What Is Web Scraping?
Learn about the importance and fundamentals of web scraping.
We'll cover the following
Introduction
Web scraping facilitates collecting unstructured data and storing it in a structured format. It is the art of fetching all types of data that are publicly available on the Internet. As programmers, we may already be familiar with the term.
During web scraping, we interact with all the information a web browser displays for a specific website. This can include links, images, videos, names, reviews, and more.
Importance
Web scraping has many benefits beyond automating processes:
It can save time and cost by providing access to vast amounts of data that would otherwise be difficult or expensive to collect.
By collecting data directly from the source, web scraping eliminates the potential for human error and ensures that the data is up-to-date and reliable.
It allows for the collection of high-quality data, leading to more informed decision-making and better project outcomes.
With web scraping, businesses can gather valuable information about their competitors, track customer sentiment, and monitor industry trends.
It is a valuable skill that helps tackle real-world project challenges like a lack of data.
💡 Did you know?
The original ChatGPT chatbot application is built on top of the GPT-3 base model, which was trained using approximately 45TB of text data scraped from the internet.
E-commerce companies often rely on web scraping to acquire current information about the selling price of a particular product on other websites, which enables them to estimate the most suitable price range.
Benefits of Python
Python is an excellent language for web scraping due to its following qualities:
Simpler syntax
High performance
Ease of coding
Flexibility
Reusability
Libraries
Python offers several powerful libraries for data processing, such as NumPy, pandas, and JSON, which help structure the scraped data. In web scraping, Python provides the following tools:
