Bypassing IPs with Residential Proxies and Web Crawlers: Solving the Data Collection Challenge

[Soren]

Have you ever wondered if there is a way to find all the information you need and help you make more money? Web Crawler (Web Crawler) is such an amazing tool. Not only is it able to systematically browse and crawl huge amounts of data on the Internet, but it can also provide you with endless business opportunities. Whether it's real-time access to pricing information on e-commerce websites or monitoring competitors' movements, Web Crawler can drastically improve your data collection efficiency and help you gain an edge over your competition.

##What is a web crawler? What can it do?
A Web Crawler, also known as a Web Spider, Web Robot, or Automatic Indexer, is an automated script or programme used to systematically browse and Web Scraping the content of web pages on the Internet.
Simply put, a web crawler is like a robot. By simply setting a set of rules, it can automatically browse web pages according to those rules and collect all kinds of data it needs, thus greatly saving labour costs.
The web crawler can traverse all airline websites to help users find the cheapest tickets. It can also crawl data in real time in areas such as e-commerce, healthcare and real estate. In addition to Web Scraping, Web Crawler is able to send data to help users book tickets and log in to various platforms. It can also analyse hot topics of public discussion or collect stock market data to aid investment decisions. The market value of these industries has reached billions of dollars.
As an important part of the search engine, the primary function of the crawler is to crawl the web data. Currently popular collector software on the market are using the principle or function of web crawlers.
Many companies have realised significant business benefits by using web crawler technology, not only to improve the efficiency of data collection, but also to provide users with high-quality information services. So, how to apply this technology to our projects?

##How do I make money with web crawlers?
The value of a web crawler is really the value of data. Firstly imagine you are a reseller or e-commerce seller who needs to compete with hundreds of competitors. Price and inventory are your main competitive advantages. Having access to real-time information and being able to adjust prices when competitors drop prices or run out of stock can lead to significant gains. But most companies will prevent you from accessing the information, and even if an API is provided, you may run into problems with rate limits, outdated information, and other issues that can undermine the system's relevance. Therefore, you need to build a web crawler to handle it for you.
And reptiles can also bring in revenue in the following industries:
Looking for reptile outsourcing jobs
The most usual way of earning money for Web Scraping is through outsourcing websites, doing small and medium scale crawling projects, and providing services such as Web Scraping, data structuring, data cleaning, etc. to the A party. Most of the new programmers will try this direction first, directly rely on technical means to earn money, but also the best way for technicians, but due to too many competitors, the price may not be very expensive.
Grabbing data for a website
You can crawl the data through Python crawler to make a website to earn money, although the income is not very objective, but after making it does not need much maintenance, it is also considered to have passive income.
Working college students
If you are a working college student, mathematics or computer-related professionals, programming ability is okay, you can look a little programming knowledge, such as crawler libraries, HTML parsing, content storage, etc., complexity also need to understand the URL ranking, simulation of login, CAPTCHA identification, multi-threading, etc., this part of the personnel engineering experience is relatively small, want to make money through the crawler, then you can look for a small number of data capture If you want to make money through the crawler, you can find some small amount of data capture project, a little bit of experience, you can try to take some monitoring projects or large-scale capture project.
Incumbent
If you are engaged in Python web crawler work yourself, earning money is very simple. The incumbent is more familiar with the project development process, experienced in engineering, and can reasonably assess the difficulty, time, and expense of a task, so you can try to find some large-scale crawling tasks, monitoring tasks, mobile simulation login and crawling tasks, etc., and the earnings are very considerable.
##How to operate a web crawler in practice?
I found an automated web crawler that scans products on e-commerce marketplaces, automatically tracks price changes, and alerts us to make adjustments to take advantage of opportunities. Using popular frameworks like DrissionPage, I visit websites, scan for products, parse the HTML, get the price and store it in a database, and then see if the price has changed.
I set time intervals to run the scanner automatically, every day, every hour or every minute on demand. As you can see I have a product search tool that analyses e-commerce prices and automatically grabs products on Amazon every day. I can enable or disable product tracking, add new products and view prices.
Operating this automated web crawler in PyCharm is very simple. Firstly, you need to download PyCharm and create a new project and make sure you choose to create a new Porfiles.
Next, activate the virtual Porfiles in PyCharm's terminal and run

pip install

DrissionPageto

install the required packages. Then, right-click on the project directory and select

New > Python File

to create a new Python file (e.g.

main.py

), copying and pasting the above code into the file. Finally, right-click on the main.py file and select Run 'main' or use the shortcut keys

Shift + F10

to run the script to see the results in the terminal and find the generated

data.json

file and

scraper.log

log file in the project directory.

