Web Scraping for Beginners
You have likely copied and pasted a piece of text from a website to a new tab or file. This could have been because of the complexity of the term or due to the fact that it contained several numbers that you did not want to get wrong if you typed. Whether you knew it or not, you engaged in what we refer to as web scraping, web data extraction, or web harvesting.
Web scraping essentially refers to the process of retrieving data from websites. It covers basic and manual functions such as copying and pasting for small-scale applications, as well as automated data extraction. This article will mainly deal with the latter.
How does Web Scraping Work?
Automated data extraction is carried out by tools known as web scrapers. These tools can be created in-house using Python or obtained from service providers. Web scrapers automatically send HTTP or HTTPS requests, similar to how you would when using a web browser.
Next, these tools receive HTML code files containing the data to be extracted. However, a human being cannot easily read the code file. In addition, the information contained therein is unstructured, meaning it cannot be analyzed. You can even confirm this by placing your cursor on a black section of a website, pressing the right-click button, and then choosing the view source code option on your web browser.
The web scraper then locates HTML elements, i.e., content on the web page. Thereafter, it organizes the unstructured data through a process known as parsing, which changes the HTML data to a human-readable, structured format. Finally, the web scraping tool extracts the retrieved content onto CSV or JSON files that can be downloaded.
Businesses use web scraping for price monitoring, review and news monitoring, market research, competitor monitoring, and more.
Importance of Choosing Reliable Web Scraping Solutions
It is worth noting that the steps highlighted above only tell of the basic steps involved in automated web harvesting. With advances in technology as well as the increased use of anti-scraping techniques, advanced tools such as the web scraper API offer additional capabilities.
At the same time, if you wish to undertake large-scale web scraping, your web scraper will likely have to go through multiple web pages. Therefore, an ideal web scraping tool should be capable of handling pagination. This means that it should use a single URL to identify other unique URLs within a given website.
Furthermore, the web scraper should have integrated mechanisms that help prevent internet protocol (IP) address blocking. Usually, web servers monitor the number of requests originating from a single IP address. If one IP address is responsible for an abnormal volume of requests, the server will flag the address. Notably, algorithms use normal human browsing behavior as a reference to determine the abnormality.
In most cases, flagging entails limiting the IP address for some time. However, it could still lead to the IP address being blocked from accessing the website.
To prevent IP blocking, it is advisable to use web scrapers along with proxy servers. A proxy refers to an intermediary computer through which all the requests from the web scraping solution will be channeled. The proxy assigns a new IP address to the computer on which the scraping tool is installed. This helps prevent IP blocking.
Importantly, however, not all proxy servers are ideal for the task. This is because the quality of the proxy provider’s IP network pool matters. A reliable proxy provider offers a vast IP network pool that enables your scraper to access geo-restricted content. In addition, you can also enjoy benefits such as an integrated IP address rotator.
As a business looking to extract data from websites, you have the option of building a web scraper from scratch using the Python programming language and its web scraping libraries. Unfortunately, you give up the aforementioned benefits of a reliable web scraper with this option.
On the other hand, if you opt for a pre-built web scraper, always ensure that it is developed by a reliable service provider. This is why you can never go wrong with the web scraper API.
Web scraping is a beneficial process for businesses. And while companies can create Python web scrapers in-house, advanced, pre-built web scraping tools, such as the web scraper API, offer more capabilities. Nonetheless, it is essential to use products created by reliable service providers.