c\u5199\u5165CSV\u6587\u4ef6\uff0c\u5305\u62ec\u4f7f\u7528csv.writer\u3001DictWriter\u3001pandas\u5e93\u7b49\u3002\u6bcf\u79cd\u65b9\u6cd5\u90fd\u6709\u5176\u72ec\u7279\u7684\u4f18\u52bf\u548c\u9002\u7528\u573a\u666f\u3002\u5728\u5b9e\u9645\u64cd\u4f5c\u4e2d\uff0c\u53ef\u4ee5\u6839\u636e\u5177\u4f53\u9700\u6c42\u9009\u62e9\u5408\u9002\u7684\u65b9\u6cd5\u3002\u540c\u65f6\uff0c\u5728\u5904\u7406\u5927\u6570\u636e\u96c6\u3001\u7279\u6b8a\u5b57\u7b26\u548c\u7a7a\u503c\u65f6\uff0c\u53ef\u4ee5\u4f7f\u7528\u4e00\u4e9b\u7279\u6b8a\u7684\u53c2\u6570\u548c\u65b9\u6cd5\u6765\u63d0\u9ad8\u5904\u7406\u6548\u7387\u548c\u51c6\u786e\u6027\u3002\u901a\u8fc7\u7075\u6d3b\u8fd0\u7528\u8fd9\u4e9b\u65b9\u6cd5\uff0c\u53ef\u4ee5\u66f4\u9ad8\u6548\u5730\u8fdb\u884cCSV\u6587\u4ef6\u7684\u8bfb\u5199\u64cd\u4f5c\u3002<\/p>\n<\/p>\n
\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n
 \u5982\u4f55\u4f7f\u7528Python\u9010\u884c\u5199\u5165CSV\u6587\u4ef6\uff1f<\/strong>
\u5728Python\u4e2d\uff0c\u53ef\u4ee5\u4f7f\u7528\u5185\u7f6e\u7684csv<\/code>\u6a21\u5757\u6765\u9010\u884c\u5199\u5165CSV\u6587\u4ef6\u3002\u53ef\u4ee5\u521b\u5efa\u4e00\u4e2acsv.writer<\/code>\u5bf9\u8c61\uff0c\u5e76\u4f7f\u7528writerow()<\/code>\u65b9\u6cd5\u5c06\u6bcf\u4e00\u884c\u6570\u636e\u5199\u5165\u6587\u4ef6\u3002\u793a\u4f8b\u4ee3\u7801\u5982\u4e0b\uff1a<\/p>\n
import csv\n\ndata = [\n    ['name', 'age', 'city'],\n    ['Alice', 30, 'New York'],\n    ['Bob', 25, 'Los Angeles'],\n]\n\nwith open('output.csv', mode='w', newline='') as file:\n    writer = csv.writer(file)\n    for row in data:\n        writer.writerow(row)\n<\/code><\/pre>\n
\u5728\u5199\u5165CSV\u6587\u4ef6\u65f6\uff0c\u5982\u4f55\u5904\u7406\u7279\u6b8a\u5b57\u7b26\uff1f<\/strong>
\u5728\u5199\u5165CSV\u6587\u4ef6\u65f6\uff0c\u53ef\u80fd\u4f1a\u9047\u5230\u7279\u6b8a\u5b57\u7b26\uff08\u5982\u9017\u53f7\u3001\u5f15\u53f7\u7b49\uff09\u3002\u53ef\u4ee5\u901a\u8fc7\u8bbe\u7f6equotechar<\/code>\u548cquoting<\/code>\u53c2\u6570\u6765\u5904\u7406\u8fd9\u4e9b\u5b57\u7b26\u3002\u4f8b\u5982\uff0c\u4f7f\u7528csv.QUOTE_MINIMAL<\/code>\u9009\u9879\u5c06\u53ea\u6709\u5305\u542b\u7279\u6b8a\u5b57\u7b26\u7684\u5b57\u6bb5\u7528\u5f15\u53f7\u62ec\u8d77\u6765\uff0c\u786e\u4fdd\u6570\u636e\u7684\u6b63\u786e\u6027\u3002<\/p>\n
\u5982\u4f55\u5728Python\u4e2d\u8ffd\u52a0\u6570\u636e\u5230\u73b0\u6709\u7684CSV\u6587\u4ef6\uff1f<\/strong>
\u4e3a\u4e86\u5728\u73b0\u6709\u7684CSV\u6587\u4ef6\u4e2d\u8ffd\u52a0\u6570\u636e\uff0c\u53ef\u4ee5\u5c06\u6253\u5f00\u6587\u4ef6\u7684\u6a21\u5f0f\u8bbe\u7f6e\u4e3a'a'<\/code>\uff08\u8ffd\u52a0\u6a21\u5f0f\uff09\u3002\u4f7f\u7528csv.writer<\/code>\u5bf9\u8c61\u540e\uff0c\u53ef\u4ee5\u7ee7\u7eed\u4f7f\u7528writerow()<\/code>\u65b9\u6cd5\u6dfb\u52a0\u65b0\u884c\u3002\u793a\u4f8b\u4ee3\u7801\u5982\u4e0b\uff1a<\/p>\n
with open('output.csv', mode='a', newline='') as file:\n    writer = csv.writer(file)\n    writer.writerow(['Charlie', 28, 'Chicago'])\n<\/code><\/pre>\n
\u6709\u6ca1\u6709\u5176\u4ed6\u5e93\u53ef\u4ee5\u7528\u4e8e\u5199\u5165CSV\u6587\u4ef6\uff1f<\/strong>
\u9664\u4e86\u5185\u7f6e\u7684csv<\/code>\u6a21\u5757\uff0cPandas\u5e93\u4e5f\u662f\u4e00\u4e2a\u975e\u5e38\u5f3a\u5927\u7684\u5de5\u5177\uff0c\u53ef\u4ee5\u65b9\u4fbf\u5730\u5904\u7406CSV\u6587\u4ef6\u3002\u4f7f\u7528Pandas\u7684DataFrame.to_csv()<\/code>\u65b9\u6cd5\uff0c\u53ef\u4ee5\u8f7b\u677e\u5199\u5165\u548c\u8bfb\u53d6CSV\u6587\u4ef6\uff0c\u652f\u6301\u66f4\u591a\u7684\u6570\u636e\u5904\u7406\u529f\u80fd\u3002\u4f8b\u5982\uff1a<\/p>\n
import pandas as pd\n\ndf = pd.DataFrame(data, columns=['name', 'age', 'city'])\ndf.to_csv('output.csv', index=False)\n<\/code><\/pre>\n","protected":false},"excerpt":{"rendered":"Python\u4e00\u884c\u4e00\u884c\u5199\u5165CSV\u7684\u65b9\u6cd5\u6709\u591a\u79cd\uff0c\u4e3b\u8981\u5305\u62ec\uff1a\u4f7f\u7528csv.writer\u3001DictWriter\u3001pand […]","protected":false},"author":3,"featured_media":1133068,"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\/1133059"}],"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=1133059"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1133059\/revisions"}],"predecessor-version":[{"id":1133071,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1133059\/revisions\/1133071"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/1133068"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=1133059"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=1133059"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=1133059"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}