webpage = tableRow.find('a').get('href') except: webpage = None 也有可能出现公司网站未显示的情况,因此我们可以使用try except条件,以防万一找不到网址。 一旦我们将所有数据保存到变量中,我们可以在循环中将每个结果添加到列表rows。 # write each result to rows rows.append([rank, company, webpage...
代码运行次数:36 importrequestsfrombs4importBeautifulSoup# 使用Requests获取网页内容url='http://example.com'# 替换为目标网站的URLresponse=requests.get(url)web_content=response.text# 使用BeautifulSoup解析HTMLsoup=BeautifulSoup(web_content,'html.parser')text=soup.get_text()# 提取网页的全部文本内容print(te...
def depth_first_search(start_url): from collections import deque visited = set() queue = deque() queue.append(start_url) while queue: url = queue.popleft() if url in visited: continue visited.add(url) for link in get_links(url): queue.appendleft(link) print(url) def breadth_first_s...
url = data[1].find('a').get('href') page = urllib.request.urlopen(url) # parse the html soup = BeautifulSoup(page, 'html.parser') # find the last result in the table and get the link try: tableRow = soup.find('table').f...
当我们打印状态时,我们得到的状态为 200,这意味着我们能够成功抓取亚马逊。您甚至可以打印我们从亚马逊收到的 HTML 代码,只需将status_code替换为text。 它看起来像这样。 如您所见,此数据根本不可读。我们需要从这个垃圾中解析出数据。为此,我们将使用BeautifulSoup。
1,webbrowser:Python 自带的,打开浏览器获取指定页面。(open) webbrowser.open('URL')#打开URL 2,requests:从因特网上下载文件和网页。(get status_code text raise_for_status iter_content) res = requests.get('URL')#获取网页或文件res.status_code#状态码res.text#获取的htmlres.raise_for_status()#检...
完整的源代码是：import requestsfrom bs4 import BeautifulSoupimport jsonfrom pandas import DataFrame as dfpage = requests.get("https://www.familydollar.com/locations/")soup = BeautifulSoup(page.text, 'html.parser')# find all state linksstate_list = soup.find_all(class_ = 'itemlist')state_...
``` # Python script for web scraping to extract data from a website import requests from bs4 import BeautifulSoup def scrape_data(url): response = requests.get(url) soup = BeautifulSoup(response.text, 'html.parser') # Your code here to extract relevant data from the website ``` 说明:...
importrequestsfrombs4importBeautifulSoupdefget_web_page(url):response=requests.get(url)ifresponse.status_code==200:returnresponse.textelse:returnNone 1. 2. 3. 4. 5. 6. 7. 8. 9. 然后,我们可以定义一个函数来爬取网页上的指定行内容,并将其保存到 TXT 文件中: ...
defget_image(self):"""Get the image from the prompt."""ifself.prompt =="":returnrx.window_alert("Prompt Empty") self.processing, self.complete =True,Falseyieldresponse = openai_client.images.generate( prompt=self.prompt, n=1, size="1024x1024") self.image_url = response.data[0].url...