Proxy for Web Scraping
Web Scraping is the process of programmatically extracting information from Internet resources.
Websites provide information to users, and sometimes this information is very valuable and needs to be available offline and in a structured way. For example, you want to have all the photos of your favorite band on your mobile device, but manually saving the photos one by one can take a very long time. Another example: an online seller wants to know what prices his competitors have set. And this data should be in a format convenient for analysis and also should be updated hourly. Web scraping can solve both of these problems. It is also worth mentioning that Web Scraping is a fundamental technology for search engines such as Google.
You can hardly imagine how widely Web Scraping is actually used. Many well-known services are built on top of scraped data.
In addition to search engines, there are many types of aggregators, such as air ticket aggregators, news aggregators, and the Internet archive.
Big Data. It's hard to imagine a Big Data system these days without using a third-party data source. Web Scraping may be a suitable solution for this type of project.
Data Mining. Data collected through Web Scraping can be a good source for Data Mining projects.
Data Science. It's no secret that Data Scientists are doing their job on data. Web Scraping can be very helpful here.
AI/ML. In the field of Artificial Intelligence and Machine Learning the main approach is based on Neural Networks. Architecturally, Neural Networks require a large amount of labeled data to train them. Web Scraping can help you get started quickly and frugally in this area.
Competitive Intelligence. All businesses are represented on the Internet these days. The Internet is a very convenient place to communicate with consumers. Every business has to put a lot of commercial data on the Internet in order to promote its products. This data can be scraped and analyzed by competitors. Your competitors' assortment, prices and warehouse stocks are very useful data for the decision making process. Market research looks similar.
Let's take a look at how Web Scrping actually works.
First of all, we need to understand that the data that we are going to scrape is located on the server in the data center. The server provides data via the HTTP protocol as a HTML page. The user sends a request to the server through the browser, the server returns an HTTP response with an HTML page, then the browser renders and displays the information in the User Interface. This simple explanation will suffice for our further analysis of Web Scraping.
We can divide the scraping process into two steps:
Crawler and proxy.
It is obvious that modern websites can have thousands or even millions of pages. If you try to send several hundred requests to some web server from your computer, you will most likely be blocked. And that's with just a hundred requests. In fact, your IP address will be blocked.
The web server receives the client's IP address with every request. And it's not rocket science to determine the IP address from which too many requests are sent.
This is where proxy come to the rescue.
The proxy server can mask your web request so that the web server thinks the source of the request is at the proxy IP address, not yours. You can find more details on how the proxy server works here.
Having a proxy list gives you the ability to send thousands of requests from one computer and not get blocked. On the market you can find several proxy solutions for Web Scraping. For Web Scraping are mainly used data center proxy. This type of proxy is the cheapest and most reliable. For special cases, residential proxy and mobile proxy can be used.
A good proxy solution for Web Scraping should provide a proxy rotation mechanism and should be easily pluggable into scraping frameworks.
Scrapy and Apify are the most popular scraping frameworks in 2023.
Scrapy is the number one web scraping framework with a long history and is written in Python. Scrapy is known for being easy to use and full featured. Apify is a younger contender. Apify is written in JavaScript and takes full advantage of the JS ecosystem.
Websites provide information to users, and sometimes this information is very valuable and needs to be available offline and in a structured way. For example, you want to have all the photos of your favorite band on your mobile device, but manually saving the photos one by one can take a very long time. Another example: an online seller wants to know what prices his competitors have set. And this data should be in a format convenient for analysis and also should be updated hourly. Web scraping can solve both of these problems. It is also worth mentioning that Web Scraping is a fundamental technology for search engines such as Google.
You can hardly imagine how widely Web Scraping is actually used. Many well-known services are built on top of scraped data.
In addition to search engines, there are many types of aggregators, such as air ticket aggregators, news aggregators, and the Internet archive.
Big Data. It's hard to imagine a Big Data system these days without using a third-party data source. Web Scraping may be a suitable solution for this type of project.
Data Mining. Data collected through Web Scraping can be a good source for Data Mining projects.
