Ip Scraper
ScraperAPI – The Proxy API For Web Scraping
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Search engine scraping – Wikipedia
Search engine scraping is the process of harvesting URLs, descriptions, or other information from search engines such as Google, Bing, Yahoo, Petal or Sogou. This is a specific form of screen scraping or web scraping dedicated to search engines only.
Most commonly larger search engine optimization (SEO) providers depend on regularly scraping keywords from search engines, especially Google, Petal, Sogou to monitor the competitive position of their customers’ websites for relevant keywords or their indexing status.
Search engines like Google have implemented various forms of human detection to block any sort of automated access to their service, [1] in the intent of driving the users of scrapers towards buying their official APIs instead.
The process of entering a website and extracting data in an automated fashion is also often called “crawling”. Search engines like Google, Bing, Yahoo, Petal or Sogou get almost all their data from automated crawling bots.
Difficulties[edit]
Google is the by far largest search engine with most users in numbers as well as most revenue in creative advertisements, which makes Google the most important search engine to scrape for SEO related companies. [2]
Although Google does not take legal action against scraping, it uses a range of defensive methods that makes scraping their results a challenging task, even when the scraping tool is realistically spoofing a normal web browser:
Google is using a complex system of request rate limitation which can vary for each language, country, User-Agent as well as depending on the keywords or search parameters. The rate limitation can make it unpredictable when accessing a search engine automated as the behaviour patterns are not known to the outside developer or user.
Network and IP limitations are as well part of the scraping defense systems. Search engines can not easily be tricked by changing to another IP, while using proxies is a very important part in successful scraping. The diversity and abusive history of an IP is important as well.
Offending IPs and offending IP networks can easily be stored in a blacklist database to detect offenders much faster. The fact that most ISPs give dynamic IP addresses to customers requires that such automated bans be only temporary, to not block innocent users.
Behaviour based detection is the most difficult defense system. Search engines serve their pages to millions of users every day, this provides a large amount of behaviour information. A scraping script or bot is not behaving like a real user, aside from having non-typical access times, delays and session times the keywords being harvested might be related to each other or include unusual parameters. Google for example has a very sophisticated behaviour analyzation system, possibly using deep learning software to detect unusual patterns of access. It can detect unusual activity much faster than other search engines. [3]
HTML markup changes, depending on the methods used to harvest the content of a website even a small change in HTML data can render a scraping tool broken until it is updated.
General changes in detection systems. In the past years search engines have tightened their detection systems nearly month by month making it more and more difficult to reliable scrape as the developers need to experiment and adapt their code regularly. [4]
Detection[edit]
When search engine defense thinks an access might be automated the search engine can react differently.
The first layer of defense is a captcha page[5] where the user is prompted to verify they are a real person and not a bot or tool. Solving the captcha will create a cookie that permits access to the search engine again for a while. After about one day the captcha page is removed again.
The second layer of defense is a similar error page but without captcha, in such a case the user is completely blocked from using the search engine until the temporary block is lifted or the user changes their IP.
The third layer of defense is a long-term block of the entire network segment. Google has blocked large network blocks for months. This sort of block is likely triggered by an administrator and only happens if a scraping tool is sending a very high number of requests.
All these forms of detection may also happen to a normal user, especially users sharing the same IP address or network class (IPV4 ranges as well as IPv6 ranges).
Methods of scraping Google, Bing, Yahoo, Petal or Sogou[edit]
To scrape a search engine successfully the two major factors are time and amount.
The more keywords a user needs to scrape and the smaller the time for the job the more difficult scraping will be and the more developed a scraping script or tool needs to be.
Scraping scripts need to overcome a few technical challenges:[6]
IP rotation using Proxies (proxies should be unshared and not listed in blacklists)
Proper time management, time between keyword changes, pagination as well as correctly placed delays Effective longterm scraping rates can vary from only 3–5 requests (keywords or pages) per hour up to 100 and more per hour for each IP address / Proxy in use. The quality of IPs, methods of scraping, keywords requested and language/country requested can greatly affect the possible maximum rate.
