Python如何爬取微信公众号文章和评论(基于 Fiddler 抓包分析)
背景说明
感觉微信公众号算得是比较难爬的平台之一，不过一番折腾之后还是小有收获的。没有用Scrapy(估计爬太快也有反爬限制)，但后面会开始整理写一些实战出来。简单介绍下本次的开发环境：
- python3
- requests
- psycopg2 (操作postgres数据库)
抓包分析
本次实战对抓取的公众号没有限制，但不同公众号每次抓取之前都要进行分析。打开Fiddler，将手机配置好相关代理，为避免干扰过多，这里给Fiddler加个过滤规则，只需要指定微信域名mp.weixin.qq.com就好：
Fiddler配置Filter规则
平时关注的公众号也比较多，本次实战以“36氪”公众号为例，继续往下看：
“36氪”公众号
公众号右上角 -> 全部消息
在公众号主页，右上角有三个实心圆点，点击进入消息界面，下滑找到并点击“全部消息”，往下请求加载几次历史文章，然后回到Fiddler界面，不出意外的话应该可以看到这几次请求，可以看到返回的数据是json格式的，同时文章数据是以json字符串的形式定义在general_msg_list字段中：
公众号文章列表抓包请求
分析文章列表接口
把请求URL和Cookie贴上来进行分析：
https://mp.weixin.qq.com/mp/profile_ext?action=getmsg&__biz=MzI2NDk5NzA0Mw==&f=json&offset=10&count=10&is_ok=1&scene=126&uin=777&key=777&pass_ticket=QhOypNwH5dAr5w6UgMjyBrTSOdMEUT86vWc73GANoziWFl8xJd1hIMbMZ82KgCpN&wxtoken=&appmsg_token=971_LwY7Z%252BFBoaEv5z8k_dFWfJkdySbNkMR4OmFxNw~~&x5=1&f=json Cookie: pgv_pvid=2027337976; pgv_info=ssid=s3015512850; rewardsn=; wxtokenkey=777; wxuin=2089823341; devicetype=android-26; version=26070237; lang=zh_CN;pass_ticket=NDndxxaZ7p6Z9PYulWpLqMbI0i3ULFeCPIHBFu1sf5pX2IhkGfyxZ6b9JieSYRUy;wap_sid2=CO3YwOQHEogBQnN4VTNhNmxQWmc3UHI2U3kteWhUeVExZHFVMnN0QXlsbzVJRUJKc1pkdVFUU2Y5UzhSVEtOZmt1VVlYTkR4SEllQ2huejlTTThJWndMQzZfYUw2SldLVGVMQUthUjc3QWdVMUdoaGN0Nml2SU05cXR1dTN2RkhRUVd1V2Y3SFJ5d01BQUF+fjCB1pLcBTgNQJVO
下面把重要的参数说明一下，没提到的说明就不那么重要了：
- __biz：相当于是当前公众号的id(唯一固定标志)
- offset：文章数据接口请求偏移量标志(从0开始)，每次返回的json数据中会有下一次请求的offset，注意这里并不是按某些规则递增的
- count：每次请求的数据量(亲测最多可以是10)
- pass_ticket：可以理解是请求票据，而且隔一段时间后(大概几个小时)就会过期，这也是为什么微信公众号比较难按固定规则进行抓取的原因
- appmsg_token：同样理解为非固定有过期策略的票据
- Cookie：使用的时候可以把整段贴上去，但最少仅需要wap_sid2这部分
是不是感觉有点麻烦，毕竟不是要搞大规模专业的爬虫，所以单就一个公众号这么分析下来，还是可以往下继续的，贴上截取的一段json数据，用于设计文章数据表：
{
"ret": 0,
"errmsg": "ok",
"msg_count": 10,
"can_msg_continue": 1,
"general_msg_list": "{\"list\":[{\"comm_msg_info\":{\"id\":1000005700,\"type\":49,\"datetime\":1535100943,\"fakeid\":\"3264997043\",\"status\":2,\"content\":\"\"},\"app_msg_ext_info\":{\"title\":\"金融危机又十年：钱荒之下，二手基金迎来高光时刻\",\"digest\":\"退出永远是基金的主旋律。\",\"content\":\"\",\"fileid\":100034824,\"content_url\":\"http:\\/\\/mp.weixin.qq.com\\/s?__biz=MzI2NDk5NzA0Mw==&mid=2247518479&idx=1&sn=124ab52f7478c1069a6b4592cdf3c5f5&chksm=eaa6d8d3ddd151c5bb95a7ae118de6d080023246aa0a419e1d53bfe48a8d9a77e52b752d9b80&scene=27#wechat_redirect\",\"source_url\":\"\",\"cover\":\"http:\\/\\/mmbiz.qpic.cn\\/mmbiz_jpg\\/QicyPhNHD5vYgdpprkibtnWCAN7l4ZaqibKvopNyCWWLQAwX7QpzWicnQSVfcBZmPrR5YuHS45JIUzVjb0dZTiaLPyA\\/0?wx_fmt=jpeg\",\"subtype\":9,\"is_multi\":0,\"multi_app_msg_item_list\":[],\"author\":\"石亚琼\",\"copyright_stat\":11,\"duration\":0,\"del_flag\":1,\"item_show_type\":0,\"audio_fileid\":0,\"play_url\":\"\",\"malicious_title_reason_id\":0,\"malicious_content_type\":0}}]}",
"next_offset": 20,
"video_count": 1,
"use_video_tab": 1,
"real_type": 0
}
可以简单抽取想要的数据，这里将文章表结构定义如下，顺便贴上建表的SQL语句：
文章数据表
