import requests import os from bs4 import BeautifulSoup cookie = os.getenv('MY_COOKIE') # 保存到环境变量中 def get_with_cookie(url): headers = { 'cookie': cookie, 'pragma': 'no-cache', 'referer': 'https://uland.taobao.com/sem/tbsearch?refpid=mm_26632258_3504122_32538762&keyword=%E7%88%B1%E6%B7%98%E5%AE%9D%E4%B9%B0%E4%B8%9C%E8%A5%BF&clk1=066356e5e429004e6730976351cc1afc&upsId=066356e5e429004e6730976351cc1afc', 'sec-ch-ua': '"Microsoft Edge";v="113", "Chromium";v="113", "Not-A.Brand";v="24"', 'sec-ch-ua-mobile': '?0', 'sec-ch-ua-platform': "Windows", 'sec-fetch-dest': 'document', 'sec-fetch-mode': 'navigate', 'sec-fetch-site': 'same-origin', 'sec-fetch-user': '?1', 'upgrade-insecure-requests': '1', 'user-agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/113.0.0.0 Safari/537.36 Edg/113.0.1774.50' } resp = requests.get(url=url, headers=headers) return resp.text # 解析HTML内容，提取商品名称、价格和销量信息 def parse_html(html): soup = BeautifulSoup(html, 'html.parser') title = soup.select_one('h3.tb-main-title[data-title]') return title # 测试接口： url = 'https://item.taobao.com/item.htm?id=699089474285&ali_refid=a3_430673_1006:1102522391:N:%2BAkz14GC%2BXi%2Bma9dw7y9M4p5Yhq5iT8I:f9e826228fbc823934848d20e28dff81&ali_trackid=162_f9e826228fbc823934848d20e28dff81&spm=a2e0b.20350158.31919782.5' resp_text = get_with_cookie(url) title = parse_html(resp_text) # 打印商品信息 print(title.text.strip())使用try-except语句捕获异常

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帮我把一下代码设置一个合理请求头，并加入一个延时import requests import os from bs4 import BeautifulSoup class NovelDownloader: def init(self, root_url): self.root_url = root_url self.book_list = [] self.chapter_list = [] def get_url(self, url): while True: try: res = requests.get(url) if res.status_code == 200: print("页面获取成功！") return res.text else: print("页面返回异常！", res.status_code) except: print("页面获取错误！") def get_book_list(self): res = self.get_url(self.root_url) html = BeautifulSoup(res, "html.parser") a_list = html.find_all("a", {"class": "name"}) for a in a_list: self.book_list.append(a["href"]) self.book_list = [self.root_url + i for i in self.book_list] self.book_list.remove('http://www.biquge5200.cc/') def get_chapter_list(self, url): res = self.get_url(url) html = BeautifulSoup(res, "html.parser") a_list = html.find_all("a", {"class": "chapter"}) for a in a_list: self.chapter_list.append((a["href"], a.text.replace("\n", ""))) def get_content(self, chapter): url = self.root_url + chapter[0] print(url) book_name = chapter[0].split("/")[1] print(book_name) if not os.path.exists(book_name): os.mkdir(book_name) res = self.get_url(url) html = BeautifulSoup(res, "html.parser") content = html.find("div", {"id": "content"}).text print(content) path = os.path.join(book_name, chapter[1]) with open(path, "w", encoding="utf8") as f: f.write(content) def main(self): self.get_book_list() for book in self.book_list: self.get_chapter_list(book) for chapter in self.chapter_list: self.get_content(chapter) if name == 'main': root_url = "http://www.biquge5200.cc/" nd = NovelDownloader(root_url) nd.main()

from bs4 import BeautifulSoup class NovelDownloader: def __init__(self, root_url): self.root_url = root_url self.book_list = [] self.chapter_list = [] self.headers = { "User-Agent": "Mozilla/...

import requests from bs4 import BeautifulSoup # 发起网络请求，获取 HTML 页面 response = requests.get('http://example.com/images') # 使用 BeautifulSoup 解析 HTML 页面 soup = BeautifulSoup(response.text, 'html.parser') # 找到所有图片链接 image_tags = soup.find_all('img') # 遍历图片链接，下载图片 for image_tag in image_tags: image_url = image_tag['src'] response = requests.get(image_url) with open('image.jpg', 'wb') as f: f.write(response.content)

from bs4 import BeautifulSoup 这些语句用于导入 Python 中的两个模块： - requests 模块是用于发送 HTTP 请求的模块。通过使用 requests 模块，你可以发送 GET 请求、POST 请求、PUT 请求、DELETE 请求等等。 - ...

