Walmart Dataset: Merchandise Data CSV Download

Why do I need a proxy IP for Walmart product data collection?

Friends of the data know that crawling Walmart and other large platforms of product information is like playing a game of whack-a-mole. You just grabbed two pages of data, the IP address will be hammered into the "dark room". At this time, if you use ipipgo's proxy IP, equivalent to having countless "gamepad" at the same time, this is blocked immediately change the next one, data collection simply can not stop.

Take a real scenario: Xiao Wang to analyze the price trend of 5000 electronic products, using their own network alone just climbed to the third page on the prompt "frequent visits". After switching to ipipgo's dynamic residential IP.Automatically switch real user IPs from different regions per requestNot only did you successfully capture the data, but you were also able to access the pricing differences between different regions.

Hands-on with proxy IP to download CSVs

Here is an example of Python to demonstrate how to get proxy IP for data collection through ipipgo's API:

import requests
from itertools import cycle

 API key from ipipgo backend
API_KEY = "your_ipipgo_key"
PROXY_URL = f "http://api.ipipgo.com/get?key={API_KEY}&type=json"

 Get 10 dynamic residential IPs
proxy_list = requests.get(PROXY_URL).json()['data']
proxy_pool = cycle(proxy_list)

 Masquerade as a normal browser visit
headers = {
    'User-Agent': 'Mozilla/5.0 (Windows NT 10.0) AppleWebKit/537.36'
}

for page in range(1, 101):: { 'User-Agent'.
     Automatically change the proxy for each request
    current_proxy = next(proxy_pool)
    proxies = {
        "http": f "http://{current_proxy}",
        "https": f "http://{current_proxy}"
    }

     Catch the product listings page
    url = f "https://www.walmart.com/api/products?page={page}"
    response = requests.get(url, headers=headers, proxies=proxies, timeout=10)

     Process the data and save the CSV...
    print(f "Successfully crawled page {page} data, using proxy IP: {current_proxy}")

Key Notes:

Common Potholes and Lightning Avoidance Guide

Three common mistakes newbies make:

1. Brush furiously with data center IPs - this type of server room IP is particularly easy to identify
2. Forgetting to set the User-Agent - it's as conspicuous as strolling around with no clothes on!
3. Continuous requests without breaks - even the best IP can't handle machine-gun fire

A previous client used a free proxy and ended up with fake prices from competitors mixed in with the data. Then they switched to ipipgo.Exclusive Enterprise Agent, the data accuracy is pulled right up to 98% or more.

QA time: what you might want to ask

Q: Is it troublesome to change the agent manually every time?
A: ipipgo's intelligent rotation mode can automatically switch IPs, just set the switching rules in the background (e.g. change every 5 requests)

Q: Why do you recommend residential agents?
A: Walmart's anti-crawl system is more friendly to residential IPs, especially home broadband IPs, which survive 3-5 times longer than server room IPs

Q: Can I still use my blocked IP?
A: ipipgo's proxy pool will automatically filter abnormal IPs and replenish new IPs within the package, so you don't have to worry about it at all!

Upgraded play: data collection + analysis in a single package

With ipipgo.Geographic orientationfunction, you can specialize in grabbing the product data of a specific region. For example, if you want to compare the price of electronics in New York and Los Angeles, you just need to set it in the background:

• U.S. West IP: Catching California Regional Pricing
• U.S. East IP: Get local New York promotions

The CSV data collected in this way comes with regional labels and is directly filtered by geographic location when doing market analysis, doubling the value of the original data.

Lastly, a nagging word: do not be greedy and cheap with those public proxy pool, before we test found that the success rate of the free proxy even 20% are less than. ipipgo new users haveTry 500MB of traffic for $1activities, it's more comfortable to try before you buy.