{"id":1158692,"date":"2025-01-13T18:43:45","date_gmt":"2025-01-13T10:43:45","guid":{"rendered":""},"modified":"2025-01-13T18:43:48","modified_gmt":"2025-01-13T10:43:48","slug":"python-%e5%a6%82%e4%bd%95%e5%be%aa%e7%8e%af%e8%af%bb%e8%a1%a8","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1158692.html","title":{"rendered":"python \u5982\u4f55\u5faa\u73af\u8bfb\u8868"},"content":{"rendered":"

\"python<\/p>\n

Python \u5faa\u73af\u8bfb\u8868\u7684\u65b9\u6cd5\u6709\u591a\u79cd\uff0c\u5305\u62ec\u4f7f\u7528 pandas \u5e93\u3001csv \u5e93\u4ee5\u53ca openpyxl \u5e93\u7b49\u3002<\/strong> <\/p>\n<\/p>\n

\u5176\u4e2d\u6700\u5e38\u7528\u7684\u65b9\u5f0f\u662f\u4f7f\u7528 pandas \u5e93\u3002<\/strong><\/p>\n<\/p>\n

\u4f7f\u7528 pandas \u5e93<\/h3>\n<\/p>\n

pandas \u662f\u4e00\u4e2a\u5f3a\u5927\u7684\u6570\u636e\u5206\u6790\u5e93\uff0c\u63d0\u4f9b\u4e86\u8bb8\u591a\u4fbf\u6377\u7684\u6570\u636e\u5904\u7406\u529f\u80fd\u3002\u4ee5\u4e0b\u662f\u4f7f\u7528 pandas \u5e93\u5faa\u73af\u8bfb\u53d6\u8868\u683c\u7684\u793a\u4f8b\uff1a<\/p>\n<\/p>\n

import pandas as pd<\/p>\n
\u8bfb\u53d6\u8868\u683c\u6570\u636e<\/strong><\/h2>\n
df = pd.read_csv('example.csv')<\/p>\n
\u5faa\u73af\u8bfb\u53d6\u6bcf\u4e00\u884c<\/strong><\/h2>\n
for index, row in df.iterrows():<\/p>\n
    print(f'Index: {index}, Row: {row}')<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5728\u4e0a\u8ff0\u4ee3\u7801\u4e2d\uff0c\u6211\u4eec\u4f7f\u7528 pd.read_csv<\/code> \u65b9\u6cd5\u8bfb\u53d6 CSV \u6587\u4ef6\uff0c\u7136\u540e\u4f7f\u7528 df.iterrows()<\/code> \u65b9\u6cd5\u5faa\u73af\u8bfb\u53d6\u6bcf\u4e00\u884c\u3002<\/strong><\/p>\n<\/p>\n
\u4e00\u3001pandas\u5e93\u7684\u4f7f\u7528<\/h2>\n<\/p>\n
1\u3001\u8bfb\u53d6CSV\u6587\u4ef6<\/h3>\n<\/p>\n
pandas \u5e93\u63d0\u4f9b\u4e86 read_csv<\/code> \u51fd\u6570\u6765\u8bfb\u53d6 CSV \u6587\u4ef6\u3002 read_csv<\/code> \u51fd\u6570\u7684\u53c2\u6570\u53ef\u4ee5\u6839\u636e\u9700\u8981\u8fdb\u884c\u8c03\u6574\uff0c\u4f8b\u5982\u5206\u9694\u7b26\u3001\u7f16\u7801\u683c\u5f0f\u7b49\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u793a\u4f8b\uff1a<\/p>\n<\/p>\n
import pandas as pd<\/p>\n
\u8bfb\u53d6 CSV \u6587\u4ef6<\/strong><\/h2>\n
df = pd.read_csv('example.csv')<\/p>\n
\u6253\u5370\u6570\u636e<\/strong><\/h2>\n
print(df)<\/p>\n
<\/code><\/pre>\n<\/p>\n
2\u3001\u8bfb\u53d6Excel\u6587\u4ef6<\/h3>\n<\/p>\n
