Web scraping Explained: How It Works, Types, and Use Cases

There are plenty of web scraping tools that can seamlessly collect massive amounts of data from any website. In this article, we will discuss everything you need to know about web scraping, including how it works, the types you can choose from, and the reasons you may consider using it. So, without wasting any more of your time, let’s jump right in.

Key Takeaways

• Web scraping is an automated way to extract large amounts of data from websites quickly, efficiently, and at scale. 
• Scraped data is used for tasks such as machine learning model training, price tracking, competitor analysis, market research, and trend monitoring.
• Web scraping tools can be classified by development type, platform and execution environment.
• Web scraping is legal when collecting publicly available data and not violating websites’ terms of service.
• The key benefits of web scraping include faster data extraction, reduced costs, better decision-making, scalability, and flexibility.
• Web scraping alternatives include APIs, open datasets, and data partnerships.

Understanding web scraping

Web scraping is the process of automatically extracting data from a website or any online platform using dedicated tools called web scrapers. This automated data extraction process allows businesses and researchers to automatically collect large amounts of data from websites without having to manually copy anything. 

The web scraping tools visit the target websites, reads the HTML, finds the data needs and then saves it in a clean format such as CSV, JSON, or a database. This data collected during web scraping can further be cleaned and used for several tasks such as machine learning models training, price tracking, competitor analysis, market research, monitoring news or trends, and more.

How Web Scrapers Work

Web scrapers work by sending a request to the target webpage, receiving the page’s HTML, and then extracting the specific data you need based on your web scraping projects configurations. A web scraping tool only extracts specific data, which helps to avoid collecting a lot of useless data that costs money and wastes time. 

The data collected after a web scraping task is then saved in formats like CVS, JSON, or any other format of your choice ready for processing. Let’s explore all the automated processes web scraping tools follow in more detail. 

Web Scraping End-to-End Flow

• Sending requests: The data scraping tool sends an HTTP request to a webpage just like a browser does.
• Receiving and parsing HTML: It downloads the HTML and reads through the tags to find the needed data as specified in your configurations.
• Handling pagination: Web crawlers follow “next page” links or page numbers to reach all available contents on the website or platform being scrapped. 
• Extracting data: The scraping tool pulls details such as text, prices, or images from each page. 
• Saving results and structuring data: The extracted data is then stored in a structured format like CSV, JSON, or a database for easy analysis.

The Crawler vs. The Scraper

It is pretty common for people to confuse these two terms. Even though both scrapers and crawlers are used during data extraction, they play different roles. 

• Crawler: A crawler is responsible for discovering webpages of a given website or online service. It crawls through pages by following links, identifying new URLs, and mapping the site. 
• Scrapper: On the other hand, a scraper extracts data from websites. It reads the HTML on each page discovered by the crawler and pulls out the exact data you need. The exact data extracted by scrapers from a given web page depends on how you configure them.  

Types of Web Scrapers

Web scraping tools today are categorized based on how they are built or deployed. Let’s explore some of the popular choices available.   

Based on Development Type

With this category, we have custom-built and pre-built data scraping tools. Here is how they differ: 

• Custom-built scraping tools: These are coded from scratch using programming languages like Python or JavaScript. Developers usually use a library like BeautifulSoup to speed up the process. Since they are built from scratch, these data scraping tools offer full control and can handle complex sites, and scale well. However, writing scrapers from scratch with languages like Python requires technical skills, more maintenance, and are generally more expensive to build. 
• Pre-built web scraping tools: These web scraping services come ready to use with point-and-click interfaces, making them more ideal for those who need to get started as soon as possible. They are easy for beginners and save time. However, pre-built web scraping software usually offers less flexibility and may struggle with very complex websites.

The choice between custom and pre-built snappers largely depends on the web scraping task at hand, technical expertise, and whether you need to get started immediately. If you want to build scrapers to handle complex specialized tasks, you may need to write one from scratch with Python.

Based on Platform

In this category, we have three options; browser extensions, standalone apps, and API-based solutions. Here are their key differences. 

• Browser extensions: These are simple tools that run inside browsers such as Google Chrome or Safari. They are usually good for small tasks but offer limited scalability and automation capabilities.
• Standalone desktop software: These scrappers are more powerful than extensions. They require installation on your computer and are typically designed to handle larger projects than extensions. However, the performance of these scrappers still relies on the resources of the device they are installed on. 
• API-based solutions: These scrappers skip HTML content parsing and return clean, structured data directly through an API. This type offers the fastest speeds since they depend on cloud resources that can be configured to any capacity depending on one’s budget. They’re also much more scalable than browser extensions and standalone software scrappers. 