[code]import time
from DrissionPage import ChromiumOptions
from DrissionPage import WebPage
import json
import logging
# Configure logging
logging.basicConfig(filename='scraper.log', level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
try:
    co=ChromiumOptions()
    co.headless()
    page=WebPage(chromium_options=co)
    page.get("https://www.amazon.com/")
    page.ele("#twotabsearchtextbox").click()
    keyword=input("Please enter a keyword and press Enter: ")
    page.ele("#twotabsearchtextbox").input(keyword)
    page.ele("#nav-search-submit-button").click()
    goods_eles=page.eles('xpath://*[@id=search]/div[1]/div[1]/div/span[1]/div[1]/div')
    logging.info("Starting data scraping...")
    data=[]
    for goods_ele in goods_eles:
        if not goods_ele.attrs['data-asin]:
            continue
        goods_name=goods_ele.ele('xpath://h2/a/span').text
        goods_href=goods_ele.ele('xpath://h2/a').link
        goods_price_ele=goods_ele.eles('xpath:/div/div/span/div/div/div[2]/div/div/span[2]')
        if len(goods_price_ele) == 1:
            goods_price=goods_price_ele[0].text
        elif len(goods_price_ele) > 1:
            goods_price=goods_price_ele[1].text
        else:
            continue
        if '$' not in goods_price:
            continue
        logging.info(f"Product Name: {goods_name}")
        logging.info(f"Product Price: {goods_price}")
        logging.info(f"Product Link: {goods_href}")
        logging.info('= * 30)
        data.append({
            "name": goods_name,
            "price": goods_price,
            "link": goods_href
        })
    logging.info('Data scraping completed')
    # Save data to file
    with open("data.json", "w", encoding="utf-8") as f:
        json.dump(data, f, ensure_ascii=False, indent=4)
    logging.info("Data has been saved to data.json")
except Exception as e:
    logging.error("An error occurred:", exc_info=True)

[/code]
After PyCharm clicks Run.
Enter keywords: You entered the keywords to be searched.
Data collection: the script searches and collects product information related to keywords on Amazon.com.
*Data saving: The collected data is saved in the

data.json

file and the log information is saved in the

scraper.log

file.
Here's an example using crawling bracelets in amazon:

Click on the image to see the product details.
But the crawler will often get blocked by the site while I'm running it, so what should I do about it?

##Challenges and countermeasures for web crawlers: how to crawl without being blocked?
Every time I try, many sites are smart enough to detect bots, they have CAPTCHA and prevent you from crawling the data. They have anti-crawler tactics like IP blocking, CAPTCHA, these "barriers" affect the efficiency of crawling and making money. After many attempts, the site is blocked. What is the solution to this problem?
This time you can make use of the Residential Proxies to operate, the principle of Proxies is very simple, we crawl the site when there will be a request to send to the server, we directly access the time, the server will know our IP address, the number of visits too many times will be banned, but we can first send to the Proxy Service, by the Proxy Service to help us to send a request. So that the site being crawled will not know what our IP is.

Here I recommend PROXY.CC, which I've been using for a long time. It has three types of proxies: Rotating Residential Proxies, Static Residential Proxies, and Unlimited Traffic Proxies:
Rotating Residential Proxies are Rotating Proxies where each Residential IP is a selectable country and city, which can help users with precise geolocation and information access efficiently and Securely. Static Residential Proxies provide fixed real residential IPs to ensure that users use the same IPs for a long time, improve access stability and security, and hide users' real IPs.
Unlimited Traffic Proxies will provide unlimited traffic to Residential Proxies for efficient and Secure Proxies to access information and ensure that the user's real IP is hidden. Very suitable for high traffic tasks, if you need to do large-scale data crawling and automated testing and if there is no requirement for the location of the country/city, this package is highly recommended, he will significantly reduce the cost of per-flow billing.
It can it automatically unlock websites, connect to Proxies, rotate your IP address, resolve CAPTCHA, and make you hassle-free web crawler.PROXY Web Scraping.
It also allows unlimited concurrent sessions, meaning that hundreds of crawler instances can be run at the same time, not limited to a single or local machine processing. If you want to know more about PROXY.CC, you can click the link to check it out and experience the powerful features of PROXY.CC. You can also get 500MB of free traffic for the first registration by contacting customer service.PROXY.CC Residential Proxies Tutorials
I purchased Residential Proxies here, just add the content of the generated Proxies in this place, I am using API Extraction, the extraction result is assumed to be [5.78.24.25:23300].
Original code:

[code]    co=ChromiumOptions()
    co.headless()
    page=WebPage(chromium_options=co)
    page.get("https://www.amazon.com/")
    page.ele("#twotabsearchtextbox").click()
    keyword=input("Please enter a keyword and press Enter: ")
    page.ele("#twotabsearchtextbox").input(keyword)
    page.ele("#nav-search-submit-button").click()
    goods_eles=page.eles('xpath://*[@id=search]/div[1]/div[1]/div/span[1]/div[1]/div')
    logging.info("Starting data scraping...")

[/code]
Code after adding Proxies:

[code]co=ChromiumOptions()
co.headless()
# co.set_proxy("http://5.78.24.25:23300")
page=WebPage(chromium_options=co)
# page.get("https://api.ip.cc/")
page.get("https://www.amazon.com/")
# time.sleep(5)
# page.get("https://www.amazon.com/s?k=fender+guitar")
# print(page.html)
page.ele("#twotabsearchtextbox").click()
keyword=input("Please enter a keyword and press Enter: ")
page.ele("#twotabsearchtextbox").input(keyword)
page.ele("#nav-search-submit-button").click()
goods_eles=page.eles('xpath://*[@id=search]/div[1]/div[1]/div/span[1]/div[1]/div')
print("Starting data scraping...")

[/code]

##Conclusion
In practice, web crawler technology has helped many enterprises and individuals to automate data collection, improve work efficiency, and save a lot of time and cost. However, the crawler often encounters anti-crawling measures of websites during operation, such as IP blocking and CAPTCHA authentication. At this point, Residential Proxies such as PROXY.CC can be used to solve these problems. Through Proxy Service, crawlers can hide their real IPs to avoid being blocked and thus carry out data collection smoothly.PROXY.CC provides various Proxy Modes, such as Rotating Residential Proxies, Static Residential Proxies, and Unlimited Traffic Proxies, to meet the needs of different users. Proxies with unlimited traffic can significantly reduce the cost, especially for users who need to capture large-scale data.