Java vs. Python Performance Comparison: Java/Python Agent Performance Testing

I. Who is more suitable for proxy testing between these two languages?

Let's be honest: Java and Python are like a drill and a screwdriver when it comes to proxy testing; Java is naturally suited forHigh-intensity concurrent requestsIf you want to measure the availability of hundreds of proxies at the same time, that's really its home turf. Python, on the other hand, is faster at writing scripts, so if you want to measure 10 or 20 proxies at the same time, you can run them in two lines of code.

To give a real scene: two days ago to help customers with ipipgo API batch pull proxy IP, take the detection program written in Java, 20 seconds to sweep through the connectivity of 1000 IP, the memory ate fast 1 G. Change the Python rewrite a version of the speed of 8 seconds slower, the memory is saved in half. This is to see the doorway -Python is easy to use, but Java has to carry the load.The

Second, hand to teach you to write test scripts

Let's use ipipgo's HTTP proxy as a demo and see how Java plays first:

// Proxy detection for Java
HttpClient client = HttpClient.newBuilder()
    .proxy(ProxySelector.of(new InetSocketAddress("proxy IP", port)))
    .build();
HttpRequest request = HttpRequest.newBuilder()
    .uri(URI.create("https://ipipgo.com/check"))
    .timeout(Duration.ofSeconds(5))
    .timeout(Duration.ofSeconds(5))
long start = System.currentTimeMillis();
HttpResponse response = client.send(request, BodyHandlers.ofString());
System.out.println("Response time: " + (System.currentTimeMillis()-start)+"ms");;

The Python version is simpler:

 Proxy detection in Python
import requests
proxies = {'http': 'http://用户名:密码@proxyIP:port'}
start = time.time()
resp = requests.get('https://ipipgo.com/check', proxies=proxies, timeout=5)
print(f "Time taken: {time.time()-start:.2f} seconds")

Third, the actual test data revealed

Took ipipgo's dynamic residential proxy and did three rounds of testing (100 requests each):

Java eats memory, but has a solid processing speed.Small-scale testingThe advantage is obvious when it comes to requests, but when the volume of requests goes up, that CPU spikes like a rocket.

Fourth, how to choose so as not to step on the pit?

Based on our experience in doing programs for clients, give aFool's Choice::

1. Proxy IP to be measured more than 500/day → Close your eyes and select Java
2. need timed tasks/distributed testing → Java not running
3. Ad hoc spot checks/small-scale validation → Python really smells good
4. both speed and saving → on ipipgo client (their one-click speed test is really convenient)

V. QA time for veteran drivers

Q: What should I do if the proxy IP always times out during testing?
A: first do not rush to change the language, eighty percent of the agent quality is not good. Suggest to change ipipgoExclusive use of static homespackage, the stability can mention 40% or more.

Q: The test program is always blocked by the target website?
A: When using a dynamic residential proxy, remember to add a random UA to the request header. ipipgo's Enterprise package comes with arequest header masquerading asfunction and save a lot of work.

Q: What's wrong with fast and slow test results?
A: 80% of them are using a shared proxy pool. Switch to ipipgo'sTK LineThe latency can be stabilized within 300ms, which is more than 2 times faster than normal lines in real life.

One last piece of solid advice: don't beat yourself to death over your language choice.Agent quality is king. It's like putting 92 gasoline in your sports car, even the best engine won't perform. Make sure you use a reliable service provider like ipipgo before you test, and you'll save enough debugging time to learn a new language.