pandas \u5e93\u63d0\u4f9b\u4e86 read_excel<\/code> \u51fd\u6570\u6765\u8bfb\u53d6 Excel \u6587\u4ef6\u3002 read_excel<\/code> \u51fd\u6570\u7684\u53c2\u6570\u53ef\u4ee5\u6839\u636e\u9700\u8981\u8fdb\u884c\u8c03\u6574\uff0c\u4f8b\u5982\u6307\u5b9a\u5de5\u4f5c\u8868\u3001\u6570\u636e\u8303\u56f4\u7b49\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u793a\u4f8b\uff1a<\/p>\n<\/p>\n
import pandas as pd<\/p>\n
\u8bfb\u53d6 Excel \u6587\u4ef6<\/strong><\/h2>\n
df = pd.read_excel('example.xlsx', sheet_name='Sheet1')<\/p>\n
\u6253\u5370\u6570\u636e<\/strong><\/h2>\n
print(df)<\/p>\n
<\/code><\/pre>\n<\/p>\n
3\u3001\u5faa\u73af\u8bfb\u53d6\u8868\u683c\u6570\u636e<\/h3>\n<\/p>\n
\u5728\u8bfb\u53d6\u8868\u683c\u6570\u636e\u540e\uff0c\u53ef\u4ee5\u4f7f\u7528 pandas \u63d0\u4f9b\u7684 iterrows<\/code> \u6216 itertuples<\/code> \u65b9\u6cd5\u6765\u5faa\u73af\u8bfb\u53d6\u6bcf\u4e00\u884c\u6570\u636e\u3002\u8fd9\u4e24\u4e2a\u65b9\u6cd5\u7684\u533a\u522b\u5728\u4e8e iterrows<\/code> \u8fd4\u56de\u7684\u662f\u7d22\u5f15\u548c\u884c\u6570\u636e\uff0c\u800c itertuples<\/code> \u8fd4\u56de\u7684\u662f\u4e00\u4e2a\u547d\u540d\u5143\u7ec4\u3002\u4ee5\u4e0b\u662f\u793a\u4f8b\uff1a<\/p>\n<\/p>\n
import pandas as pd<\/p>\n
\u8bfb\u53d6 CSV \u6587\u4ef6<\/strong><\/h2>\n
df = pd.read_csv('example.csv')<\/p>\n
\u4f7f\u7528 iterrows \u65b9\u6cd5\u5faa\u73af\u8bfb\u53d6\u6bcf\u4e00\u884c\u6570\u636e<\/strong><\/h2>\n
for index, row in df.iterrows():<\/p>\n
    print(f'Index: {index}, Row: {row}')<\/p>\n
\u4f7f\u7528 itertuples \u65b9\u6cd5\u5faa\u73af\u8bfb\u53d6\u6bcf\u4e00\u884c\u6570\u636e<\/strong><\/h2>\n
for row in df.itertuples():<\/p>\n
    print(f'Row: {row}')<\/p>\n
<\/code><\/pre>\n<\/p>\n
4\u3001\u5904\u7406\u5927\u6570\u636e\u6587\u4ef6<\/h3>\n<\/p>\n
\u5bf9\u4e8e\u5927\u6570\u636e\u6587\u4ef6\uff0c\u76f4\u63a5\u8bfb\u53d6\u6574\u4e2a\u6587\u4ef6\u53ef\u80fd\u4f1a\u5360\u7528\u5927\u91cf\u5185\u5b58\u3002\u53ef\u4ee5\u4f7f\u7528 pandas \u63d0\u4f9b\u7684 chunksize<\/code> \u53c2\u6570\u6765\u5206\u5757\u8bfb\u53d6\u6587\u4ef6\uff0c\u6bcf\u6b21\u8bfb\u53d6\u6307\u5b9a\u6570\u91cf\u7684\u884c\u3002\u4ee5\u4e0b\u662f\u793a\u4f8b\uff1a<\/p>\n<\/p>\n
import pandas as pd<\/p>\n
\u5206\u5757\u8bfb\u53d6 CSV \u6587\u4ef6\uff0c\u6bcf\u6b21\u8bfb\u53d61000\u884c<\/strong><\/h2>\n
chunksize = 1000<\/p>\n
for chunk in pd.read_csv('example.csv', chunksize=chunksize):<\/p>\n