Correct handling of URL parameters, cookies as well as HTTP headers to emulate a user with a typical browser[7]
HTML DOM parsing (extracting URLs, descriptions, ranking position, sitelinks and other relevant data from the HTML code)
Error handling, automated reaction on captcha or block pages and other unusual responses[8]
Captcha definition explained as mentioned above by[9]
An example of an open source scraping software which makes use of the above mentioned techniques is GoogleScraper. [7] This framework controls browsers over the DevTools Protocol and makes it hard for Google to detect that the browser is automated.
Programming languages[edit]
When developing a scraper for a search engine almost any programming language can be used. Although, depending on performance requirements, some languages will be favorable.
PHP is a commonly used language to write scraping scripts for websites or backend services, since it has powerful capabilities built-in (DOM parsers, libcURL); however, its memory usage is typically 10 times the factor of a similar C/C++ code. Ruby on Rails as well as Python are also frequently used to automated scraping jobs. For highest performance, C++ DOM parsers should be considered.
Additionally, bash scripting can be used together with cURL as a command line tool to scrape a search engine.
Tools and scripts[edit]
When developing a search engine scraper there are several existing tools and libraries available that can either be used, extended or just analyzed to learn from.
iMacros – A free browser automation toolkit that can be used for very small volume scraping from within a users browser [10]
cURL – a command line browser for automation and testing as well as a powerful open source HTTP interaction library available for a large range of programming languages. [11]
google-search – A Go package to scrape Google. [12]
SEO Tools Kit – Free Online Tools, Duckduckgo, Baidu, Petal, Sogou) by using proxies (socks4/5, proxy). The tool includes asynchronous networking support and is able to control real browsers to mitigate detection. [13]
se-scraper – Successor of SEO Tools Kit. Scrape search engines concurrently with different proxies. [14]
Legal[edit]
When scraping websites and services the legal part is often a big concern for companies, for web scraping it greatly depends on the country a scraping user/company is from as well as which data or website is being scraped. With many different court rulings all over the world. [15][16][17]
However, when it comes to scraping search engines the situation is different, search engines usually do not list intellectual property as they just repeat or summarize information they scraped from other websites.
The largest public known incident of a search engine being scraped happened in 2011 when Microsoft was caught scraping unknown keywords from Google for their own, rather new Bing service, [18] but even this incident did not result in a court case.
One possible reason might be that search engines like Google, Petal, Sogou are getting almost all their data by scraping millions of public reachable websites, also without reading and accepting those terms.
See also[edit]
Comparison of HTML parsers
References[edit]
^ “Automated queries – Search Console Help”. Retrieved 2017-04-02.
^ “Google Still World’s Most Popular Search Engine By Far, But Share Of Unique Searchers Dips Slightly”. 11 February 2013.
^ “Does Google know that I am using Tor Browser? “.
^ “Google Groups”.
^ “My computer is sending automated queries – reCAPTCHA Help”. Retrieved 2017-04-02.
^ “Scraping Google Ranks for Fun and Profit”.
^ a b “Python3 framework GoogleScraper”. scrapeulous.
^ Deniel Iblika (3 January 2018). “De Online Marketing Diensten van DoubleSmart”. DoubleSmart (in Dutch). Diensten. Retrieved 16 January 2019.
^ Jan Janssen (26 September 2019). “Online Marketing Services van SEO SNEL”. SEO SNEL (in Dutch). Services. Retrieved 26 September 2019.
^ “iMacros to extract google results”. Retrieved 2017-04-04.
^ “libcurl – the multiprotocol file transfer library”.
^ “A Go package to scrape Google” – via GitHub.
