How to scrape a website for information (for beginners)
Why should one learn how to scrape data from a website? What methods can you use to scrape a website? Why should you learn Python?
Most websites display content that users can view without any form of access to the data. So, if one wants to download this useful data, they have manually to copy it or use an automated program to retrieve it. If you are an absolute beginner, this write-up will show you how to scrape a website to obtain vital information that will help you optimize your site.
Why should one learn how to scrape data from a website?
In general, web scraping helps you gain access to many online resources. It is the process of extracting useful information from a website. Often, the contents are saved to a spreadsheet or a database. Even though you can download the online data using standard copy-paste methods, the preferred option is the use of automated bots.
In practice, scraping a website involves sending GET-request to the target website(s), obtaining and parsing the HTML content, and storing the data in the right format. Some data, you can harvest from scraping a website, include media files, catalog of goods, text, and contact details. You can also use separate services, that work through the API (Diffbot) or other open source-code scrapers (Scrapy).
But why is Web scraping necessary?
There is no limit to the amount of information you can acquire if you know how to scrape data from a website. However, there are other benefits to web harvesting.
Here they are:
- Scraping helps in gathering contact info from any website.
- Knowing how to web scrape, will save you a lot of time, spent on acquiring data from scratch.
- Businesses can use a Web scraper for market analysis, by monitoring trends and customer behavior.
- Web scraping assists in gathering information to a centralized source instantly.
- Web scraping helps researchers to acquire data from multiple sources within a short time. It helps minimize the time and effort spent on data collection, while providing an extensive database and sample size.
What methods can you use to scrape a website?
Web scraping can be done using different manual and automated techniques. The most primitive method of scraping a website is copying the entire source code or fragments of the code into text files. As well there exist the other automated methods of retrieving data, more functional and specific.
Here they are:
- HTML and DOM parsing — access multiple dynamically generated web pages based on their unique templates.
- Vertical aggregation — Makes use of a robust platform of bots.
- Web page analysis — Makes use of machine learning to acquire information from websites.
- Softwares and libraries — Scrapy and Beautiful Soup (both written in Python)
Python is an integral component in the development of these procedures and software because it is a versatile programming language for web crawling. Python is also a great language for those, who wish to learn how to scrape data from a website.
Alternatively, a lot of other non-Python-based services exist, which do
not require technical coding skills to use — no-code services.
How to scrape a website?
Some of these no-code services include:
Is it better to scrape an entire website or just sections?
There is no hardline rule on what amount of data to scrape from the internet. But a significant factor to consider, when learning how to scrape a website for data, is purpose. This distinction will help you focus your resources and save time when harvesting data by streamlining the type of data you want to scrape.
For example, when you find a popular website with an extensive database on every page, you can copy information from the entire site. If you find a site with useful features, but you only want to copy data from specific pages, you don’t need to scrape the entire website. Focus on the fragments containing the data most relevant to your project.
Moreover, most industries prefer to cross-reference data from multiple sites. The crawler will visit multiple URLs to detect specific data snippets pertaining to diverse datasets. This practice is helpful when harvesting information for commercial purposes like real-estate and market research.
Python as the language of scraping
As already mentioned earlier, it is advisable to acquaint yourself with Python, if you want to learn, how to screen scrape a website. Not only is it popular, but it is also used for compiling libraries like Scrapy and Selenium. You also need an in-depth knowledge of HTML and DOM. These markup languages will help you understand the structure and arrangement of web content.
Why should you learn Python?
First of all, Python is a pretty easy language to grasp for beginners. Also, most operating systems come with Python pre-installed (Windows users might have to install manually). Most importantly, Python has the most extensive community for data science and scraping worldwide. So, most of the tools you will be using will be written in Python code.
In conclusion, you need to understand Python to master how to web scrape. Try to limit the scope of your data harvesting to specific databases, because this will help you to conserve time and resources. You can scrape a website manually or use automated programs to enhance the process’s productivity.
Stay ahead in the data race by learning effective ways of scraping data from online sources!