-- ---------------------------- -- Table structure for tb_article -- ---------------------------- DROP TABLE IF EXISTS "public"."tb_article"; CREATE TABLE "public"."tb_article" ( "id" serial4 PRIMARY KEY, "msg_id" int8 NOT NULL, "title" varchar(200) COLLATE "pg_catalog"."default" NOT NULL, "author" varchar(20) COLLATE "pg_catalog"."default", "cover" varchar(500) COLLATE "pg_catalog"."default", "digest" varchar(200) COLLATE "pg_catalog"."default", "source_url" varchar(800) COLLATE "pg_catalog"."default", "content_url" varchar(600) COLLATE "pg_catalog"."default" NOT NULL, "post_time" timestamp(6), "create_time" timestamp(6) NOT NULL ) ; COMMENT ON COLUMN "public"."tb_article"."id" IS '自增主键'; COMMENT ON COLUMN "public"."tb_article"."msg_id" IS '消息id (唯一)'; COMMENT ON COLUMN "public"."tb_article"."title" IS '标题'; COMMENT ON COLUMN "public"."tb_article"."author" IS '作者'; COMMENT ON COLUMN "public"."tb_article"."cover" IS '封面图'; COMMENT ON COLUMN "public"."tb_article"."digest" IS '关键字'; COMMENT ON COLUMN "public"."tb_article"."source_url" IS '原文地址'; COMMENT ON COLUMN "public"."tb_article"."content_url" IS '文章地址'; COMMENT ON COLUMN "public"."tb_article"."post_time" IS '发布时间'; COMMENT ON COLUMN "public"."tb_article"."create_time" IS '入库时间'; COMMENT ON TABLE "public"."tb_article" IS '公众号文章表'; -- ---------------------------- -- Indexes structure for table tb_article -- ---------------------------- CREATE UNIQUE INDEX "unique_msg_id" ON "public"."tb_article" USING btree ( "msg_id" "pg_catalog"."int8_ops" ASC NULLS LAST );
附请求文章接口并解析数据保存到数据库的相关代码：
class WxMps(object):
"""微信公众号文章、评论抓取爬虫"""
def __init__(self, _biz, _pass_ticket, _app_msg_token, _cookie, _offset=0):
self.offset = _offset
self.biz = _biz # 公众号标志
self.msg_token = _app_msg_token # 票据(非固定)
self.pass_ticket = _pass_ticket # 票据(非固定)
self.headers = {
'Cookie': _cookie, # Cookie(非固定)
'User-Agent': 'Mozilla/5.0 AppleWebKit/537.36 (KHTML, like Gecko) Version/4.0 Chrome/57.0.2987.132 '
}
wx_mps = 'wxmps' # 这里数据库、用户、密码一致(需替换成实际的)
self.postgres = pgs.Pgs(host='localhost', port='5432', db_name=wx_mps, user=wx_mps, password=wx_mps)
def start(self):
"""请求获取公众号的文章接口"""
offset = self.offset
while True:
api = 'https://mp.weixin.qq.com/mp/profile_ext?action=getmsg&__biz={0}&f=json&offset={1}' \
'&count=10&is_ok=1&scene=124&uin=777&key=777&pass_ticket={2}&wxtoken=&appmsg_token' \
'={3}&x5=1&f=json'.format(self.biz, offset, self.pass_ticket, self.msg_token)
resp = requests.get(api, headers=self.headers).json()
ret, status = resp.get('ret'), resp.get('errmsg') # 状态信息
if ret == 0 or status == 'ok':
print('Crawl article: ' + api)
offset = resp['next_offset'] # 下一次请求偏移量
general_msg_list = resp['general_msg_list']
msg_list = json.loads(general_msg_list)['list'] # 获取文章列表
for msg in msg_list:
comm_msg_info = msg['comm_msg_info'] # 该数据是本次推送多篇文章公共的
msg_id = comm_msg_info['id'] # 文章id
post_time = datetime.fromtimestamp(comm_msg_info['datetime']) # 发布时间