Based on Execution Environment

Here we have two types; local scripts and cloud-based scrappers. 

• Local scripts: These are scripts (such as python scripts) designed to run locally on your machine. They are easy to control but may be slow, unreliable for large tasks, and harder to maintain since these data scraping tools rely on the hardware capabilities of your local machine. 
• Cloud-based data scraping tools: Like you may have guessed, these scrappers run on cloud servers, allowing them to offer better speed, uptime, and scalability. They handle maintenance and IP rotation more effectively than local scripts. The only downside is that they are usually more expensive. However, their pricing varies based on usage, so users can find a perfect balance of cost and utility based on their needs.  

Why Is Python So Popular for Web Scraping?

Python is by far the most used language for writing web scraping scripts. The main reason behind its popularity are its massive library options that are available for developers to use when writing their scripts. Some of the popular Python library options used for web scraping include 

Requests (for sending HTTP requests), BeautifulSoup and lxml ( handle HTML parsing), and Scrapy that offers a full web scraping framework with web crawling. Using a Python library like BeautifulSoup to write scripts makes the developers work a lot easier. 

What Is Web Scraping Used For?

Web scraping has several real world applications across different industries. Some of the most common real world applications include: 

Price Monitoring

Businesses and researchers use web scraping to track product prices across multiple websites. The data collected is then used to create strategies that enable them to stay competitive, adjust pricing tactics, or monitor market changes in real time.

Market Research

Before investing in any business, doing market research is one of the first steps. By using web scraping, companies can collect data on competitors, products, customer reviews, and industry trends. This data helps understand demand, supply, and several other metrics that are crucial for success.

News & Content Monitoring

Organizations and digital marketers often gather articles, blog posts, and updates from different sources to stay informed or power content aggregation platforms. They use web scraping to collect this data from multiple sources and then analyze it using machine learning algorithms to extract the most useful insights. 

Sentiment Analysis

This is common especially in the finance sector. Many financial firms scrape social media posts, reviews, and comments on various platforms and forums to understand public opinion about products, services, or brands. This allows them to make decisions based on real user sentiment and not assumptions. 

Lead Generation

Sales teams and digital marketing agencies extract user data such as contact details, business profiles, and listings from directories and websites to build targeted lead lists. This data is then fed in sales management and CRM tools like salesforce to follow up on these leads.

Is web scraping Legal?

Web scraping in itself is not illegal. However it depends on how and where it is done. Here are some of the key things you need understand about the legality of web scraping: 

• Public data is generally safe to scrape: Any information that is publicly available on websites that don’t require authentication can be scrapped.
• Terms of service matter: There are some websites and platforms that clearly ban web scraping. So, ignoring these rules can lead to legal penalties if detected. Your data scraping tools will be blocked if you try to use them to extra data from such websites.
• Traffic volume: Triggering many web scraping tasks on one website can overload its servers, leading to slowdowns. Websites usually block access if they detect too many requests coming from the same IP address. 
• Copyright laws still apply: Even though you can scrape publicly available data, you still have to use it within the copyright rules. 

Benefits and Business Value of web scraping

• Faster data extraction: web scraping automates the process of gathering data from many websites. Automating the data collection process is more time efficient than doing it manually. 
• Cost-effective: web scraping is also more cost effective compared to doing manual research.
• Better decision-making: It provides businesses with a lot of data that can be fed into intelligent systems for analytics purposes. Insights from these systems are used by business leaders to make better decisions. 
• Competitive advantage: By web scraping data from competitor websites, you can quickly analyze their offerings, allowing you to optimize your strategy to offer more value to your target customers.
• Scalable: By web scraping, you can collect thousands or even millions of records without extra manual work.
• Customizable and flexible: Web scrappers can be configured to extract exactly the type of data you need, from any number of sites.

Web Scraping Challenges and Best Practices

Despite the benefits, web scraping has a number of challenges that you must be aware of before doing it. Let’s discuss some of these challenges and the best practices to overcome them: 

Handling Anti-Bot Protection

There are many websites that use tools like CAPTCHAs, rate limits, and IP blocking to stop bots from accessing and web scraping data. To deal with the challenge, you may need to slow down request speeds or rotate IP addresses using residential or mobile web scraping proxies. These web scraping proxies allow you to use different IPs for your requests, minimizing the chances of IP blocks. 

Maintaining Data Accuracy and Quality

It is common for websites to change their layouts, which can break your data scraping tool and lead to missing or collecting incorrect data. To keep data clean, you should validate the results, monitor scraper errors, and update your scraper tools’ code when website structure changes are detected.

Staying Ethical and Compliant

Web scraping should always follow legal and ethical rules. Avoid web scraping websites that don’t allow bots to access their web pages. