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from email import header
import requests
from hyper.contrib import HTTP20Adapter #导入HTTP2的模块
import json
import math
import time
#import xlwt #导入excel官方模块，用于将字典生成excel
import pandas as pd #将字典列表转换为DataFrame
import re
def load_data(st,end):#加载数据需要传入st开始位置和end结束位置
url = 'https://qun.qq.com/cgi-bin/qun_mgr/search_group_members'
cookie = '您的cookie'
headers = {
":authority": "qun.qq.com",
":method": "POST",
":path": "/cgi-bin/qun_mgr/search_group_members",
":scheme": "https",
"accept": "application/json, text/javascript, */*; q=0.01",
"accept-encoding": "gzip, deflate, br",
"accept-language": "zh-CN,zh;q=0.9",
"content-length": "45",
"content-type": "application/x-www-form-urlencoded; charset=UTF-8",
"cookie": cookie,
"origin": "https://qun.qq.com",
"referer": "https://qun.qq.com/member.html",
"user-agent": "Mozilla/5.0 (Windows NT 10.0; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/69.0.3947.100 Safari/537.36",
"x-requested-with": "XMLHttpRequest"
}
def cookie_to_dict(cookie):#将cookie字符串转换为字典
cookie_dict = {}
for i in cookie.split('; '):
cookie_dict[i.split('=')[0]] = i.split('=')[1]
return cookie_dict
def get_bkn():#从QQ群中获取bkn函数
e = cookie_to_dict(cookie)['skey'] #e = cookie里skey的值,调用cookie_to_dict函数将cookie字符串转换为字典
t = 5381
n = 0
o = len(e)
while n < o:
t += (t << 5) + ord(e[n])
n += 1
return(2147483647 & t)
# print(get_bkn())
# gc = input('请输入要查询的群号:')
global gc
gc = '599500635' # 群号
data = {
"gc": gc,
"st": st,
"end": end,
"sort": "0",
"bkn": get_bkn()
}
sessions=requests.session()
sessions.mount('https://qun.qq.com', HTTP20Adapter())
response=sessions.post(url,headers=headers,data=data)
response = response.text
response = response.encode('utf-8').decode("unicode_escape")
return response
def get_qq_member_count():#获取群成员数量函数
response = load_data(0,0)
qq_member_count = json.loads(response)['count'] #qq群人数
# print(qq_member_count)
return qq_member_count
global qq_qun_info #全局变量qq群信息列表
qq_qun_info = []
def get_qq_member_list():#获取群成员列表函数
count = math.ceil(get_qq_member_count()/21) #需要循环的次数
# print('需要循环的次数：'+str(count))
n = 0 #用于计数
j = 0 #计数器用于判断当前循环的次数
num = 1 #用于给字典里的信息加序号
while j < count:
#load_data()参数的取值 第一次是从0到20 第二次是从21到41 第三次是从42到62以此类推保证不获取重复值
response = load_data(n+j,n+20+j)
res = json.loads(response)['mems']
# print('res='+str(res))
qq_name = '' # qq名字
qq_qun_name = '' # qq群名字
qq_number = '' # qq号码
sex = '' # 性别
qq_age = '' #q龄
join_qun_time = '' # 入群时间
last_speak_time = '' # 最后一次发言
for i in res:
qq_name = i['nick']
#替换qq昵称中的\为空
qq_name = filter_emoji(qq_name,'???')
qq_qun_name = i['card']
#替换qq群昵称中的\为空
qq_qun_name = filter_emoji(qq_qun_name,'???')
qq_number = str(i['uin'])
sex = i['g'] #如果sex = 0则为男性, sex = -1未知, sex = 1为女性
if sex == 0:
sex = '男'
elif sex == 1:
sex = '女'
elif sex == -1:
sex = '未知'
else:
sex = '错误'
qq_age = i['qage']
join_qun_time = i['join_time'] #这里返回的是10位整数
last_speak_time = i['last_speak_time']
#将以上内容加入字典dict1中
dict1 = {}
dict1['num'] = num
dict1["qq_name"] = qq_name
dict1["qq_qun_name"] = qq_qun_name
dict1["qq_number"] = qq_number
dict1["sex"] = sex
dict1["qq_age"] = qq_age
#将十位数入群时间转为正常时间
join_qun_time = time.strftime("%Y-%m-%d %H:%M:%S", time.localtime(join_qun_time))
dict1["join_qun_time"] = join_qun_time
#将十位数最后一次发言时间转为正常时间
last_speak_time = time.strftime("%Y-%m-%d %H:%M:%S", time.localtime(last_speak_time))
dict1["last_speak_time"] = last_speak_time
qq_qun_info.append(dict1)
num = num + 1
j = j + 1
n += 20
print(qq_qun_info)
#将qq_qun_info列表导出为excel表格
# export_excel(qq_qun_info)
print('导出表格完成')
def export_excel(export):#将qq_qun_info列表保存为excel函数
#将字典列表转换为DataFrame
pf = pd.DataFrame(list(export))
#指定字段顺序
order = ['num','qq_name','qq_qun_name','qq_number','sex','qq_age','join_qun_time','last_speak_time']
pf = pf[order]
#将列名替换为中文
columns_map = {
'num':'序号',
'qq_name':'qq昵称',
'qq_qun_name':'qq群昵称',
'qq_number':'qq号码',
'sex':'性别',
'qq_age':'Q龄',
'join_qun_time':'入群时间',
'last_speak_time':'最近发言时间'
}
pf.rename(columns = columns_map,inplace = True)
#指定生成的Excel表格名称
file_path = pd.ExcelWriter(gc+'.xlsx')
#替换空单元格
pf.fillna(' ',inplace = True)
#输出
pf.to_excel(file_path,encoding = 'utf-8',index = False)
#保存表格
file_path.save()
def filter_emoji(desstr, restr=''):#过滤特殊字符函数
#desstr是要过滤的字符串
#restr是替换的字符串
# 过滤表情
res = re.compile(u'[\U00010000-\U0010ffff\\uD800-\\uDBFF\\uDC00-\\uDFFF]')
return res.sub(restr, desstr)
if __name__ == '__main__':
get_qq_member_list()
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