整个项目流程如下图所示：
网页分析
首先，我们打开一个话题，通过F12查看，可以看到是一个异步加载的网页，我们需要对其进行找包，如图，这个包就是我们所需要的。
接着，我们分析下这个url，可以发现，除了offset用于分页，questions后面的数字为不同问题的ID。之外，其他url的参数都是固定的，所以我们只需要构造这个url，不断循环请求就好了。
https://www.zhihu.com/api/v4/questions/29024583/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%2Cvoteup_count%2Creshipment_settings%2Ccomment_permission%2Ccreated_time%2Cupdated_time%2Creview_info%2Crelevant_info%2Cquestion%2Cexcerpt%2Crelationship.is_authorized%2Cis_author%2Cvoting%2Cis_thanked%2Cis_nothelp%2Cis_labeled%3Bdata%5B%2A%5D.mark_infos%5B%2A%5D.url%3Bdata%5B%2A%5D.author.follower_count%2Cbadge%5B%2A%5D.topics&limit=3&offset=3&platform=desktop&sort_by=default
返回的数据为json数据，我们这里只是需要图片，所以只提取用户昵称和内容（昵称用于图片取名，内容中有图片信息）。
图片信息存在content字段中，我们通过正则表达式来进行提取。
爬虫代码
根据上面的思路，我们编写爬虫代码：
import requests
from lxml import etree
import json
import time
import re
headers = {
'user-agent':'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/68.0.3440.106 Safari/537.36',
'cookie':''
}
def get_img(url):
res = requests.get(url,headers=headers)
i = 1
json_data = json.loads(res.text)
datas = json_data['data']
for data in datas:
id = data['author']['name']
content = data['content']
imgs = re.findall('img src="(.*?)"',content,re.S)
if len(imgs) == 0:
pass
else:
for img in imgs:
if 'jpg' in img:
res_1 = requests.get(img,headers=headers)
fp = open('row_img/' + id + '+' + str(i) + '.jpg','wb')
fp.write(res_1.content)
i = i + 1
print(id,img)
if __name__ == '__main__':
urls = ['https://www.zhihu.com/api/v4/questions/29024583/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%2Cvoteup_count%2Creshipment_settings%2Ccomment_permission%2Ccreated_time%2Cupdated_time%2Creview_info%2Crelevant_info%2Cquestion%2Cexcerpt%2Crelationship.is_authorized%2Cis_author%2Cvoting%2Cis_thanked%2Cis_nothelp%2Cis_labeled%3Bdata%5B%2A%5D.mark_infos%5B%2A%5D.url%3Bdata%5B%2A%5D.author.follower_count%2Cbadge%5B%2A%5D.topics&limit=5&offset={}&platform=desktop&sort_by=default'.format(str(i)) for i in range(0,25000,5)]
for url in urls:
get_img(url)
time.sleep(2)
这里cookie需要换成自己的，我们图片的命名为用户昵称+数字（由于一个回答可能有多个图片），结果如图，这样，就解锁了一份小姐姐图片。
人脸识别API
由于爬取了图片，有一些是没人像，有些是男的…而且是为了找到高颜值小姐姐，如果人工筛选费事费力，这里调用百度的人脸识别API，进行图片过滤和颜值打分，选出知乎最美小姐姐。
接着我们通过API Key和Secret Key获取token：
import requests
ak = ''
sk = ''
host = 'https://aip.baidubce.com/oauth/2.0/token?grant_type=client_credentials&client_id={}&client_secret={}'.format(ak,sk)
res = requests.post(host)
print(res.text)
我们拿着token，来请求对应的网页就可以获取图片的内容了。我们拿张超越妹妹的图片做例子~
import base64
import json
token = ''
def get_img_base(file):
with open(file,'rb') as fp:
content = base64.b64encode(fp.read())
return content
request_url = "https://aip.baidubce.com/rest/2.0/face/v3/detect"
request_url = request_url + "?access_token=" + token
params = {
'image':get_img_base('test.jpg'),
'image_type':'BASE64',
'face_field':'age,beauty,gender'
}
res = requests.post(request_url,data=params)
result = res.text
json_result = json.loads(result)
code = json_result['error_code']
gender = json_result['result']['face_list'][0]['gender']['type']
beauty = json_result['result']['face_list'][0]['beauty']
print(code,gender,beauty)
### result 0 female 76.25
这里的token为前面请求得到的，params的参数中，图片需要base64编码~超越妹妹76.25，还算给力。
综合使用
最后，我们逐一请求我们保存的图片，过滤掉非人物以及男性图片，获取小姐姐图片的分数（这里处理为1-10分），并分别存在不同的文件夹中。
import requests
import os
import base64
import json
import time
def get_img_base(file):
with open(file,'rb') as fp:
content = base64.b64encode(fp.read())
return content
file_path = 'row_img'
list_paths = os.listdir(file_path)
for list_path in list_paths:
img_path = file_path + '/' + list_path
# print(img_path)
token = '24.a2d7a4d09435e716cf1cb163f176cb12.2592000.1553929524.282335-15648650'
request_url = "https://aip.baidubce.com/rest/2.0/face/v3/detect"
request_url = request_url + "?access_token=" + token
params = {
'image':get_img_base(img_path),
'image_type':'BASE64',
'face_field':'age,beauty,gender'
}
res = requests.post(request_url,data=params)
json_result = json.loads(res.text)
code = json_result['error_code']
if code == 222202:
continue
try:
gender = json_result['result']['face_list'][0]['gender']['type']
if gender == 'male':
continue
beauty = json_result['result']['face_list'][0]['beauty']
new_beauty = round(beauty/10,1)
print(img_path,new_beauty)
if new_beauty >= 8:
os.rename(os.path.join(file_path,list_path),os.path.join('8分',str(new_beauty) + '+' + list_path))
elif new_beauty >= 7:
os.rename(os.path.join(file_path,list_path),os.path.join('7分',str(new_beauty) + '+' + list_path))
elif new_beauty >= 6:
os.rename(os.path.join(file_path,list_path),os.path.join('6分',str(new_beauty) + '+' + list_path))
elif new_beauty >= 5:
os.rename(os.path.join(file_path,list_path),os.path.join('5分',str(new_beauty) + '+' + list_path))
else:
os.rename(os.path.join(file_path,list_path),os.path.join('其他分',str(new_beauty) + '+' + list_path))
time.sleep(1)
except KeyError:
pass
except TypeError:
pass
代码获取：808713721裙共享里