from bs4 import BeautifulSoup
import requests,re,os,socket
from urllib import request
element_ui_version = "2.15.13"
element_ui_dir = "D:/tmp"
save_ui_dir = os.path.join(element_ui_dir,"element-ui")
if not os.path.isdir(save_ui_dir):
os.makedirs(save_ui_dir)
element_ui_url = "https://unpkg.com/browse/element-ui@" + element_ui_version + "/"
headers = {
"User-Agent":"Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:73.0) Gecko/20100101 Firefox/73.0"
}
def get_page(url,save_dir):
print("Current Page: ",url)
response = requests.get(url,headers=headers)
soup = BeautifulSoup(str(response.content), "lxml")
tbody = soup.find("tbody")
rule_name = r'href="(.+?)"'
td_href = re.findall(rule_name,str(tbody))
dir_list = []
for href in td_href:
href_path = os.path.join(save_dir, href)
if href == "../":
pass
elif "/" in href:
os.mkdir(href_path)
print("Makedir: ",href_path.replace(save_ui_dir,""))
dir_list.append(href)
else:
file_url = url + href
abs_name = file_url.replace(element_ui_url, "")
print("Download: ", abs_name)
get_file(file_url,href_path)
for sub_dir in dir_list:
sub_url = url + sub_dir
sub_dir = os.path.join(save_dir,sub_dir)
get_page(sub_url,sub_dir)
def get_file(url,filename):
opener =request.build_opener()
opener.addheaders = [('User-agent', 'Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:73.0) Gecko/20100101 Firefox/73.0')]
request.install_opener(opener)
socket.setdefaulttimeout(30)
url = url.replace("browse/","")
count = 1
while count <= 5:
try:
request.urlretrieve(url, filename)
break
except socket.timeout:
err_info = '<Timeout> Reloading for %d time' % count
print(err_info)
count += 1
except Exception as e:
err_info = '<'+str(e)+'> Reloading for %d time' % count
print(err_info)
count += 1
if count > 5:
print("<Error> download job failed!")
else:
pass
get_page(element_ui_url,save_ui_dir)
【推荐】国内首个AI IDE,深度理解中文开发场景,立即下载体验Trae
【推荐】编程新体验,更懂你的AI,立即体验豆包MarsCode编程助手
【推荐】抖音旗下AI助手豆包,你的智能百科全书,全免费不限次数
【推荐】轻量又高性能的 SSH 工具 IShell:AI 加持,快人一步
· 物流快递公司核心技术能力-地址解析分单基础技术分享
· 单线程的Redis速度为什么快?
· 展开说说关于C#中ORM框架的用法!
· Pantheons:用 TypeScript 打造主流大模型对话的一站式集成库
· SQL Server 2025 AI相关能力初探