How to Use Standard Web Scraping Methods?
The efficiency of data scraping is determined by its use for researching the competitor’s websites and getting the essential data for creating new and unique content. Such a method of investigating sites is widely used nowadays, and for maximum efficiency, deep programming knowledge is required. So, let’s discover the standard algorithms such as HTML and regular expressions and understand the peculiarities of each.
What is HTML-Scraping?
HTML-parsing is a technique that allows you to extract structured data from web pages. Modern websites are user-focused and provide the best visual presentation of the information. So, it must be automatically extracted to use such data for specific aims. The languages supporting this getting data type are the following:
The data extraction is a complex procedure that requires at least medium HTML knowledge and skills working with the open code. Here, you can find examples of using well-known languages for providing the investigation of web pages.
Scraping with Python
provides several libraries for data mining: Requests (to get the pages’ HTML) and BeautifulSoup (to process and get the desired element in the page). Then, the process should be provided with the following steps:
- Import the first library using “import requests”. To refer to the website, create a URL variable and assign it the value of the desired site.
- Send a request to the server using the “get” command to the input of which the URL variable is passed (we get the unreadable code that will be next processed with the BeautifulSoup library).
- Import the second library using the “from bs4 import BeautifulSoup” command.
- We need to pass the response received with Requests. So, it’s necessary to create a “soup” variable, pass “r.text” and specify the required format (in our case, lxml).
- Then, create a “data” variable, which we’ll use for other requested code elements. It must be moved to the beginning of the code so that it is not overwritten with each new cycle but supplemented.
- Create a cycle in which we choose the necessary elements of the page using the “select” method.
- Now, the code is ordered and ready for launch. The tags go one by one, and we can provide the data extraction.
It’s a simplified instruction, and the code can be customized depending on the necessary website for parsing. For instance, different attributes, methods, and selectors of BeautifulSoup can be used for a more detailed site investigation.
Scraping with PHP
Here, data analytics is provided with the straightforward algorithm:
- Install the “simpleHTMLdom” library.
- Call the function specifying the page you’ll use for parsing.
- Declare a global array by creating a new “simple_html_dom” object, and then load the page.
- Once you have a DOM object, you can start working with it using the “find()” method and creating collections (a group of objects found by a selector).
- Extract the necessary data using the specific methods, and write a PHP function to display pre-stored information.
If you are running scraping on a large number of pages or the entire website, it’ll be a durable process. So, advanced PHP knowledge is required for a highly-efficient operation and to minimize code failure risks.
What is Scraping with Regular Expressions (Regex)?
- str.match – looks for matches with regex in the “str.”.
- str.matchAll – it is used to find all matches along with bracket groups.
- str.split – splits the string into an array based on the delimiter.
- str.search – the method returns the position of the first regex match in str, or -1 if there is no match.
- str.replace – the indispensable method for search and replacement.
- regex.exec – it looks for a match with regex in the “str.” (Unlike the previous methods, it is called on a regular expression, not a string).
- regex.test – it looks for matches and returns true/false depending on whether it finds one.
The listed methods are obligatory for efficient regex web crawling and should be learned by each programmer.
To Sum Up
Overall, regex and HTML parsing are the primary methods for getting information from the websites and using it for web optimization. They require proficient programming knowledge and skills in implementing the libraries’ functions, so it’s better to learn a detailed guide to minimize the risks.