# msg_type = comm_msg_info['type'] # 文章类型
# msg_data = json.dumps(comm_msg_info, ensure_ascii=False) # msg原数据
app_msg_ext_info = msg.get('app_msg_ext_info') # article原数据
if app_msg_ext_info:
# 本次推送的首条文章
self._parse_articles(app_msg_ext_info, msg_id, post_time)
# 本次推送的其余文章
multi_app_msg_item_list = app_msg_ext_info.get('multi_app_msg_item_list')
if multi_app_msg_item_list:
for item in multi_app_msg_item_list:
msg_id = item['fileid'] # 文章id
if msg_id == 0:
msg_id = int(time.time() * 1000) # 设置唯一id,解决部分文章id=0出现唯一索引冲突的情况
self._parse_articles(item, msg_id, post_time)
print('next offset is %d' % offset)
else:
print('Before break , Current offset is %d' % offset)
break
def _parse_articles(self, info, msg_id, post_time):
"""解析嵌套文章数据并保存入库"""
title = info.get('title') # 标题
cover = info.get('cover') # 封面图
author = info.get('author') # 作者
digest = info.get('digest') # 关键字
source_url = info.get('source_url') # 原文地址
content_url = info.get('content_url') # 微信地址
# ext_data = json.dumps(info, ensure_ascii=False) # 原始数据
self.postgres.handler(self._save_article(), (msg_id, title, author, cover, digest,
source_url, content_url, post_time,
datetime.now()), fetch=True)
@staticmethod
def _save_article():
sql = 'insert into tb_article(msg_id,title,author,cover,digest,source_url,content_url,post_time,create_time) ' \
'values(%s,%s,%s,%s,%s,%s,%s,%s,%s)'
return sql
if __name__ == '__main__':
biz = 'MzI2NDk5NzA0Mw==' # "36氪"
pass_ticket = 'NDndxxaZ7p6Z9PYulWpLqMbI0i3ULFeCPIHBFu1sf5pX2IhkGfyxZ6b9JieSYRUy'
app_msg_token = '971_Z0lVNQBcGsWColSubRO9H13ZjrPhjuljyxLtiQ~~'
cookie = 'wap_sid2=CO3YwOQHEogBQnN4VTNhNmxQWmc3UHI2U3kteWhUeVExZHFVMnN0QXlsbzVJRUJKc1pkdVFUU2Y5UzhSVEtOZmt1VVlYTkR4SEllQ2huejlTTThJWndMQzZfYUw2SldLVGVMQUthUjc3QWdVMUdoaGN0Nml2SU05cXR1dTN2RkhRUVd1V2Y3SFJ5d01BQUF+fjCB1pLcBTgNQJVO'
# 以上信息不同公众号每次抓取都需要借助抓包工具做修改
wxMps = WxMps(biz, pass_ticket, app_msg_token, cookie)
wxMps.start() # 开始爬取文章
分析文章评论接口
获取评论的思路大致是一样的，只是会更加麻烦一点。首先在手机端点开一篇有评论的文章，然后查看Fiddler抓取的请求：
公众号文章评论
公众号文章评论接口抓包请求
提取其中的URL和Cookie再次分析：
https://mp.weixin.qq.com/mp/appmsg_comment?action=getcomment&scene=0&__biz=MzI2NDk5NzA0Mw==&appmsgid=2247518723&idx=1&comment_id=433253969406607362&offset=0&limit=100&uin=777&key=777&pass_ticket=NDndxxaZ7p6Z9PYulWpLqMbI0i3ULFeCPIHBFu1sf5pX2IhkGfyxZ6b9JieSYRUy&wxtoken=777&devicetype=android-26&clientversion=26070237&appmsg_token=971_dLK7htA1j8LbMUk8pvJKRlC_o218HEgwDbS9uARPOyQ34_vfXv3iDstqYnq2gAyze1dBKm4ZMTlKeyfx&x5=1&f=json Cookie: pgv_pvid=2027337976; pgv_info=ssid=s3015512850; rewardsn=; wxuin=2089823341; devicetype=android-26; version=26070237; lang=zh_CN; pass_ticket=NDndxxaZ7p6Z9PYulWpLqMbI0i3ULFeCPIHBFu1sf5pX2IhkGfyxZ6b9JieSYRUy; wap_sid2=CO3YwOQHEogBdENPSVdaS3pHOWc1V2QzY1NvZG9PYk1DMndPS3NfbGlHM0Vfal8zLU9kcUdkWTQxdUYwckFBT3RZM1VYUXFaWkFad3NVaWFXZ28zbEFIQ2pTa1lqZktfb01vcGdPLTQ0aGdJQ2xOSXoxTVFvNUg3SVpBMV9GRU1lbnotci1MWWl5d01BQUF+fjCj45PcBTgNQAE=; wxtokenkey=777
接着分析参数：
- __biz：同上
- pass_ticket：同上
- Cookie：同上