import requests from bs4 import BeautifulSoup import random import time main_url="http://www.xsbiquge.org/book/11432/" headers={ 'User-Agent':'Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:109.0) Gecko/20100101 Firefox/114.0' } main_req=requests.get(main_url,headers=headers) title_list=[] chapters_list=[] main_bs4=BeautifulSoup(main_req.text,"html.parser") #print(main_bs4.text) main_find_list=main_bs4.find_all("div",class_="info-chapters flex flex-wrap")[1].select("a") #print(main_find_list[1].text) #print(len(main_find_list)) for i in main_find_list: #print(i) title_list.append(i.text) chapters_list.append("www.xsbiquge.org"+i["href"]) #print(title_list) #print(chapters_list) fp=open("./shu.txt","w",encoding="utf-8") for i,chapter_url in enumerate(chapters_list): chapter_req=requests.get(chapter_url,headers=headers) chapter_bs4=BeautifulSoup(chapter_req.text,"html.parser") print(chapter_bs4.select("#article"))

from bs4 import BeautifulSoup import random import time 2. chapters_list 中存储的是每个章节的链接地址，但是在输出章节内容时，代码中使用了 chapter_bs4.select("#article")，这个选择器是用来...

import os import requests from bs4 import BeautifulSoup # 创建目录用于保存图片 if not os.path.exists('data'): os.mkdir('data') # 爬取网站 url = 'https://www.sucai999.com/pic/cate/263_267.html' response = requests.get(url) soup = BeautifulSoup(response.text, 'html.parser') # 获取图片链接并下载保存 img_tags = soup.find_all('img', class_='lazy') for index, img_tag in enumerate(img_tags[:20]): img_url = img_tag['data-original'] response = requests.get(img_url) with open(f'data/img{index}.jpg', 'wb') as f: f.write(response.content) print('图片保存完毕！')把这段代码优化成连续保存20张图片的代码

import os import requests from bs4 import BeautifulSoup # 创建目录用于保存图片 if not os.path.exists('data'): os.mkdir('data') # 爬取网站 url = '...requests.get(url) soup = BeautifulSoup(response.text, '...

import requests from bs4 import BeautifulSoup def getHTMLText(url): try: r = requests.get(url,timeout=30) r.raise_for_status() r.encoding = r.apparent_encoding return r.text except: return "产生异常" def jiexi(html_doc): soup = BeautifulSoup(html_doc,"html.parser") links = soup.find_all('a') for link in links: print(link.name,link["nref"],link.get.next()) if name == 'main': url = "https://wallhaven.cc/toplist?page=7" print(getHTMLText(url))改进代码

from bs4 import BeautifulSoup def get_html_text(url): try: r = requests.get(url, timeout=30) r.raise_for_status() r.encoding = r.apparent_encoding return r.text except: return "产生异常" def...

import requests from bs4 import BeautifulSoup import re import docx from docx.oxml.ns import qn

from bs4 import BeautifulSoup import re import docx from docx.oxml.ns import qn def my_function(): # 在这里编写代码请注意，这只是一个示例，您需要根据您的实际需求来编写函数或方法。在您的函数或...

import requests import os from bs4 import BeautifulSoup class book_spider(): def init(self,root_url): self.root_url=root_url self.book_list=[] #一级页面中获取的数据（二级页面地址）存放于此列表 self.chapter_list=[] #二级页面中获取的数据（三级页面地址和章节名）存放于此列表 def get_url(url): while True: try: res=requests.get(url) if res.status_code==200: res.encoding =res.apparent_encoding print("页面获取成功") return res.text else: print("页面返回异常",res.status_code) except: print("页面获取错误") def get_book_list(self.url): res = self.get_url(url) html = BeautifulSoup(res,"html.parser") a_list = html.find_all("a",{"class":"name"}) for a in a_list: self.book_list.append(a["href"]) self.book_list = [self.root_url+i for i in self.bbok_list] self.book_list.remove('http://10.1.88.252:7000/庆余年') print(book_list) def get_chapter_list(self,url): res = self.get_url(url) html = BeautifulSoup(res,"html.parser") a_list = html.find_all("a",{"class":"chapter"}) for a in a_list: self.chapter_list.append((a["href"],a.text.replace("\n",""))) def get_content(self.chapter): url = self.root_url + chapter[0] print(url) book_name = chapter[0].split("/")[1] print(book_name) if not os.path.exists(book_name): os.mkdir(book_name) res = self.get_url(url) html = BeautifulSoup(res,"html.parser") content = html.find("div",{"id":"content"}).text print(content) path = os.path.join(book_name,chapter[1]) with open(path,"w",encoding="utf8") as f: f.write(content) def main(): self.get_book_list(self.root_url) for book in self.book_list: self.get_chapter_liat(book) for chapter in chapter_list: self.get_content(chapter) book_s = book_spider("http://10.1.88.252:7000") book_s.main()这是一段爬虫代码，找出里面的错误并改正

from bs4 import BeautifulSoup class book_spider(): def __init__(self,root_url): self.root_url=root_url self.book_list=[] self.chapter_list=[] @staticmethod def get_url(url): while True: try...

