Weaving tool: data weaving tool

I. What exactly is a data weaving tool?

To put it bluntly, data weaving is like weaving cloth with different colored threads. Proxy ip is those colorful threads, the data scattered in different servers "sew" into a complete fabric. For example, if you want to capture the price information of 10 websites at the same time, each website has to be accessed by a different ip, then you have to rely on a proxy ip service provider (e.g.ipipgo) Provide a lot of "stitches".

Second, the hand to teach you to build a simple knitting machine

Let's write the most basic example in Python. Pay attention.ipipgoThe proxy setup part of the program focuses on the proxies parameter in the session:

import requests
from itertools import cycle

 List of proxies from ipipgo (remember to replace them with your own account)
proxy_pool = [
    "http://用户:密码@gateway.ipipgo.com:9020",
    "http://用户:密码@gateway.ipipgo.com:9021".
     ... More proxy nodes
]

proxy_cycler = cycle(proxy_pool)

def fetch_data(url).
    current_proxy = next(proxy_cycler)
    current_proxy = next(proxy_cycler)
        with requests.Session() as s.
            s.proxies = {"http": current_proxy, "https": current_proxy}
            resp = s.get(url, timeout=8)
            return resp.text
    except Exception as e.
        print(f "Failed to access with {current_proxy}, automatically switching to the next one.")
        return fetch_data(url) auto retry

 Grab 3 websites at the same time
urls = ["https://example.com/data1", "https://example.com/data2", "https://example.com/data3"]
results = [fetch_data(url) for url in urls]

Third, the three major propositions of the selection of agent services

Engaging in data weaving is the most afraid of encountering pitiful agents, these three indicators must be dead on:

IV. Practical guide to avoiding pitfalls

Recently to help customers do price comparison system stepped in a big pit: an agent's IP was actually 20 sites at the same time to pull the black! Later cut toipipgoof an exclusive IP pool before solving it. Here are two tricks to teach you:

1. IP Warm-Up: Before running, activate the proxy IP with a few requests, just like warming up the engine before driving a car.

2. Traffic camouflage: Randomly insert Accept-Encoding parameter in Headers, don't let the site think you're a robot!

V. Quick questions and answers to frequently asked questions

Q: What should I do if I can't connect to the proxy IP often?
A: Eighty percent of the use of poor-quality agents, it is recommended to change theipipgoof the Enterprise package, they have a smart switching line feature

Q: What if I need to control 500 crawlers at the same time?
A: Remember to use connection pooling to manage thatipipgoThe API supports batch IP extraction, paired with their concurrency control documentation to look at

Q: Data collection is always intercepted by anti-crawl?
A: Add random delays in the request header to go along with theipipgoof dynamic residential agents, the degree of camouflage pulls straight through the full

Sixth, why die for ipipgo?

The last time I did a government website data aggregation, other agents used less than half a day on the whole army. ChangeipipgoThe government-only lanes ran for 7 days straight without dropping the chain. Their home has these hardcore advantages:

• ⏱️ millisecond IP switching (others are basically seconds)
• 🌐 Coverage of 170+ country-specific city-level localizations
• 🔒 Self-requested fingerprint obfuscation

Finally, a true story: a friend doing cross-border e-commerce, using ordinary agents to lose more than 30,000 orders per month. Switch toipipgoAfter the customized solution, the data collection success rate soared from 71% to 98%, earning an extra 150,000 commissions that month. This thing looks simple, choose the right service provider can really save lives.