The evolution of the internet and the increased importance of search engines as primary tools for organic marketing are some of the reasons that have propelled web scraping to its current status. Web scraping is proving vital for businesses and companies because of several factors.
Web scraping can aid in reputation monitoring, monitoring competitors’ prices, gathering data to train machine learning algorithms and market analysis, among others. As you may already tell, web scraping entails gathering data from websites.
What is Web Scraping?
Web scraping works on the premise that the internet is a trove of information, which, when harnessed, could prove beneficial to certain users. It is as mundane as manually copying text from a website and pasting it onto a document on your computer. But if the information to be gathered is extensive, this exercise would be time-consuming and inefficient.
This is why automated web scraping tools exist – they can collect large volumes of data quickly. They go a step further by converting unstructured data into structured data, thereby guaranteeing convenience. However, there are two types of automated web scraping tools, namely in-house and ready-to-use tools, which could prove confusing given that they have different requirements and functionalities.
In-House Web Scraping Tools
In-house web scraping tools are also known as Python web scraping tools because the data extraction is performed using a Python script. It is regarded as in-house because you get to write and run the code, thereby implying that you create your web scraping tool, albeit not from scratch.
Python web scraping relies on Python requests libraries’ content, made up of numerous HTTP requests. It makes issuing such requests user-friendly and uncomplicated, thereby enabling you to focus on the service you intend to use the platform for instead of first having to understand how it works. The libraries are a simple API.
With Python web scraping, you simply install the requests library using your terminal and then write a few lines of code that should contain the URL whose website you intend to extract data. The code performs an HTTP request per the information and structure contained in the requests library.
Upon querying the website’s server, HTML data is sent to your computer and subsequently stored as a Python object. While the data the server sends contains all the information the website’s user sees, it is not structured as yet. More tools are required to make this possible.
Benefits of Python Web Scraping
- The Python programming language is easy to use.
- Only a few lines of code are needed to conduct large data extraction tasks.
- You are never alone. When stuck, you can post questions to Python forums and communities, and you’ll subsequently receive help.
- Python web scraping is relatively inexpensive since the requests library and resources are available online for free.
Challenges of Python Web Scraping
- Python web scraping requires a technical background.
- If you lack the technical know-how, you have to hire a programmer to create your business’s web scraping tool, an exercise that could prove ineffective.
- Websites are structured differently. Thus, you may have to take a different approach for each website, which is time-consuming.
- Websites are ever-changing. So, you have to update your python web scraping tool to keep up continually. This may gobble up additional resources.
- These tools require multiple tools for extracting and organizing the data.
If you have the technical background needed or the finances, python web scraping could be a fun way of extracting data. You can try to build your web scraper by following thorough instructions in this article on Python web scraping.
Ready-to-use Web Scraping Tools
Ready-to-use or off-the-shelf web scraping tools do not require a technical programming background. You do not need to know how to write and run code or operate a terminal. With these ready-to-use tools, you simply purchase them, install, and run them, and, voila, you can harness as much information as you wish. Notably, some are even available for free.
Unlike Python web scraping tools, these off-the-shelf web scraping tools scour the internet for the information you are looking for, extract it, organize it in a structured format and avail it for download as a .csv or spreadsheet file.
Benefits of Ready-to-use Web Scraping Tools
- They are convenient since they eliminate the need to have programming knowledge.
- They are efficient because they search for data, extract, and organize it.
- They are a fast web scraping option as they can access multiple websites simultaneously.
Challenges of Ready-to-use Web Scraping Tools
- Some tools are expensive.
- With this type, you rely on customer support, some of whom may not be reliable.
It is crucial to use web scraping tools alongside a proxy server. Proxies facilitate smooth data extraction since they deal with IP blocking, a popular anti-scraping tool among web developers.