    for index, row in chunk.iterrows():<\/p>\n
        print(f'Index: {index}, Row: {row}')<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e8c\u3001csv \u5e93\u7684\u4f7f\u7528<\/h2>\n<\/p>\n
1\u3001\u8bfb\u53d6CSV\u6587\u4ef6<\/h3>\n<\/p>\n
csv \u5e93\u662f Python \u5185\u7f6e\u7684\u5e93\uff0c\u53ef\u4ee5\u7528\u6765\u5904\u7406 CSV \u6587\u4ef6\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u8bfb\u53d6 CSV \u6587\u4ef6\u7684\u793a\u4f8b\uff1a<\/p>\n<\/p>\n
import csv<\/p>\n
\u6253\u5f00 CSV \u6587\u4ef6<\/strong><\/h2>\n
with open('example.csv', mode='r', encoding='utf-8') as file:<\/p>\n
    reader = csv.reader(file)<\/p>\n
    # \u5faa\u73af\u8bfb\u53d6\u6bcf\u4e00\u884c\u6570\u636e<\/p>\n
    for row in reader:<\/p>\n
        print(row)<\/p>\n
<\/code><\/pre>\n<\/p>\n
2\u3001\u8bfb\u53d6\u5e26\u6709\u8868\u5934\u7684CSV\u6587\u4ef6<\/h3>\n<\/p>\n
\u5982\u679c CSV \u6587\u4ef6\u5e26\u6709\u8868\u5934\uff0c\u53ef\u4ee5\u4f7f\u7528 csv.DictReader<\/code> \u7c7b\u6765\u8bfb\u53d6\u6587\u4ef6\u3002 DictReader<\/code> \u7c7b\u4f1a\u5c06\u6bcf\u4e00\u884c\u6570\u636e\u8f6c\u6362\u4e3a\u4e00\u4e2a\u5b57\u5178\uff0c\u952e\u662f\u8868\u5934\uff0c\u503c\u662f\u5bf9\u5e94\u7684\u5217\u503c\u3002\u4ee5\u4e0b\u662f\u793a\u4f8b\uff1a<\/p>\n<\/p>\n
import csv<\/p>\n
\u6253\u5f00 CSV \u6587\u4ef6<\/strong><\/h2>\n
with open('example.csv', mode='r', encoding='utf-8') as file:<\/p>\n
    reader = csv.DictReader(file)<\/p>\n
    # \u5faa\u73af\u8bfb\u53d6\u6bcf\u4e00\u884c\u6570\u636e<\/p>\n
    for row in reader:<\/p>\n
        print(row)<\/p>\n
<\/code><\/pre>\n<\/p>\n
3\u3001\u5904\u7406\u5927\u6570\u636e\u6587\u4ef6<\/h3>\n<\/p>\n
\u4e0e pandas \u7c7b\u4f3c\uff0c\u5bf9\u4e8e\u5927\u6570\u636e\u6587\u4ef6\uff0c\u53ef\u4ee5\u5206\u5757\u8bfb\u53d6 CSV \u6587\u4ef6\u3002\u4ee5\u4e0b\u662f\u793a\u4f8b\uff1a<\/p>\n<\/p>\n
import csv<\/p>\n
\u6253\u5f00 CSV \u6587\u4ef6<\/strong><\/h2>\n
with open('example.csv', mode='r', encoding='utf-8') as file:<\/p>\n
    reader = csv.reader(file)<\/p>\n
    # \u5206\u5757\u8bfb\u53d6\u6587\u4ef6\uff0c\u6bcf\u6b21\u8bfb\u53d61000\u884c<\/p>\n
    chunk_size = 1000<\/p>\n
    chunk = []<\/p>\n
    for row in reader:<\/p>\n
        chunk.append(row)<\/p>\n
        if len(chunk) == chunk_size:<\/p>\n
            # \u5904\u7406\u5f53\u524d\u5757\u6570\u636e<\/p>\n
            for row in chunk:<\/p>\n
                print(row)<\/p>\n
            chunk = []<\/p>\n
    # \u5904\u7406\u5269\u4f59\u6570\u636e<\/p>\n
    if chunk:<\/p>\n
        for row in chunk:<\/p>\n
            print(row)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e09\u3001openpyxl \u5e93\u7684\u4f7f\u7528<\/h2>\n<\/p>\n
1\u3001\u8bfb\u53d6Excel\u6587\u4ef6<\/h3>\n<\/p>\n
openpyxl \u5e93\u662f\u4e00\u4e2a\u7528\u4e8e\u5904\u7406 Excel \u6587\u4ef6\u7684\u7b2c\u4e09\u65b9\u5e93\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u8bfb\u53d6 Excel \u6587\u4ef6\u7684\u793a\u4f8b\uff1a<\/p>\n<\/p>\n
from openpyxl import load_workbook<\/p>\n
\u6253\u5f00 Excel \u6587\u4ef6<\/strong><\/h2>\n
workbook = load_workbook(filename='example.xlsx')<\/p>\n
\u83b7\u53d6\u5de5\u4f5c\u8868<\/strong><\/h2>\n
sheet = workbook.active<\/p>\n
\u5faa\u73af\u8bfb\u53d6\u6bcf\u4e00\u884c\u6570\u636e<\/strong><\/h2>\n
for row in sheet.iter_rows(values_only=True):<\/p>\n
    print(row)<\/p>\n
<\/code><\/pre>\n<\/p>\n
2\u3001\u8bfb\u53d6\u6307\u5b9a\u5de5\u4f5c\u8868<\/h3>\n<\/p>\n
\u53ef\u4ee5\u901a\u8fc7\u5de5\u4f5c\u8868\u540d\u79f0\u83b7\u53d6\u6307\u5b9a\u7684\u5de5\u4f5c\u8868\u3002\u4ee5\u4e0b\u662f\u793a\u4f8b\uff1a<\/p>\n<\/p>\n
from openpyxl import load_workbook<\/p>\n
\u6253\u5f00 Excel \u6587\u4ef6<\/strong><\/h2>\n
workbook = load_workbook(filename='example.xlsx')<\/p>\n
\u83b7\u53d6\u6307\u5b9a\u5de5\u4f5c\u8868<\/strong><\/h2>\n
sheet = workbook['Sheet1']<\/p>\n
\u5faa\u73af\u8bfb\u53d6\u6bcf\u4e00\u884c\u6570\u636e<\/strong><\/h2>\n
for row in sheet.iter_rows(values_only=True):<\/p>\n
    print(row)<\/p>\n
<\/code><\/pre>\n<\/p>\n
3\u3001\u5904\u7406\u5927\u6570\u636e\u6587\u4ef6<\/h3>\n<\/p>\n
\u5bf9\u4e8e\u5927\u6570\u636e\u6587\u4ef6\uff0c\u53ef\u4ee5\u5206\u5757\u8bfb\u53d6 Excel \u6587\u4ef6\u3002\u7531\u4e8e openpyxl \u4e0d\u652f\u6301\u539f\u751f\u7684\u5206\u5757\u8bfb\u53d6\uff0c\u53ef\u4ee5\u901a\u8fc7\u624b\u52a8\u63a7\u5236\u8bfb\u53d6\u7684\u884c\u6570\u6765\u5b9e\u73b0\u5206\u5757\u8bfb\u53d6\u3002\u4ee5\u4e0b\u662f\u793a\u4f8b\uff1a<\/p>\n<\/p>\n
from openpyxl import load_workbook<\/p>\n
\u6253\u5f00 Excel \u6587\u4ef6<\/strong><\/h2>\n
workbook = load_workbook(filename='example.xlsx')<\/p>\n
\u83b7\u53d6\u5de5\u4f5c\u8868<\/strong><\/h2>\n
sheet = workbook.active<\/p>\n
\u5206\u5757\u8bfb\u53d6\u6587\u4ef6\uff0c\u6bcf\u6b21\u8bfb\u53d61000\u884c<\/strong><\/h2>\n
chunk_size = 1000<\/p>\n
rows = list(sheet.iter_rows(values_only=True))<\/p>\n
for i in range(0, len(rows), chunk_size):<\/p>\n
    chunk = rows[i:i+chunk_size]<\/p>\n
    for row in chunk:<\/p>\n
        print(row)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u56db\u3001\u7ed3\u8bba<\/h2>\n<\/p>\n
\u5728 Python \u4e2d\uff0c\u5faa\u73af\u8bfb\u53d6\u8868\u683c\u6570\u636e\u53ef\u4ee5\u4f7f\u7528\u591a\u79cd\u65b9\u6cd5\uff0c\u5305\u62ec pandas \u5e93\u3001csv \u5e93\u4ee5\u53ca openpyxl \u5e93\u7b49\u3002\u9009\u62e9\u54ea\u79cd\u65b9\u6cd5\u53d6\u51b3\u4e8e\u5177\u4f53\u9700\u6c42\u548c\u6587\u4ef6\u7c7b\u578b\u3002pandas \u5e93\u529f\u80fd\u5f3a\u5927\uff0c\u9002\u5408\u5904\u7406\u5927\u591a\u6570\u8868\u683c\u6570\u636e\uff0ccsv \u5e93\u662f Python \u5185\u7f6e\u7684\u5e93\uff0c\u9002\u5408\u5904\u7406\u7b80\u5355\u7684 CSV \u6587\u4ef6\uff0copenpyxl \u5e93\u9002\u5408\u5904\u7406 Excel \u6587\u4ef6\u3002<\/strong>\u5bf9\u4e8e\u5927\u6570\u636e\u6587\u4ef6\uff0c\u53ef\u4ee5\u4f7f\u7528\u5206\u5757\u8bfb\u53d6\u7684\u65b9\u6cd5\u6765\u51cf\u5c11\u5185\u5b58\u5360\u7528\u3002\u65e0\u8bba\u9009\u62e9\u54ea\u79cd\u65b9\u6cd5\uff0c\u638c\u63e1\u8fd9\u4e9b\u5de5\u5177\u548c\u6280\u5de7\u53ef\u4ee5\u5e2e\u52a9\u6211\u4eec\u66f4\u9ad8\u6548\u5730\u5904\u7406\u8868\u683c\u6570\u636e\u3002<\/p>\n<\/p>\n
\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n
 \u5982\u4f55\u5728Python\u4e2d\u6709\u6548\u5730\u5faa\u73af\u8bfb\u53d6\u8868\u683c\u6570\u636e\uff1f<\/strong>
\u5728Python\u4e2d\uff0c\u53ef\u4ee5\u4f7f\u7528\u591a\u79cd\u5e93\u6765\u5faa\u73af\u8bfb\u53d6\u8868\u683c\u6570\u636e\uff0c\u5982Pandas\u3001openpyxl\u7b49\u3002Pandas\u662f\u6700\u5e38\u7528\u7684\u5e93\uff0c\u5b83\u63d0\u4f9b\u4e86\u5f3a\u5927\u7684\u6570\u636e\u5904\u7406\u529f\u80fd\u3002\u60a8\u53ef\u4ee5\u4f7f\u7528pd.read_csv()<\/code>\u8bfb\u53d6CSV\u6587\u4ef6\u6216pd.read_excel()<\/code>\u8bfb\u53d6Excel\u6587\u4ef6\u3002\u8bfb\u53d6\u540e\uff0c\u53ef\u4ee5\u4f7f\u7528DataFrame.iterrows()<\/code>\u65b9\u6cd5\u8fdb\u884c\u5faa\u73af\u904d\u5386\u6bcf\u4e00\u884c\u6570\u636e\uff0c\u4ece\u800c\u8fdb\u884c\u76f8\u5e94\u7684\u5904\u7406\u3002<\/p>\n
\u5728\u8bfb\u53d6\u8868\u683c\u6570\u636e\u65f6\uff0c\u6709\u54ea\u4e9b\u5e38\u89c1\u7684\u9519\u8bef\u9700\u8981\u907f\u514d\uff1f<\/strong>