^ “Free online SEO Tools (like Google, Yandex, Bing, Duckduckgo,… ). Including asynchronous networking support. : NikolaiT/SEO Tools Kit”. 15 January 2019 – via GitHub.
^ Tschacher, Nikolai (2020-11-17), NikolaiT/se-scraper, retrieved 2020-11-19
^ “Is Web Scraping Legal? “. Icreon (blog).
^ “Appeals court reverses hacker/troll “weev” conviction and sentence [Updated]”.
^ “Can Scraping Non-Infringing Content Become Copyright Infringement… Because Of How Scrapers Work? “.
^ Singel, Ryan. “Google Catches Bing Copying; Microsoft Says ‘So What? ‘”. Wired.
External links[edit]
Scrapy Open source python framework, not dedicated to search engine scraping but regularly used as base and with a large number of users.
Compunect scraping sourcecode – A range of well known open source PHP scraping scripts including a regularly maintained Google Search scraper for scraping advertisements and organic resultpages.
Justone free scraping scripts – Information about Google scraping as well as open source PHP scripts (last updated mid 2016)
rvices source code – Python and PHP open source classes for a 3rd party scraping API. (updated January 2017, free for private use)
PHP Simpledom A widespread open source PHP DOM parser to interpret HTML code into variables.
SerpApi Third party service based in the United States allowing you to scrape search engines legally.
10 Tips to avoid getting Blocked while Scraping Websites | Codementor
Published May 22, 2020Last updated Apr 17, 2021Data Scraping is something that has to be done quite responsibly. You have to be very cautious about the website you are scraping. It could have negative effects on the website. There are FREE web scrapers in the market which can smoothly scrape any website without getting blocked. Many websites on the web do not have any anti-scraping mechanism but some of the websites do block scrapers because they do not believe in open data access.
One thing you have to keep in mind is BE NICE and FOLLOW SCRAPING POLICIES of the website
But if you are building web scrapers for your project or a company then you must follow these 10 tips before even starting to scrape any website.
1.
First of all, you have to understand what is file and what is its functionality. So, basically it tells search engine crawlers which pages or files the crawler can or can’t request from your site. This is used mainly to avoid overloading any website with requests. This file provides standard rules about scraping. Many websites allow GOOGLE to let them scrape their websites. One can find file on websites — Sometimes certain websites have User-agent: * or Disallow:/ in their file which means they don’t want you to scrape their websites.
Basically anti-scraping mechanism works on a fundamental rule which is: Is it a bot or a human? For analyzing this rule it has to follow certain criteria in order to make a decision.
Points referred by an anti-scraping mechanism:
If you are scraping pages faster than a human possibly can, you will fall into a category called “bots”.
Following the same pattern while scraping. Like for example, you are going through every page of that target domain for just collecting images or links.
If you are scraping using the same IP for a certain period of time.
User Agent missing. Maybe you are using a headerless browser like Tor Browser
If you keep these points in mind while scraping a website, I am pretty sure you will be able to scrape any website on the web.
2. IP Rotation
This is the easiest way for anti-scraping mechanisms to caught you red-handed. If you keep using the same IP for every request you will be blocked. So, for every successful scraping request, you must use a new IP for every request. You must have a pool of at least 10 IPs before making an HTTP request. To avoid getting blocked you can use proxy rotating services like Scrapingdog or any other Proxy services. I am putting a small python code snippet which can be used to create a pool of new IP address before making a request.
from bs4 import BeautifulSoup
import requests
l={}
u=list()
url=”+country_code+”/”
respo = (url)
soup = BeautifulSoup(respo, ’’)
allproxy = nd_all(“tr”)
for proxy in allproxy:
foo = nd_all(“td”)
try:
l[“ip”]=foo[0](“\n”, ””). replace(“(“, ””). replace(“)”, ””). replace(“\’”, ””). replace(“;”, ””)
except:
l[“ip”]=None
l[“port”]=foo[1](“\n”, ””). replace(“ “, ””)
l[“port”]=None
l[“country”]=foo[5](“\n”, ””). replace(“ “, ””)
l[“country”]=None
if(l[“port”] is not None):
(l)
print(u)
This will provide you a JSON response with three properties which are IP, port, and country. This proxy API will provide IPs according to a country code. you can find country code here.
