Consider everything you do each day. You may check the news, write an email, look for the greatest bargain on a product, or look for the jobs on the internet. Web scraping can simplify most of these operations, so rather than spending hours going through sites, a machine can accomplish it in a matter of minutes.
The technique of obtaining data from a webpage is known as web scraping. Learning Web Scraping Services could be as simple as watching a lesson on how Python libraries like Beautiful Soup, Selenium, or Scrapy function; however, if you can't put all the ideas you've learned into action, you've wasted your time.
This is the only reason why should you try web scraping projects that help you not just to master web scraping theory but also design bots that will automate your daily work, keeping you inspired to learn this new talent.
In this blog, we have mentioned few projects that will enhance 4 web scraping projects everyone will come across.
1. Repetitive Tasks Can Be Automated
Because BeautifulSoup is the easiest Python library for web scraping, we'll use it for this initial project to make it beginner-friendly.
The project's purpose is to extract the headline and body content from any website's article (e.g., news articles, posts, etc.). After that, exporting all the material to an a.txt file with the title of the article as the filename. The animation below shows a demonstration of this project. Rather than just scraping a news article, we have scraped the Titanic movie transcript in this example.
2. Scrape Football Information: Automating Sports Analytics
If you enjoy sports, you certainly go to websites that provide free data such as final results and team performance after each game. Isn't it cool if you could collect that information after every new league? Imagine being willing to generate a presentation that reveals unique facts regarding your favorite club or league.
The second project's purpose is to crawl a database that provides statistics from your favorite team. Because this sort of data is usually contained within a table, please ensure to save it in CSV format so that you may analyze it with the Pandas library and get insights afterward.
The majority of sports-related websites use JavaScript to dynamically update their data. We won't ever be able to use the BeautifulSoup library for such a project as a result of this. Instead, we'll utilize Selenium to tap on buttons, choose objects from dropdown menus, and retrieve the information we need.
3. Scraping a Job Portal: Automating Job Hiring
Using web scraping, finding a job can be a lot easier. Manually browsing through numerous pages for new positions, evaluating the prerequisites of a certain job, and determining the maximum salary can consume up to 20 minutes. Fortunately, with a few code lines, all of this can be automated.
For this project, we will construct a bot that will scrape a company website to obtain information about a certain job's requirements, and the compensation was given. This project may be done using either BeautifulSoup or Selenium, however, the technique would be different depending on which library you select.
We would suggest you to utilize Selenium because it will allow you to perform more activities on the website. The nicest part is that you can execute the script after each operation and view the bot's actions in the browser. Consider all of the steps you'd take to collect data from your preferred employment portal if you were using Selenium. Going to the webpage, type in the job description, hitting the search bar, and browsing through each job ad to collect any necessary details, for example. Then, using the Selenium package in Python, recreate these steps.
4. Pricing Intelligence: Scrape the Best Price
If you're looking for the greatest offer on a particular piece, shopping can take a long time. It can take hours to search websites for the best possible price on a car, TV, or clothing; luckily, with our next web data extraction project, it will just take a few minutes.
This is the article's most complex project, which is divided into two pieces. To begin, go over to your favorite web retailer and collect product information such as name, price, discount, and links so how you can locate them afterward. For the second part, of the blog, you will now scrape the prices of the product. Hence, when the product price will drop, you will be notified of the same.
- Scraping Stock Prices
- Scraping Bookies
- Scraping Cryptocurrency Pricing
For further guidance, you can contact our team at iWeb Scraping.