\u5728\u8bfb\u53d6\u8868\u683c\u6570\u636e\u65f6\uff0c\u5e38\u89c1\u7684\u9519\u8bef\u5305\u62ec\u6587\u4ef6\u8def\u5f84\u9519\u8bef\u3001\u6587\u4ef6\u683c\u5f0f\u4e0d\u517c\u5bb9\u3001\u6570\u636e\u7c7b\u578b\u4e0d\u4e00\u81f4\u7b49\u3002\u786e\u4fdd\u6587\u4ef6\u8def\u5f84\u6b63\u786e\uff0c\u4e14\u6587\u4ef6\u683c\u5f0f\u4e0e\u6240\u7528\u7684\u8bfb\u53d6\u51fd\u6570\u5339\u914d\u975e\u5e38\u91cd\u8981\u3002\u6b64\u5916\uff0c\u53ef\u4ee5\u4f7f\u7528dtype<\/code>\u53c2\u6570\u6765\u6307\u5b9a\u5217\u7684\u6570\u636e\u7c7b\u578b\uff0c\u4ece\u800c\u907f\u514d\u7c7b\u578b\u4e0d\u4e00\u81f4\u7684\u95ee\u9898\u3002<\/p>\n
\u5982\u4f55\u63d0\u9ad8\u5faa\u73af\u8bfb\u53d6\u8868\u683c\u7684\u6027\u80fd\uff1f<\/strong>
\u8981\u63d0\u9ad8\u5faa\u73af\u8bfb\u53d6\u8868\u683c\u7684\u6027\u80fd\uff0c\u53ef\u4ee5\u8003\u8651\u4f7f\u7528DataFrame.itertuples()<\/code>\u4ee3\u66ffiterrows()<\/code>\uff0c\u56e0\u4e3a\u524d\u8005\u7684\u6027\u80fd\u66f4\u4f18\u3002\u6b64\u5916\uff0c\u5c3d\u91cf\u51cf\u5c11\u5728\u5faa\u73af\u5185\u7684\u8ba1\u7b97\uff0c\u5c06\u9700\u8981\u7684\u64cd\u4f5c\u63d0\u524d\u5904\u7406\u3002\u5bf9\u4e8e\u8f83\u5927\u7684\u6570\u636e\u96c6\uff0c\u4f7f\u7528\u5206\u5757\u8bfb\u53d6\u7684\u65b9\u6cd5\u4e5f\u662f\u4e00\u4e2a\u4e0d\u9519\u7684\u9009\u62e9\uff0c\u53ef\u4ee5\u901a\u8fc7chunksize<\/code>\u53c2\u6570\u6765\u5b9e\u73b0\u3002\u8fd9\u6837\u53ef\u4ee5\u6709\u6548\u5730\u51cf\u5c11\u5185\u5b58\u6d88\u8017\u5e76\u63d0\u9ad8\u5904\u7406\u901f\u5ea6\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"Python \u5faa\u73af\u8bfb\u8868\u7684\u65b9\u6cd5\u6709\u591a\u79cd\uff0c\u5305\u62ec\u4f7f\u7528 pandas \u5e93\u3001csv \u5e93\u4ee5\u53ca openpyxl \u5e93\u7b49\u3002 \u5176\u4e2d […]","protected":false},"author":3,"featured_media":1158698,"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\/1158692"}],"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=1158692"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1158692\/revisions"}],"predecessor-version":[{"id":1158699,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1158692\/revisions\/1158699"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/1158698"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=1158692"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=1158692"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=1158692"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}