- offset和limit：代表偏移量和请求数量，由于公众号评论最多展示100条，所以这两个参数也不用改它
- comment_id：获取文章评论数据的标记id，固定但需要从当前文章结构(Html)解析提取
- appmsgid：票据id，非固定每次需要从当前文章结构(Html)解析提取
- appmsg_token：票据token，非固定每次需要从当前文章结构(Html)解析提取
可以看到最后三个参数要解析html获取(当初真的找了好久才想到看文章网页结构)。从文章请求接口可以获得文章地址，对应上面的content_url字段，但请求该地址前仍需要对url做相关处理，不然上面三个参数会有缺失，也就获取不到后面评论内容：
def _parse_article_detail(self, content_url, article_id):
"""从文章页提取相关参数用于获取评论,article_id是已保存的文章id"""
try:
api = content_url.replace('amp;', '').replace('#wechat_redirect', '').replace('http', 'https')
html = requests.get(api, headers=self.headers).text
except:
print('获取评论失败' + content_url)
else:
# group(0) is current line
str_comment = re.search(r'var comment_id = "(.*)" \|\| "(.*)" \* 1;', html)
str_msg = re.search(r"var appmsgid = '' \|\| '(.*)'\|\|", html)
str_token = re.search(r'window.appmsg_token = "(.*)";', html)
if str_comment and str_msg and str_token:
comment_id = str_comment.group(1) # 评论id(固定)
app_msg_id = str_msg.group(1) # 票据id(非固定)
appmsg_token = str_token.group(1) # 票据token(非固定)
再回来看该接口返回的json数据，分析结构后然后定义数据表(含SQL)：
文章评论数据表
-- ---------------------------- -- Table structure for tb_article_comment -- ---------------------------- DROP TABLE IF EXISTS "public"."tb_article_comment"; CREATE TABLE "public"."tb_article_comment" ( "id" serial4 PRIMARY KEY, "article_id" int4 NOT NULL, "comment_id" varchar(50) COLLATE "pg_catalog"."default", "nick_name" varchar(50) COLLATE "pg_catalog"."default" NOT NULL, "logo_url" varchar(300) COLLATE "pg_catalog"."default", "content_id" varchar(50) COLLATE "pg_catalog"."default" NOT NULL, "content" varchar(3000) COLLATE "pg_catalog"."default" NOT NULL, "like_num" int2, "comment_time" timestamp(6), "create_time" timestamp(6) NOT NULL ) ; COMMENT ON COLUMN "public"."tb_article_comment"."id" IS '自增主键'; COMMENT ON COLUMN "public"."tb_article_comment"."article_id" IS '文章外键id'; COMMENT ON COLUMN "public"."tb_article_comment"."comment_id" IS '评论接口id'; COMMENT ON COLUMN "public"."tb_article_comment"."nick_name" IS '用户昵称'; COMMENT ON COLUMN "public"."tb_article_comment"."logo_url" IS '头像地址'; COMMENT ON COLUMN "public"."tb_article_comment"."content_id" IS '评论id (唯一)'; COMMENT ON COLUMN "public"."tb_article_comment"."content" IS '评论内容'; COMMENT ON COLUMN "public"."tb_article_comment"."like_num" IS '点赞数'; COMMENT ON COLUMN "public"."tb_article_comment"."comment_time" IS '评论时间'; COMMENT ON COLUMN "public"."tb_article_comment"."create_time" IS '入库时间'; COMMENT ON TABLE "public"."tb_article_comment" IS '公众号文章评论表'; -- ---------------------------- -- Indexes structure for table tb_article_comment -- ---------------------------- CREATE UNIQUE INDEX "unique_content_id" ON "public"."tb_article_comment" USING btree ( "content_id" COLLATE "pg_catalog"."default" "pg_catalog"."text_ops" ASC NULLS LAST );
万里长征快到头了，最后贴上这部分代码，由于要先获取文章地址，所以和上面获取文章数据的代码是一起的：
import json
import re
import time
from datetime import datetime
import requests
from utils import pgs
