Preface
Take a recently discovered free proxy IP website as an example: http://www.xicidaili.com/nn/. When using it, I found that many IPs cannot be used.
So I wrote a script in Python, which can detect the available proxy IPs.
The script is as follows:
#encoding=utf8 import urllib2 from bs4 import BeautifulSoup import urllib import socket User_Agent = 'Mozilla/5.0 (Windows NT 6.3; WOW64; rv:43.0) Gecko/20100101 Firefox/43.0' header = {} header['User-Agent'] = User_Agent ''' 获取所有代理IP地址 ''' def getProxyIp(): proxy = [] for i in range(1,2): try: url = 'http://www.xicidaili.com/nn/'+str(i) req = urllib2.Request(url,headers=header) res = urllib2.urlopen(req).read() soup = BeautifulSoup(res) ips = soup.findAll('tr') for x in range(1,len(ips)): ip = ips[x] tds = ip.findAll("td") ip_temp = tds[1].contents[0]+"\t"+tds[2].contents[0] proxy.append(ip_temp) except: continue return proxy ''' 验证获得的代理IP地址是否可用 ''' def validateIp(proxy): url = "http://ip.chinaz.com/getip.aspx" f = open("E:\ip.txt","w") socket.setdefaulttimeout(3) for i in range(0,len(proxy)): try: ip = proxy[i].strip().split("\t") proxy_host = "http://"+ip[0]+":"+ip[1] proxy_temp = {"http":proxy_host} res = urllib.urlopen(url,proxies=proxy_temp).read() f.write(proxy[i]+'\n') print proxy[i] except Exception,e: continue f.close() if __name__ == '__main__': proxy = getProxyIp() validateIp(proxy)
After running successfully, open the file under E drive, you can see the following available Proxy IP address and port:
Summary
This is just the first page crawled IP address, if necessary, you can crawl a few more pages. At the same time, the website is updated from time to time, so it is recommended to only crawl the first few pages when crawling. The above is the entire content of this article. I hope it will be helpful to everyone learning to use Python.
For more articles related to proxy IPs available for Python crawling, please pay attention to the PHP Chinese website!

Python and C each have their own advantages, and the choice should be based on project requirements. 1) Python is suitable for rapid development and data processing due to its concise syntax and dynamic typing. 2)C is suitable for high performance and system programming due to its static typing and manual memory management.

Choosing Python or C depends on project requirements: 1) If you need rapid development, data processing and prototype design, choose Python; 2) If you need high performance, low latency and close hardware control, choose C.

By investing 2 hours of Python learning every day, you can effectively improve your programming skills. 1. Learn new knowledge: read documents or watch tutorials. 2. Practice: Write code and complete exercises. 3. Review: Consolidate the content you have learned. 4. Project practice: Apply what you have learned in actual projects. Such a structured learning plan can help you systematically master Python and achieve career goals.

Methods to learn Python efficiently within two hours include: 1. Review the basic knowledge and ensure that you are familiar with Python installation and basic syntax; 2. Understand the core concepts of Python, such as variables, lists, functions, etc.; 3. Master basic and advanced usage by using examples; 4. Learn common errors and debugging techniques; 5. Apply performance optimization and best practices, such as using list comprehensions and following the PEP8 style guide.

Python is suitable for beginners and data science, and C is suitable for system programming and game development. 1. Python is simple and easy to use, suitable for data science and web development. 2.C provides high performance and control, suitable for game development and system programming. The choice should be based on project needs and personal interests.

Python is more suitable for data science and rapid development, while C is more suitable for high performance and system programming. 1. Python syntax is concise and easy to learn, suitable for data processing and scientific computing. 2.C has complex syntax but excellent performance and is often used in game development and system programming.

It is feasible to invest two hours a day to learn Python. 1. Learn new knowledge: Learn new concepts in one hour, such as lists and dictionaries. 2. Practice and exercises: Use one hour to perform programming exercises, such as writing small programs. Through reasonable planning and perseverance, you can master the core concepts of Python in a short time.

Python is easier to learn and use, while C is more powerful but complex. 1. Python syntax is concise and suitable for beginners. Dynamic typing and automatic memory management make it easy to use, but may cause runtime errors. 2.C provides low-level control and advanced features, suitable for high-performance applications, but has a high learning threshold and requires manual memory and type safety management.


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