But for websites which have advanced bot detection mechanism, you have to use either mobile or residential proxies. you can again use Scrapingdog for such services. The number of IPs in the world is fixed. By using these services you will get access to millions of IPs which can be used to scrape millions of pages. This is the best thing you can do to scrape successfully for a longer period of time.
3. User-Agent
The User-Agent request header is a character string that lets servers and network peers identify the application, operating system, vendor, and/or version of the requesting user agent. Some websites block certain requests if they contain User-Agent that don’t belong to a major browser. If user-agents are not set many websites won’t allow viewing their content. You can get your user-agent by typing What is my user agent on google.
You can also check your user-string here:
Somewhat same technique is used by an anti-scraping mechanism that they use while banning IPs. If you are using the same user-agent for every request you will be banned in no time. What is the solution? Well, the solution is pretty simple you have to either create a list of User-Agents or maybe use libraries like fake-useragents. I have used both techniques but for efficiency purposes, I will urge you to use the library.
A user-agent string listing to get you started can be found here:
4. Make Scraping slower, keep Random Intervals in between
As you know the speed of crawling websites by humans and bots is very different. Bots can scrape websites at a very fast pace. Making fast unnecessary or random requests to a website is not good for anyone. Due to this overloading of requests a website may go down.
To avoid this mistake, make your bot sleep programmatically in between scraping processes. This will make your bot look more human to the anti-scraping mechanism. This will also not harm the website. Scrape the smallest number of pages at a time by making concurrent requests. Put a timeout of around 10 to 20 seconds and then continue scraping. As I said earlier respect the file.
Use auto throttling mechanisms which will automatically throttle the crawling speed based on the load on both the spider and the website that you are crawling. Adjust the spider to an optimum crawling speed after a few trials run. Do this periodically because the environment does change over time.
5. Change in Scraping Pattern & Detect website change
Generally, humans don’t perform repetitive tasks as they browse through a site with random actions. But web scraping bots will crawl in the same pattern because they are programmed to do so. As I said earlier some websites have great anti-scraping mechanisms. They will catch your bot and will ban it permanently.
Now, how can you protect your bot from being caught? This can be achieved by Incorporating some random clicks on the page, mouse movements, and random actions that will make a spider look like a human.
Now, another problem is many websites change their layouts for many reasons and due to this your scraper will fail to bring data you are expecting. For this, you should have a perfect monitoring system that detects changes in their layouts and then alert you with the scenario. Then this information can be used in your scraper to work accordingly.
One of my friends is working in a large online travel agency and they crawl the web to get prices of their competitors. While doing so they have a monitoring system that mails them every 15 minutes about the status of their layouts. This keeps everything on track and their scraper never breaks.
When you make a request to a website from your browser it sends a list of headers. Using headers, website analyses about your identity. To make your scraper look more human you can use these headers. Just copy them and paste them in your header object inside your code. That will make your request look like it’s coming from a real browser. On top of that using IP and User-Agent Rotation will make your scraper unbreakable. You can scrape any website whether it is dynamic or static. I am pretty sure using these techniques you will be able to beat 99. 99% anti-scraping mechanisms.
Now, there is a header “Referer”. It is an HTTP request header that lets the site know what site you are arriving from. Generally, it’s a good idea to set this so that it looks like you’re arriving from Google, you can do this with the header:
“Referer”: “
You can replace it to or if you are trying to scrape websites based in the UK or India. This will make your request look more authentic and organic. You can also look up the most common referrers to any site using a tool like, often this will be a social media site like Youtube or Facebook.