class WxMps(object):
"""微信公众号文章、评论抓取爬虫"""
def __init__(self, _biz, _pass_ticket, _app_msg_token, _cookie, _offset=0):
self.offset = _offset
self.biz = _biz # 公众号标志
self.msg_token = _app_msg_token # 票据(非固定)
self.pass_ticket = _pass_ticket # 票据(非固定)
self.headers = {
'Cookie': _cookie, # Cookie(非固定)
'User-Agent': 'Mozilla/5.0 AppleWebKit/537.36 (KHTML, like Gecko) Version/4.0 Chrome/57.0.2987.132 '
}
wx_mps = 'wxmps' # 这里数据库、用户、密码一致(需替换成实际的)
self.postgres = pgs.Pgs(host='localhost', port='5432', db_name=wx_mps, user=wx_mps, password=wx_mps)
def start(self):
"""请求获取公众号的文章接口"""
offset = self.offset
while True:
api = 'https://mp.weixin.qq.com/mp/profile_ext?action=getmsg&__biz={0}&f=json&offset={1}' \
'&count=10&is_ok=1&scene=124&uin=777&key=777&pass_ticket={2}&wxtoken=&appmsg_token' \
'={3}&x5=1&f=json'.format(self.biz, offset, self.pass_ticket, self.msg_token)
resp = requests.get(api, headers=self.headers).json()
ret, status = resp.get('ret'), resp.get('errmsg') # 状态信息
if ret == 0 or status == 'ok':
print('Crawl article: ' + api)
offset = resp['next_offset'] # 下一次请求偏移量
general_msg_list = resp['general_msg_list']
msg_list = json.loads(general_msg_list)['list'] # 获取文章列表
for msg in msg_list:
comm_msg_info = msg['comm_msg_info'] # 该数据是本次推送多篇文章公共的
msg_id = comm_msg_info['id'] # 文章id
post_time = datetime.fromtimestamp(comm_msg_info['datetime']) # 发布时间
# msg_type = comm_msg_info['type'] # 文章类型
# msg_data = json.dumps(comm_msg_info, ensure_ascii=False) # msg原数据
app_msg_ext_info = msg.get('app_msg_ext_info') # article原数据
if app_msg_ext_info:
# 本次推送的首条文章
self._parse_articles(app_msg_ext_info, msg_id, post_time)
# 本次推送的其余文章
multi_app_msg_item_list = app_msg_ext_info.get('multi_app_msg_item_list')
if multi_app_msg_item_list:
for item in multi_app_msg_item_list:
msg_id = item['fileid'] # 文章id
if msg_id == 0:
msg_id = int(time.time() * 1000) # 设置唯一id,解决部分文章id=0出现唯一索引冲突的情况
self._parse_articles(item, msg_id, post_time)
print('next offset is %d' % offset)
else:
print('Before break , Current offset is %d' % offset)
break
def _parse_articles(self, info, msg_id, post_time):
"""解析嵌套文章数据并保存入库"""
title = info.get('title') # 标题
cover = info.get('cover') # 封面图
author = info.get('author') # 作者
digest = info.get('digest') # 关键字
source_url = info.get('source_url') # 原文地址
content_url = info.get('content_url') # 微信地址
# ext_data = json.dumps(info, ensure_ascii=False) # 原始数据
content_url = content_url.replace('amp;', '').replace('#wechat_redirect', '').replace('http', 'https')
article_id = self.postgres.handler(self._save_article(), (msg_id, title, author, cover, digest,
source_url, content_url, post_time,
datetime.now()), fetch=True)
if article_id:
self._parse_article_detail(content_url, article_id)
def _parse_article_detail(self, content_url, article_id):
"""从文章页提取相关参数用于获取评论,article_id是已保存的文章id"""
try:
html = requests.get(content_url, headers=self.headers).text
except:
print('获取评论失败' + content_url)
