求看多线程爬取代码问题

[QIANJUFEN]

mport requests
import threading
import pandas as pd
import time
from lxml import etree
from fake_useragent import UserAgent
from random import choice
from queue import Queue

代理IP池，隐藏或改变爬虫的真实IP地址。

proxies = [
('http', 'http://120.55.14.64:80'),
('http', 'http://47.96.37.159:80'),
('http', 'http://60.174.0.184:8089'),
('http', 'http://182.204.178.124:8089')
]

#随机生成useragent
ua = UserAgent()
#生成1-50页url
def url_creat():
url = 'https://nj.lianjia.com/ershoufang/pg{}/'
#生成前100页url列表
links=[url.format(i) for i in range(1,51)]
return links

#解析url并提取数据
def url_parse(url,result_queue):
try:
headers = {
'Accept-Encoding': 'gzip, deflate, br, zstd',
'Accept-Language': 'zh-CN,zh;q=0.9,en;q=0.8,en-GB;q=0.7,en-US;q=0.6',
'Cache-Control': 'no-cache',
'Connection': 'keep-alive',
'Cookie': 'lianjia_uuid=1482b2e7-3112-4886-a41e-9d2d2e86b44d; _jzqc=1; _jzqckmp=1; sajssdk_2015_cross_new_user=1; _ga=GA1.2.452213069.1724131249; _gid=GA1.2.1832912406.1724131249; _ga_654P0WDKYN=GS1.2.1724131249.1.0.1724131249.0.0.0; hip=apJG191KDRPikxgtTyi3OmoLYtJFJa9yCiORXQVgZ51QYD0SMeG3eATx2a1EuGGf7_iZ0YxmbRitHPS-wygw6eU7_uOz42xUXwELiqydaMqCOjZqUVrz7n77aek0s8UJGOuDAVObHUnwVJIEA9dtMtsaU2qLrjx0DsDaDb26BNk6uSjJ2owluyHyCg%3D%3D; _jzqx=1.1724131236.1724138261.2.jzqsr=cn%2Ebing%2Ecom|jzqct=/.jzqsr=hip%2Elianjia%2Ecom|jzqct=/; _ga_DX18CJBZRT=GS1.2.1724138272.1.0.1724138272.0.0.0; _ga_EYZV9X59TQ=GS1.2.1724138272.1.0.1724138272.0.0.0; select_city=320100; lianjia_ssid=aed34a25-3548-4cb0-9828-61f1b13e8284; Qs_lvt_200116=1724138352; Hm_lvt_9152f8221cb6243a53c83b956842be8a=1724138353; HMACCOUNT=67BCC534482CC88A; jzqa=1.3305053847575342600.1724131236.1724138261.1724140333.3; sensorsdata2015jssdkcross=%7B%22distinct_id%22%3A%221916e3adab62f-06c1cb6122e849-4c657b58-1024000-1916e3adab777c%22%2C%22%24device_id%22%3A%221916e3adab62f-06c1cb6122e849-4c657b58-1024000-1916e3adab777c%22%2C%22props%22%3A%7B%22%24latest_traffic_source_type%22%3A%22%E7%9B%B4%E6%8E%A5%E6%B5%81%E9%87%8F%22%2C%22%24latest_referrer%22%3A%22%22%2C%22%24latest_referrer_host%22%3A%22%22%2C%22%24latest_search_keyword%22%3A%22%E6%9C%AA%E5%8F%96%E5%88%B0%E5%80%BC%E7%9B%B4%E6%8E%A5%E6%89%93%E5%BC%80%22%7D%7D; Qs_pv_200116=2599661905406085600%2C889815816991505000%2C2899766764332378600%2C91402511096122320%2C1000057718938937700; Hm_lpvt_9152f8221cb6243a53c83b956842be8a=1724140491; _jzqb=1.5.10.1724140333.1; _ga_E91JCCJY3Z=GS1.2.1724140344.3.1.1724140502.0.0.0; _ga_MFYNHLJT0H=GS1.2.1724140344.3.1.1724140502.0.0.0',
'Host': 'dig.lianjia.com',
'Pragma': 'no-cache',
'Referer': 'https://nj.lianjia.com/',
'sec-ch-ua': '"Not)A;Brand";v="99", "Microsoft Edge";v="127", "Chromium";v="127"',
'sec-ch-ua-mobile': '?1',
'Sec-Fetch-Dest': 'empty',
'Sec-Fetch-Mode': 'no-cors',
'Sec-Fetch-Site': 'same-site',
'Sec-Fetch-User': '?1',
'Upgrade-Insecure-Requests': '1',
'User-Agent':ua.random
}
proxy = choice(proxies)
response=requests.get(url=url,headers=headers,proxies={proxy[0]: proxy[1]})
response.raise_for_status() # 检查请求是否成功
tree=etree.HTML(response.text)
#ul列表下的全部li标签
li_List=tree.xpath("//*[@Class='sellListContent']/li")
results=[]

    for li in li_List:
        try:
    #标题
            title=li.xpath('./div/div/a/text()')[0]
    #网址
            link=li.xpath('./div/div/a/@href')[0]
    #位置
            postion=li.xpath('./div/div[2]/div/a/text()')[0]+li.xpath('./div/div[2]/div/a[2]/text()')[0]
    #类型
            types=li.xpath('./div/div[3]/div/text()')[0].split(' | ')[0]
    #面积
            area=li.xpath('./div/div[3]/div/text()')[0].split(' | ')[1]
    #房屋信息
            info=li.xpath('./div/div[3]/div/text()')[0].split(' | ')[2:-1]
            info=''.join(info)
    #总价
            count_price=li.xpath('.//div/div[6]/div/span/text()')[0]+'万'
    #单价
            angle_price=li.xpath('.//div/div[6]/div[2]/span/text()')[0]
            dic={'标题':title,"位置":postion,'房屋类型':types,'面积':area,"单价":angle_price,'总价':count_price,'介绍':info,"网址":link}
            print(dic)
    #将房屋信息加入总列表中
            results.append(dic)
        except IndexError:  
            print(f"Error parsing data from {url}")  
            continue  
        # 将结果放入队列中
    result_queue.put(results)  
except requests.RequestException as e:  
    print(f"Request error for {url}: {e}")  

def run():
links = url_creat()
threads=[]
result_queue = Queue()
lock = threading.Lock()
all_results=[]
#多线程爬取
for i in links:
x=threading.Thread(target=url_parse,args=(i,result_queue))
x.start()
threads.append(x)
#设置请求之间的时间间隔
time.sleep(1)
for t in threads:
t.join()

# 收集所有结果  
while not result_queue.empty():   
    page_results = result_queue.get()  # 取出的是列表的列表  
    all_results.extend(page_results[0])  # 扩展第一个元素（即包含字典的列表）  
#将全部房屋信息转化为excel
data=pd.DataFrame(all_results)
data.to_excel('房屋信息822.xlsx',index=False)

if name == 'main':
run()