7. Headless Browser
Websites display their content on the basis of which browser you are using. Certain displays differently on different browsers. Let’s take the example of Google search. If the browser (identified by the user agent) has advanced capabilities, the website may present “richer” content — something more dynamic and styled which may have a heavy reliance on Javascript and CSS.
The problem with this is that when doing any kind of web scraping, the content is rendered by the JS code and not the raw HTML response the server delivers. In order to scrape these websites, you may need to deploy your own headless browser (or have Scrapingdog do it for you! ).
Automation Browsers like Selenium or Puppeteer provides APIs to control browsers and Scrape dynamic websites. I must say a lot of effort goes in for making these browsers go undetectable. But his is the most effective way to scrape a website. You can even use certain browserless services to let you open an instance of a browser on their servers rather than increasing the load on your server. You can even open more than 100 instances at once on their services. So, all & all its a boon for the Scraping industry.
8. Captcha Solving Services
Many websites use ReCaptcha from Google which lets you pass a test. If the test goes successful within a certain time frame then it considers that you are not a bot but a real human being. f you are scraping a website on a large scale, the website will eventually block you. You will start seeing captcha pages instead of web pages. There are services to get past these restrictions such as Scrapingdog. Note that some of these CAPTCHA solving services are fairly slow and expensive, so you may need to consider whether it is still economically viable to scrape sites that require continuous CAPTCHA solving over time.
## 9. Honeypot Traps
There are invisible links to detect hacking or web scraping. Actually it is an application that imitates the behavior of a real system. Certain websites have installed honeypots on their system which are invisible by a normal user but can be seen by bots or web scrapers. You need to find out whether a link has the “display: none” or “visibility: hidden” CSS properties set, and if they do avoid following that link, otherwise a site will be able to correctly identify you as a programmatic scraper, fingerprint the properties of your requests, and block you quite easily.
Honeypots are one of the easiest ways for smart webmasters to detect crawlers, so make sure that you are performing this check on each page that you scrape.
10. Google Cache
Now, sometime google keeps a cached copy of some websites. So, rather than making a request to that website, you can also make a request to it cached copy. Simply prepend “ to the beginning of the URL. For example, to scrape documentation of Scrapingdog you could scrape “.
But one thing you should keep in mind is that this technique should be used for websites that do not have sensitive information which also keeps changing. Like for example, Linkedin tells Google to not cache their data. Google also creates a cached copy of a website in a certain interval of time. It also depends on the popularity of the website.
Hopefully, you have learned new scraping tips by reading this article. I must remind you to keep respecting the file. Also, try not to make large requests to smaller websites because they might not have the budget that large enterprises have.
Feel free to comment and ask me anything. You can follow me on Twitter and Medium. Thanks for reading and please hit the like button!
Additional Resources
And there’s the list! At this point, you should feel comfortable writing your first web scraper to gather data from any website. Here are a few additional resources that you may find helpful during your web scraping journey:
10 Best datacenter proxy providers
Web Scraping with Nodejs
Web Scraping with Java
Web Scraping with Python
Free Proxy List
Web Scraping with Javascript
Frequently Asked Questions about ip scraper
Is Google scraping legal?
Although Google does not take legal action against scraping, it uses a range of defensive methods that makes scraping their results a challenging task, even when the scraping tool is realistically spoofing a normal web browser: … Network and IP limitations are as well part of the scraping defense systems.
Can you get banned for web scraping?
Change in Scraping Pattern & Detect website change Generally, humans don’t perform repetitive tasks as they browse through a site with random actions. But web scraping bots will crawl in the same pattern because they are programmed to do so. … They will catch your bot and will ban it permanently.May 22, 2020
Is data scraping legal in US?
It is perfectly legal if you scrape data from websites for public consumption and use it for analysis. However, it is not legal if you scrape confidential information for profit. For example, scraping private contact information without permission, and sell them to a 3rd party for profit is illegal.Aug 16, 2021