else:
# group(0) is current line
str_comment = re.search(r'var comment_id = "(.*)" \|\| "(.*)" \* 1;', html)
str_msg = re.search(r"var appmsgid = '' \|\| '(.*)'\|\|", html)
str_token = re.search(r'window.appmsg_token = "(.*)";', html)
if str_comment and str_msg and str_token:
comment_id = str_comment.group(1) # 评论id(固定)
app_msg_id = str_msg.group(1) # 票据id(非固定)
appmsg_token = str_token.group(1) # 票据token(非固定)
# 缺一不可
if appmsg_token and app_msg_id and comment_id:
print('Crawl article comments: ' + content_url)
self._crawl_comments(app_msg_id, comment_id, appmsg_token, article_id)
def _crawl_comments(self, app_msg_id, comment_id, appmsg_token, article_id):
"""抓取文章的评论"""
api = 'https://mp.weixin.qq.com/mp/appmsg_comment?action=getcomment&scene=0&__biz={0}' \
'&appmsgid={1}&idx=1&comment_id={2}&offset=0&limit=100&uin=777&key=777' \
'&pass_ticket={3}&wxtoken=777&devicetype=android-26&clientversion=26060739' \
'&appmsg_token={4}&x5=1&f=json'.format(self.biz, app_msg_id, comment_id,
self.pass_ticket, appmsg_token)
resp = requests.get(api, headers=self.headers).json()
ret, status = resp['base_resp']['ret'], resp['base_resp']['errmsg']
if ret == 0 or status == 'ok':
elected_comment = resp['elected_comment']
for comment in elected_comment:
nick_name = comment.get('nick_name') # 昵称
logo_url = comment.get('logo_url') # 头像
comment_time = datetime.fromtimestamp(comment.get('create_time')) # 评论时间
content = comment.get('content') # 评论内容
content_id = comment.get('content_id') # id
like_num = comment.get('like_num') # 点赞数
# reply_list = comment.get('reply')['reply_list'] # 回复数据
self.postgres.handler(self._save_article_comment(), (article_id, comment_id, nick_name, logo_url,
content_id, content, like_num, comment_time,
datetime.now()))
@staticmethod
def _save_article():
sql = 'insert into tb_article(msg_id,title,author,cover,digest,source_url,content_url,post_time,create_time) ' \
'values(%s,%s,%s,%s,%s,%s,%s,%s,%s) returning id'
return sql
@staticmethod
def _save_article_comment():
sql = 'insert into tb_article_comment(article_id,comment_id,nick_name,logo_url,content_id,content,like_num,' \
'comment_time,create_time) values(%s,%s,%s,%s,%s,%s,%s,%s,%s)'
return sql
if __name__ == '__main__':
biz = 'MzI2NDk5NzA0Mw==' # "36氪"
pass_ticket = 'NDndxxaZ7p6Z9PYulWpLqMbI0i3ULFeCPIHBFu1sf5pX2IhkGfyxZ6b9JieSYRUy'
app_msg_token = '971_Z0lVNQBcGsWColSubRO9H13ZjrPhjuljyxLtiQ~~'
cookie = 'wap_sid2=CO3YwOQHEogBQnN4VTNhNmxQWmc3UHI2U3kteWhUeVExZHFVMnN0QXlsbzVJRUJKc1pkdVFUU2Y5UzhSVEtOZmt1VVlYTkR4SEllQ2huejlTTThJWndMQzZfYUw2SldLVGVMQUthUjc3QWdVMUdoaGN0Nml2SU05cXR1dTN2RkhRUVd1V2Y3SFJ5d01BQUF+fjCB1pLcBTgNQJVO'
# 以上信息不同公众号每次抓取都需要借助抓包工具做修改
wxMps = WxMps(biz, pass_ticket, app_msg_token, cookie)
wxMps.start() # 开始爬取文章及评论
文末小结
最后展示下数据库里的数据，单线程爬的慢而且又没这方面的数据需求，所以也只是随便试了下手：
抓取的部分数据
有时候写爬虫是个细心活，如果觉得太麻烦的话，推荐了解下WechatSogou这个工具。有问题的欢迎底部留言讨论。
完整代码：GitHub
以上就是本文的全部内容，希望对大家的学习有所帮助，也希望大家多多支持【听图阁-专注于Python设计】。
