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Web Scraping for Beginners

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  • August 18, 2021

Data collection is essential for each company in any industry. A company can harvest data from a website using a variety of methods. It is also necessary to be able to get the data in a proper, structured format. Most individuals prefer to copy and paste data manually. It is not possible, however, to do so for huge websites with hundreds of pages. Sometimes, websites may contain data you cannot copy and paste; how will you copy that data then? Would you write down whatever you saw word for word? This is where web scraping appears to be beneficial.

What is Web Scraping?

Web scraping is a way of automatically obtaining huge volumes of data from websites. In other words, it is the technique of automating data extraction in an effective and timely manner allowing you to scrape data from any website, no matter how huge the data. The majority of this data is unstructured HTML data. Different methods are being use to scrape data. These include leveraging internet services, specific APIs, or even writing your own web scraping scripts from scratch. Many big websites, such as Google, Facebook, StackOverflow, and others, have APIs that allow you to access their data in a structured way. There are other websites that do not provide people with access to vast volumes of data in an organized format. In that case, it is best to scrape the website for data using Web Scraping.

Web Scraping Fundamentals

Web scraping is a basic process that consists of two components: a web crawler and a web scraper. Essentially, the crawler guides the scraper through the internet. Let us have a better understanding of these two concepts.

A web crawler, often known as a “spider,” downloads and analyses information from all across the Internet. The objective of such a bot is to learn about nearly every webpage on the internet.

Web Scraping, on the other hand, concentrates on a specific collection of data on a website. These may be stock prices, sports statistics, financial information, or any other type of data collection.

A web scraper is a powerful tool intended to collect data from a web page properly and rapidly. The style and complexity of web scrapers vary greatly depending on the problem. The data locators used to discover the data you wish to extract from the HTML file are an essential element of any scraper. CSS selectors, XPath, regex, or a mix of these are commonly used.

Applications of Web Scraping

  • Price Tracking: Businesses can use web scraping to collect product information for their own items as well as competitors’ products to evaluate how it affects their pricing strategies. This data can be used by businesses to identify the best pricing for their commodities in order to maximize income. Extracting product and pricing information from e-commerce websites and converting it into intelligence is a key element of contemporary e-commerce firms that wish to make better marketing data-driven decisions.
  • Market Research: Companies can utilize web scraping for market research. Elevated online scraped data acquired in big quantities can be extremely beneficial to businesses in assessing customer patterns and determining which path the firm should take in the future. It allows market analysts to concentrate their efforts on giving strategic insights based on the information gathered.
  • Finance: Analysts require financial documents in order to assess a company’s performance and advise their clients on whether or not to invest in it. Web scraping technologies are being used to gather financial statements from various sites.
  • Promotion through Emails: Web scraping can also be used for email marketing by corporations. They can use web scraping to acquire Email IDs from numerous sites and then send mass promotional and marketing emails to everyone who has these Email IDs.
  • News Tracking: Web scraping news sites can supply a firm with thorough reports on current events. This is especially important for firms that are regularly in the news or rely on daily news for their day-to-day operations. After all, in a single day’s news, modern media can deliver great value or an existential danger to your firm.
  • Machine Learning Algorithms: Web scraping is being used to collect data from the internet and make it available to ML training models.

One of the most commonly asked questions when it comes to web scraping. Web scraping is a tool, just like any other. It has both good and evil purposes. Web scraping is not unlawful in and of itself. It all depends on what your objective is while you are web scraping and what you plan to do with the data you collect. Scraping non-public information is one example; as self-explanatory as it seems, it is not available to the public. If you’re attempting to gain access to it, you may be breaking the law.

Web Scraping Tools

There are a number of web scraping tools available to assist you in extracting data. We’ll go over some of those tools briefly before diving further into one of them.

  • ScrapeSimple is the ideal solution for anyone looking to have a customized web scraper tool developed for them. It is quick, free, and easy to use.
  • Octoparse is a wonderful scraper tool for those who wish to extract data from websites without needing to code, but still having complete control over the entire process solely because of its simple user interface.
  • Scrapy is an open source online scraping toolkit for Python developers that want to create robust web crawlers. It’s a full web crawling framework that covers all of the infrastructure that makes creating web crawlers complex, such as queueing and requests.
  • Diffbot is an enterprise-level solution for businesses with extremely specific data crawling and screen scraping requirements, particularly those that scrape websites that often modify their HTML structure.
  • BeautifulSoup is an open source library mostly for Python programmers who desire a simple interface for parsing HTML but don’t need the power and complexity of Scrapy.
  • Webhose.io is suitable for platforms or businesses that require a fully built web scraper for content marketing. Its content indexing is rather quick. The platform’s pricing is fairly reasonable for developing businesses. It also provides access to historical feeds dating back up to ten years.
  • Mozenda is a cloud-based self-service solution for businesses. It offers phone and email assistance to all clients and is a highly scalable platform.
  • Scraper API is an easy-to-integrate tool for web scraper developers. It handles proxies, CAPTCHAs, and browsers, allowing developers to retrieve raw HTML from any website with a single API request.
  • ParseHub is a sophisticated tool for creating web scrapers without coding that has an easy-to-use graphical interface. It can extract data from tables and maps and has an automatic IP rotation. Analysts, data scientists, and everyone in between uses it.

Why should you use Python for Web Scraping?

  • Libraries: Python includes a large number of libraries, such as Numpy, Scrapy, BeautifulSoup, and Pandas, that provide techniques and functions for a variety of uses. As a result, it is appropriate for web scraping and subsequent processing of collected data.
  • Community: Python has one of the largest and most active communities where you can seek assistance if you are experiencing complicated challenges while programming and are unable to find a solution.


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