import requests from bs4 import BeautifulSoup from concurrent.futures import ThreadPoolExecutor url_template = 'https://book.douban.com/tag/编程?start={}&type=T' headers = { 'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/58.0.3029.110 Safari/537.36'} def get_book_list(start): url = url_template.format(start) response = requests.get(url, headers=headers) soup = BeautifulSoup(response.text, 'html.parser') book_list = soup.find_all('li', class_='subject-item') return book_list def get_book_info(book): title = book.find('div', class_='info').a.get_text().strip() rating = book.find('span', class_='rating_nums').get_text().strip() return title, rating if name == 'main': with ThreadPoolExecutor(max_workers=10) as executor: futures = [] for start in range(0, 100, 20): futures.append(executor.submit(get_book_list, start)) books = [] for future in futures: books.extend(future.result()) futures = [] for book in books: futures.append(executor.submit(get_book_info, book)) for future in futures: title, rating = future.result() print(title, rating)改成正确代码

from bs4 import BeautifulSoup from concurrent.futures import ThreadPoolExecutor url_template = 'https://book.douban.com/tag/编程?start={}&type=T' headers = { 'User-Agent': 'Mozilla/5.0 (Windows NT ...

import requests from bs4 import BeautifulSoup import openpyxl from time import sleep # 设置请求头，模拟浏览器访问 headers = { 'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/114.0.0.0 Safari/537.36'} # 从天眼查获取公司邮箱和电话 def get_info(company): email = '' phone = '' url = 'https://www.tianyancha.com/search?key=' + company r = requests.get(url, headers=headers) soup = BeautifulSoup(r.text, 'html.parser') # try: # 获取公司详情页链接 company_url = soup.find_all('a', class_='index_alink__zcia5 link-click')[0].get('href') r = requests.get(company_url, headers=headers) soup = BeautifulSoup(r.text, 'html.parser') # 获取公司邮箱和电话 email = soup.find_all('span', class_='index_detail-email__B_1Tq')[0].text sleep(0.5) phone = soup.find('span',class_='index_detail-tel__fgpsE').text # except: # pass # return email,phone # 从Excel文件中读取公司名称 def read_from_excel(file_path): wb = openpyxl.load_workbook(file_path) ws = wb.active company_list = [] for row in ws.iter_rows(min_row=2, values_only=True): company_list.append(row[0]) return company_list # 将公司邮箱和电话写入Excel文件 def write_to_excel(company_list): wb = openpyxl.Workbook() ws = wb.active ws.title = 'Company Info' # 写入表头 ws.cell(row=1, column=1, value='Company Name') ws.cell(row=1, column=2, value='Email') ws.cell(row=1, column=3, value='Phone') # 写入数据 for i, company in enumerate(company_list): email,phone = get_info(company) ws.cell(row=i+2, column=1, value=company) ws.cell(row=i+2, column=2, value=email) ws.cell(row=i+2, column=3, value=phone) # 保存Excel文件 wb.save('company_info.xlsx') if name == 'main': file_path = 'company_names.xlsx' company_list = read_from_excel(file_path) write_to_excel(company_list) 此段代码定位天眼查的公司电话失败，帮助我重新写一遍代码，能够正确定位天眼查公司电话邮箱

from bs4 import BeautifulSoup import openpyxl from time import sleep # 设置请求头，模拟浏览器访问 headers = { 'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like...

import requestsfrom bs4 import BeautifulSoup# 发送 GET 请求获取网页内容url = 'https://buff.163.com/market/goods?goods_id=35864&from=market#tab=selling'res = requests.get(url)# 使用 BeautifulSoup 解析 HTMLsoup = BeautifulSoup(res.text, 'html.parser')# 查找手套武器箱价格并打印price = soup.find('span', {'class': 'price'}).textprint('手套武器箱价格为：' + price)

这段代码的问题在于第一行 import requestsfrom bs4 import BeautifulSoup，requests 和 bs4 库的导入应该在两行中分开导入，即应该写成： python import requests from bs4 import BeautifulSoup # 发送...

