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The Fundamentals of Web Scraping: What You Need to Know to Get Started

by Innov8tiv.com

Are you in need of digital information that you do not have access to? Web scraping is the way to go. Read this article to learn why and how!

There is every possibility that you do not know what web scraping is even though you have been doing it all along. The World Wide Web, as you know very well, is a colossal repository of information and content. Web scraping allows us to extract data from the seemingly endless array of pages on the Internet.

The information that is gathered can then be stored in the form of a local file on your personal computer or any other device of your choice. This data is then available for use in any number of open source projects, different APIs, website interfaces, or simply for general documentation. The purpose of this article is to provide a comprehensive guide on the basics of web scraping.

What Is Web Scraping?

As mentioned above, web scraping enables the user to download distinct information from websites, depending on several parameters. These days, a lot of this is being done by artificially intelligent bots that are adept at crawling web pages, collecting data, and storing them in data repositories. Thus, it is safe to say that the phenomenon of web crawling itself is a crucial component of web scraping.

To understand what web scraping truly refers to, you would need to learn how the entire system works in the first place. Initially, the pages that contain the required information are identified. Then, the pages are fetched and downloaded to carry out a thorough search on them. They are processed in a lot of ways, including copying, reformatting, editing, and more, depending on the needs of the user.

Modern web scrapers are capable of extracting texts, images, videos, product information, contact information, and a whole lot more. Such is the impact of web scraping these days that it is being considered as a core component of most digital infrastructures. The claim is further solidified based on the fact that leading search engines, like Google or Bing, use web scraping techniques to crawl the web.

Getting Help from Experts

The best way to start web scraping is by seeking the help of experts in this field. Certain organizations specialize in assisting their clients by creating a web scraping API, developing custom cookies, pre-processing related outputs, rendering website pages, executing Javascript codes, avoiding captchas, and more. These services are really valuable considering you would have to learn and execute them yourself otherwise.

These organizations also specialize in drawing out detailed web scraping plans for clients. Users can simply follow the path shown by the experts and begin their web scraping process. In many cases, users may decide to have the actual scraping done by these professionals.

Is Web Scraping Unethical?

There are a lot of prevalent misunderstandings about web scraping as many renowned critics consider web scraping to be unethical. While this claim might sound fair up to a certain extent, in reality, it is not. For a better understanding of this aspect, let us take a look at an example. Google is, without doubt, the leading search engine in the entire world, and rightfully so.

The key reason behind its uncontested success is the fact that it can scrape through more websites than its nearest competitors. Had web scraping been unethical or illegal, some of the most prominent search engines like Google would not be in the position they are in today.

Web Scraping Libraries and Tools That You Should Know About

Although the scope is vast, there does exist many programming libraries that make the task of web scraping easier. You will be greatly benefited if you have any prior knowledge of the programming language known as Python. We suggest you acquire at least a general idea of how it works as it will come to your aid eventually. The following sections describe some of the most popular libraries that you can use for scraping the web.

Selenium

This is not exactly a library but is similar to one. In reality, Selenium is an automation tool that is integrated into the web browser. The software can click buttons, fill up forms, and search for specific pieces of information similar to a bot. Selenium can also be used to create large repositories that will enable you to scrape various websites.

BeautifulSoup

This is a Python package that can extract data from XML and HTML files. After that, it tends to develop parsed trees that make scraping through colossal chunks of data relatively easy and fast. As of now, both the 2.7 and 3.0 versions of Python are capable of running BeautifulSoup.

Pandas

This is a Python library that can manipulate and index data. The key advantage of using Pandas is that it allows the analysis of data completely on Python, without having to switch to other programming languages like R, or even Java.

Make no mistake: some other tools and libraries can do the same tasks. However, the methods they opt for are not as efficient as the aforementioned ones.

How Does Web Scraping Work?

Despite the availability of many different web scrapers that work in distinct ways, there are some common aspects in them all. We have tried to keep the following sections as generalized as possible so that anyone can attempt web scraping about this article.

Identify the Target URL

First things first: you need to determine the web domain that you are intending to scrape from. This does not need to be a single web page; a collection of pages is also applicable for web scraping.

Perform a Page Inspection

Web scrapers work directly with the coding of a page. It will only do what you tell it to do, making it your job to direct it to the underlying codes. The scraper will go through all the HTML elements and tags to understand the structure of the data on the page.

If you want to check these fields on your own, right-click on the page that you want to be scraped and hit the “inspect” button. This will take you to the backend of the page. Here, you will be able to find all the tags, elements, metadata, and everything else that your scraper will need. Once this step is completed, the real scraping finally begins.

Initialize the Web Scraper

You should now be able to scrape the Internet in a variety of methods. If you are feeling adventurous and have the necessary expertise, try developing it from the ground up in Python. To make this work, you will need to implement libraries like BeautifulSoup.

If you find Python too difficult, you can employ specialized software that simplifies the overall procedure. Nowadays, there are several options that you can choose from, although most of them are not free. They are frequently implemented by businesses as part of online SaaS (software as a service) data platforms.

In case you simply want to scrape a few websites, you are better off developing your web scraper. However, when dealing with sophisticated functions, seek software solutions that are right for you.

Unload the Scraped Data

Once the scraper starts running, even before the entire process is completed, you will start seeing the results start to compile into a pre-set location on your hard drive. You can either wait for the process to finish or simply start going through the accumulated data right away, although the former is usually preferred to reduce inconsistencies in the final output.

For your system to be able to read the compiled data, you might have to resort to Regex or regular expressions to convert it into readable text. This final stage is completely dependent on the amount of data that you have gathered. For instance, if you are scraping an immense amount of data, chances are, you will need a separate parser just to make the outcome readable and discernible.

Final Words

If you are planning a web scraping project, now is the time. Web scraping is necessary if you wish to make sense of the vast repository of information that is available online. The data being globally retrieved from scraping the web is currently contributing to important sectors like machine learning, big data analytics, and artificial intelligence. It is the wave of the future, and it makes no sense to not be aware of it.

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