What is a web scraper?

Web scraping is the process of extracting data from a website, automatically. Although online scraping can be done manually, web scrapers are used to automate scraping web data because of their efficiency and accuracy. A web scraper is a tool used for web scraping.

A website scraper is used to conduct HTTP requests on a website and retrieve the data from a page. It retrieves content that is publicly available, and the server renders it as HTML. It also sends queries to internal application programming interfaces (APIs) for associated data, such as product prices or contact information, which is then saved in a database and provided to a browser via HTTP requests.

Now that we know what a web scraper is, let's dive into its workflow.

Workflow of a web scraper

Web scrapers work in a straightforward but complex manner.

Firstly, the scrapper is provided with one or more URLs. It will process the data from the URLs provided. The scraper extracts the HTML code for that URL, some optimized scrapers also extract the CSS and JavaScript elements.

The scraper will then either extract all of the data on the page or specific data selected by the user before running the project. The user should ideally go through the process of selecting the specific data they require from the page. For example, when web scraping on an e-commerce website, users may only be interested just to process the features and price of products for comparison but not the product reviews.

Finally, the web scraper will output all of the collected data in a manner that is more valuable to the user. Most online scrapers will output data to a CSV or Excel spreadsheet. However, more powerful scrapers will support other formats, such as JSON, which can be used for an API.

Applications of a web scraper

Web scraping has numerous applications in various industries, including data science, e-commerce, sales, research, real estate, and social media. Here are some specific examples of how web scraping can be applied in each of these domains:

1. Data science: In data science, web scraping is frequently used to retrieve large datasets for analysis and modeling.

2. E-commerce: Web scraping is used in the e-commerce industry for pricing comparison, product information extraction, and cE-commerce: ompetition monitoring to improve product offers and elevate their market position.

3. Sales: Web scraping can assist sales teams in a market study where they can extract contact information and company details from business platforms as well as social media platforms and promote their business.

4. Research: Web scraping is widely used in academic research where researchers can gather data from scientific publications and surveys and analyze trends for their study.

5. Real estate: Web scraping can be used in the real estate industry for property data collection, including prices, features, and availability. This allows investors and agents to analyze market trends, compare prices, and identify potential investment opportunities.

6. Social media: Web scraping is beneficial for analyzing social media platforms to extract user-generated content and monitor brand mentions.

Web scraper tools

Web scraping tools are software programs or libraries that extract information from websites. They make it easier to acquire vast amounts of information from the internet by automating the process of retrieving, parsing, and organizing data from web pages.

There are several web scraping tools available, each with its own features and advantages. The image below shows a few examples.

Let's have an overview of these tools in the table below.

Note: When it comes to web scraping tools, there are different deployment options available, including browser extensions, cloud-based solutions, and installable software.

Conclusion

In conclusion, web scraping is a valuable technique for extracting data from websites. It allows us to automate the process of gathering information, saving time and effort compared to manual data collection. Web scraping finds applications in various domains, such as data science, e-commerce, sales, research, real estate, and social media. The choice of web scraper depends on the requirements of the scraping project, including the target websites, desired data, and complexity of the website structure.