Beautiful Soup Advanced Parsing Tips

First, use proxy IP to solve the pitfalls of dynamic loading

Many partners in the use of Beautiful Soup, the most headache is to encounter dynamically loaded web pages. For example, the price information of an e-commerce site is clearly visible in the browser, but when you use the script to capture it, there is nothing. At this time, do not be in a hurry to suspect that their code is written wrong - eighty percent of the site with asynchronous loading technology.

at this momentExclusive proxy IP for ipipgocan come in handy. With the requests set proxy parameters, the request is dispersed to different IP, can effectively bypass the site's anti-climbing strategy. To give a real case: there is a price comparison system customers, originally every collection of 100 times was blocked, replaced with ipipgo rotating proxy, continuous collection of 5000 times are as stable as the old dog.

Real-world code snippet:
"`python
proxies = {
'http': 'http://username:password@gateway.ipipgo.com:9020',
'https': 'http://username:password@gateway.ipipgo.com:9020'
}
response = requests.get(url, proxies=proxies)
soup = BeautifulSoup(response.text, 'lxml')
“`

II. The Ultimate Weapon Combination Against Counter-Climbing

Nowadays, many websites will detect traces of parser usage. Here to teach you three tricks:

Special note: ipipgo's residential proxies are highly effective in simulating the behavior of real people and are more than a notch more reliable than server room IPs.

Third, the correct posture of multi-threaded collection

When batch collection is needed, single-threaded efficiency can simply kill you in a hurry. With the concurrent.futures module with the agent pool, the speed directly take off. But pay attention to two points:

1. Each thread must use a separate IP
2. Control the number of concurrency not to crash the site

Here we highly recommend ipipgo's concurrency package, they specifically optimize the IP allocation mechanism for multi-threaded scenarios. The actual test with 10 threads continued to run for 1 hour, the success rate remains above 98%.

"`python
from concurrent.futures import ThreadPoolExecutor

def worker(url).
Get new IP from ipipgo
proxy = get_new_ip_from_ipipgo()
Implementation of acquisition tasks
return parse_data(url, proxy)

with ThreadPoolExecutor(max_workers=5) as executor:
results = executor.map(worker, url_list)
“`

IV. QA First Aid Kit

Q: Why is the content parsed with Beautiful Soup different from what the browser sees?
A: eighty percent encountered dynamic rendering, first proxy IP to obtain the complete source code, and then use soup.select () to locate the element

Q: How do ipipgo's agents choose their packages?
A：Small-scale collection choose to pay by volume, long-term projects with monthly packages more cost-effective, enterprise-level needs directly find customer service customization

Q: What should I do if I always extract empty data?
A: first check whether the trigger anti-climbing (change ipipgo's quality proxy to try), and then see whether the CSS selector is out of date

Fifth, the ultimate anti-sealing method

And finally, a trick: using ipipgo'sIP warm-up strategyThe new IP is first used with low frequency request to raise the number. New IP first with a low frequency request to raise the number, and slowly enhance to the normal collection frequency. Just like playing the game practicing trumpet, after raising the IP reputation value, the collection success rate is directly doubled.

Remember these three key numbers: no more than 500 requests per day from a single IP, random 2-5 second intervals between each request, and replacing 1/3 of the IP pool every week. Customers who follow this program have maintained a record of up to 11 consecutive months without being blocked.

(Note: Some of the tips in this article need to be realized with the enterprise version of ipipgo, individual users are recommended to start from the basic version first)