import os import requests from bs4 import BeautifulSoup # 定义函数，下载图片并保存到指定目录下 def download_img(img_url, path): response = requests.get(img_url) with open(path, 'wb') as f: f.write(response.content) # 论坛模块链接 url = 'https://bbs.zol.com.cn/dcbbs/d15.html' # 发送请求 response = requests.get(url) # 解析页面 soup = BeautifulSoup(response.text, 'html.parser') # 找到所有帖子的链接 post_links = soup.select('.post-td a') # 遍历所有帖子链接 for post_link in post_links: post_url = post_link['href'] post_response = requests.get(post_url) post_soup = BeautifulSoup(post_response.text, 'html.parser') # 找到帖子标题 post_title = post_soup.select('.post-title a')[0].text.strip() # 创建以帖子标题为名字的文件夹 folder_path = os.path.join(os.getcwd(), post_title) if not os.path.exists(folder_path): os.makedirs(folder_path) # 找到帖子中所有图片链接 img_links = post_soup.select('.post-text img') # 遍历所有图片链接，下载并保存到文件夹中 for i, img_link in enumerate(img_links): img_url = img_link['src'] img_path = os.path.join(folder_path, f'{i}.jpg') download_img(img_url, img_path)报错修改C:\ProgramData\Anaconda3\lib\site-packages\urllib3\connection.py:329: SystemTimeWarning: System time is way off (before 2019-01-01). This will probably lead to SSL verification errors warnings.warn(

如果你使用的是Anaconda环境，可以尝试打开Anaconda Prompt，使用以下命令来更新conda的环境： conda update --all 如果还是无法解决问题，可以尝试升级urllib3库到最新版本： pip install --upgrade...

解释下列代码import requests from bs4 import BeautifulSoup import os def download_file(url, filename): r = requests.get(url, stream=True) with open(filename, 'wb') as f: for chunk in r.iter_content(chunk_size=1024): if chunk: f.write(chunk) if name == 'main': root_url = 'https://www.xuekewang.com/' subject_url = 'https://www.xuekewang.com/subject/' subject_list = ['xl', 'yw', 'sx', 'yy', 'wl', 'hx', 'zz'] for subject in subject_list: # 创建保存文件夹 save_path = 'C:/Users/用户名/Desktop/学科网/' if not os.path.exists(save_path): os.makedirs(save_path) # 获取网页源代码并用 BeautifulSoup 解析 response = requests.get(subject_url + subject + '/') soup = BeautifulSoup(response.content, 'html.parser') # 找到所有的资源链接并下载 for link in soup.find_all('a', {'class': 'down'}): resource_url = 'https://www.zxxk.com/soft/39428339.html' resource_name = '生物' # 可以自定义资源文件名 download_file(resource_url, save_path + resource_name) print(subject + ' 课程下载完成！')

1. 首先导入必要的模块：requests用于发送HTTP请求，bs4用于解析HTML，os用于操作文件系统。 2. 定义了一个下载文件的函数download_file，接收两个参数：要下载的文件的URL和下载后保存的文件名。函数内部使用...

爬取该网址的图书封面信息import requestsfrom bs4 import BeautifulSoupurl = 'https://book.douban.com/subject/36321306/'response = requests.get(url)soup = BeautifulSoup(response.text, 'html.parser')img = soup.select_one('.nbg img')img_url = img['src']with open('book_cover.jpg', 'wb') as f: f.write(requests.get(img_url).content)

from bs4 import BeautifulSoup url = 'https://book.douban.com/subject/36321306/' response = requests.get(url) soup = BeautifulSoup(response.text, 'html.parser') img = soup.select_one('.nbg img') img_...

修改代码，使得li_list的编码格式是utf-8import requests from bs4 import BeautifulSoup url = 'https://www.icbc.com.cn/page/827855918799994880.html' response = requests.get(url=url) page_response = response.text soup = BeautifulSoup(page_response, 'html.parser',from_encoding='utf-8') li_list = soup.select('#mypagehtmlcontent p')

from bs4 import BeautifulSoup url = 'https://www.icbc.com.cn/page/827855918799994880.html' response = requests.get(url=url) page_response = response.content.decode('utf-8') soup = BeautifulSoup(page_...

import requests from bs4 import BeautifulSoup import csv def crawl_news_websites(url): response = requests.get(url)#get url soup = BeautifulSoup(response.text, 'html.parser')#创建 beautifulsoup 对象# 'html.parser' 指定解析器 websites = soup.find_all('a', class_='link')#查找节点 #find_all会将所有满足条件的值取出，组成一个list results = [] for website in websites: site_name = website.text site_url = website['href'] results.append((site_name, site_url)) return results def save_to_csv(results): with open('news_websites.csv', 'w', newline='', encoding='utf-8') as csvfile: writer = csv.writer(csvfile) writer.writerow(['Website Name', 'Website URL']) writer.writerows(results) if name == 'main': url = 'http://www.hao123.com/newswangzhi' news_websites = crawl_news_websites(url)

这段代码是用 Python 实现了一个爬虫程序，用于爬取指定网址中的新闻网站名称和链接，并将结果保存在一个名为 "news_websites.csv" 的文件中。其中，程序使用了 requests 库发送 HTTP 请求，BeautifulSoup 库对 ...

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