Data Science. It's no secret that Data Scientists are doing their job on data. Web Scraping can be very helpful here.
AI/ML. In the field of Artificial Intelligence and Machine Learning the main approach is based on Neural Networks. Architecturally, Neural Networks require a large amount of labeled data to train them. Web Scraping can help you get started quickly and frugally in this area.
Competitive Intelligence. All businesses are represented on the Internet these days. The Internet is a very convenient place to communicate with consumers. Every business has to put a lot of commercial data on the Internet in order to promote its products. This data can be scraped and analyzed by competitors. Your competitors' assortment, prices and warehouse stocks are very useful data for the decision making process. Market research looks similar.
Let's take a look at how Web Scrping actually works.
First of all, we need to understand that the data that we are going to scrape is located on the server in the data center. The server provides data via the HTTP protocol as a HTML page. The user sends a request to the server through the browser, the server returns an HTTP response with an HTML page, then the browser renders and displays the information in the User Interface. This simple explanation will suffice for our further analysis of Web Scraping.
We can divide the scraping process into two steps:
- Get a response from the server;
- Extract data.
Crawler and proxy.
It is obvious that modern websites can have thousands or even millions of pages. If you try to send several hundred requests to some web server from your computer, you will most likely be blocked. And that's with just a hundred requests. In fact, your IP address will be blocked.
The web server receives the client's IP address with every request. And it's not rocket science to determine the IP address from which too many requests are sent.
This is where proxy come to the rescue.
The proxy server can mask your web request so that the web server thinks the source of the request is at the proxy IP address, not yours. You can find more details on how the proxy server works here.
Having a proxy list gives you the ability to send thousands of requests from one computer and not get blocked. On the market you can find several proxy solutions for Web Scraping. For Web Scraping are mainly used data center proxy. This type of proxy is the cheapest and most reliable. For special cases, residential proxy and mobile proxy can be used.
A good proxy solution for Web Scraping should provide a proxy rotation mechanism and should be easily pluggable into scraping frameworks.
Scrapy and Apify are the most popular scraping frameworks in 2023.
Scrapy is the number one web scraping framework with a long history and is written in Python. Scrapy is known for being easy to use and full featured. Apify is a younger contender. Apify is written in JavaScript and takes full advantage of the JS ecosystem.
List of Web Scraping Frameworks.
Proxy rotation solution for Scrapy and Apify can provide a choice of several levels of proxy quality.
Free proxy mean you get public open proxy servers. This may be a good starting point, but it can bring problems such as high latency, low server availability, and many error responses.
The next step in quality will be shared proxy servers. Shared proxy servers can provide you with a much more stable and predictable service. Compared to public open proxy servers that can be used by thousands of users at the same time, shared proxy servers have a load of from ten to hundred users. Fewer server users means less server load so the server can provide lower latency and fewer errors. Also, fewer requests lead to the server being more slowly recognized by the target server as the source of a large number of requests, and will be blocked later.
Another option is a dedicated proxy server. A dedicated proxy server means that a specific proxy server with a specific IP address is used exclusively by you. A dedicated proxy server costs a lot more than a shared proxy server and honestly isn't worth it in most cases. A dedicated proxy server along with residential proxy and mobile proxy may be needed in rare cases.
Free proxy mean you get public open proxy servers. This may be a good starting point, but it can bring problems such as high latency, low server availability, and many error responses.
The next step in quality will be shared proxy servers. Shared proxy servers can provide you with a much more stable and predictable service. Compared to public open proxy servers that can be used by thousands of users at the same time, shared proxy servers have a load of from ten to hundred users. Fewer server users means less server load so the server can provide lower latency and fewer errors. Also, fewer requests lead to the server being more slowly recognized by the target server as the source of a large number of requests, and will be blocked later.
Another option is a dedicated proxy server. A dedicated proxy server means that a specific proxy server with a specific IP address is used exclusively by you. A dedicated proxy server costs a lot more than a shared proxy server and honestly isn't worth it in most cases. A dedicated proxy server along with residential proxy and mobile proxy may be needed in rare cases.
