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思路&代码参考微信公众号：Python与Excel之交 ，作者小刀

以知乎热搜《男子因太能吃被「自助」餐厅拉黑，餐厅此种行为合法吗？》为例

网页：男子因太能吃被「自助」餐厅拉黑，餐厅此种行为合法吗？ - 知乎

评论

进入浏览器的开发者模式

 评论往下拉就会自动生成下一页，会有新的数据包

真实的url

https://www.zhihu.com/api/v4/questions/499739058/answers?include=data%5B%2A%5D.is_normal%2Cadmin_closed_comment%2Creward_info%2Cis_collapsed%2Cannotation_action%2Cannotation_detail%2Ccollapse_reason%2Cis_sticky%2Ccollapsed_by%2Csuggest_edit%2Ccomment_count%2Ccan_comment%2Ccontent%2Ceditable_content%2Cattachment%2Cvoteup_count%2Creshipment_settings%2Ccomment_permission%2Ccreated_time%2Cupdated_time%2Creview_info%2Crelevant_info%2Cquestion%2Cexcerpt%2Cis_labeled%2Cpaid_info%2Cpaid_info_content%2Crelationship.is_authorized%2Cis_author%2Cvoting%2Cis_thanked%2Cis_nothelp%2Cis_recognized%3Bdata%5B%2A%5D.mark_infos%5B%2A%5D.url%3Bdata%5B%2A%5D.author.follower_count%2Cvip_info%2Cbadge%5B%2A%5D.topics%3Bdata%5B%2A%5D.settings.table_of_content.enabled&limit=5&offset=5&platform=desktop&sort_by=default

https://www.zhihu.com/api/v4/questions/499739058/answers?include=data%5B%2A%5D.is_normal%2Cadmin_closed_comment%2Creward_info%2Cis_collapsed%2Cannotation_action%2Cannotation_detail%2Ccollapse_reason%2Cis_sticky%2Ccollapsed_by%2Csuggest_edit%2Ccomment_count%2Ccan_comment%2Ccontent%2Ceditable_content%2Cattachment%2Cvoteup_count%2Creshipment_settings%2Ccomment_permission%2Ccreated_time%2Cupdated_time%2Creview_info%2Crelevant_info%2Cquestion%2Cexcerpt%2Cis_labeled%2Cpaid_info%2Cpaid_info_content%2Crelationship.is_authorized%2Cis_author%2Cvoting%2Cis_thanked%2Cis_nothelp%2Cis_recognized%3Bdata%5B%2A%5D.mark_infos%5B%2A%5D.url%3Bdata%5B%2A%5D.author.follower_count%2Cvip_info%2Cbadge%5B%2A%5D.topics%3Bdata%5B%2A%5D.settings.table_of_content.enabled&limit=5&offset=10&platform=desktop&sort_by=default

只有offset在变，由5到10 以5递增的规律

代码

import requests
import pandas as pd
import re
import time
import random

df = pd.DataFrame()
headers ={
    'user-agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/95.0.4638.54 Safari/537.36'
}

for page in range(0,25,5):
    url = f'https://www.zhihu.com/api/v4/questions/499739058/answers?include=data%5B%2A%5D.is_normal%2Cadmin_closed_comment%2Creward_info%2Cis_collapsed%2Cannotation_action%2Cannotation_detail%2Ccollapse_reason%2Cis_sticky%2Ccollapsed_by%2Csuggest_edit%2Ccomment_count%2Ccan_comment%2Ccontent%2Ceditable_content%2Cattachment%2Cvoteup_count%2Creshipment_settings%2Ccomment_permission%2Ccreated_time%2Cupdated_time%2Creview_info%2Crelevant_info%2Cquestion%2Cexcerpt%2Cis_labeled%2Cpaid_info%2Cpaid_info_content%2Crelationship.is_authorized%2Cis_author%2Cvoting%2Cis_thanked%2Cis_nothelp%2Cis_recognized%3Bdata%5B%2A%5D.mark_infos%5B%2A%5D.url%3Bdata%5B%2A%5D.author.follower_count%2Cvip_info%2Cbadge%5B%2A%5D.topics%3Bdata%5B%2A%5D.settings.table_of_content.enabled&limit=5&offset={page}&platform=desktop&sort_by=default'
    response = requests.get(url,headers=headers).json()
    data = response['data']
    for list_ in data:
        name = list_['author']['name']  # 知乎作者
        id_ = list_['author']['id']  # 作者id
        created_time = time.strftime("%Y-%m-%d %H:%M:%S", time.localtime(list_['created_time'] )) # 回答时间
        voteup_count = list_['voteup_count']  # 赞同数
        comment_count = list_['comment_count']  # 底下评论数
        content = list_['content']  # 回答内容
        content = ''.join(re.findall("[\u3002\uff1b\uff0c\uff1a\u201c\u201d\uff08\uff09\u3001\uff1f\u300a\u300b\u4e00-\u9fa5]", content))  # 正则表达式提取
        dataFrame = pd.DataFrame(
            {'知乎作者': [name], '作者id': [id_], '回答时间': [created_time], '赞同数': [voteup_count], '底下评论数': [comment_count],
             '回答内容': [content]})
        df = pd.concat([df, dataFrame])
        time.sleep(random.uniform(2,3))