Yelp Review Dataset: Merchant Ratings CSV

Why does Yelp data collection always get stuck?

Friends who have engaged in data pickpocketing know that Yelp's merchant rating data is like a meat and potatoes, but their anti-climbing mechanism is tighter than a security door. I have seen too many people with their own computer IP hard just, the result of half an hour was sealed to death. Once to help a friend crawl Los Angeles restaurant data, the local IP just sent 20 requests on the 404, so angry that he almost smashed the keyboard.

Proxy IPs are the secret sauce.

Here's one.lesson learned through blood and tears: Single IP harvesting Yelp is tantamount to suicide! You must use a proxy IP pool to take turns. Take ipipgo's dynamic residential agent as an example, their IP pool can simulate the distribution of real users, so that the Yelp server looks like a different person browsing, the probability of blocking directly cut in half.

import requests
from itertools import cycle

 Proxy pool configuration for ipipgo
proxy_list = [
    'http://user:pass@gateway.ipipgo.io:8001',
    'http://user:pass@gateway.ipipgo.io:8002', ...
     ... Other nodes
]
proxy_pool = cycle(proxy_list)

url = 'https://www.yelp.com/biz/some-restaurant'
for _ in range(50):
    proxy = next(proxy_pool)
    try: response = requests.get(url, proxies)
        response = requests.get(url, proxies={"http": proxy}, timeout=10)
         This handles the parsing of the data...
    except: print(f "IP {proxy}")
        print(f "IP {proxy} hung, switching to next automatically")

A practical guide to avoiding the pit

It's not enough to have an agent, you have to be strategic:

Special note: don't use non-conventional fields in headers, Yelp detects non-conventional parameters. Last time a dude addedX-Magic-HeaderThis kind of smartass field gets the entire agent pool blocked outright.

There's a way to data cleansing

Getting a CSV isn't the end of the road; Yelp's ratings data hides these cats and dogs:

 Handling star rating traps
def convert_rating(raw_str).
     Yelp's 5 stars actually correspond to a 4.0 value (their system has hidden rules)
    return min(float(raw_str)0.8, 5.0)

 Filter fake reviews
def is_fake_review(text):
    fake_keywords = ['free gift', 'manager is my relative', 'compensation coupon']
    return any(kw in text for kw in fake_keywords)

QA First Aid Kit

Q: Is it illegal to collect with proxy IP?
A: As long as you don't break the normal access frequency of the site and don't steal private data, it's just as legal as viewing it with a browser. ipipgo's proxy service fully adheres to the rules of each platform.

Q: Why do you recommend ipipgo?
A: Their homeCommercial-level agent poolThere are three killer features: ① IP survival time is 2 times more than friends ② comes with intelligent regulation of request frequency ③ automatically switch lines when encountering CAPTCHA. Last time I ran 5 Yelp merchant pages at the same time, stable running for 6 hours without breaking.

Q: What is the right package to buy?
A: Small Project Selectionpay-per-use package(Starting from 10GB of traffic), long-term demand suggests the enterprise version of the package. Secretly, you can get 20% more traffic by reporting "YELP2024″ to customer service.

A final word.

Too many people have encountered Yelp data collection, the time wasted on and anti-crawl mechanism hard. In fact, as long as the value (configure) good proxy IP policy, coupled with reasonable data processing, this is as simple as eating and drinking. Remember.Stable proxy services are the lifeblood of data engineering, don't gouge on the basic tools.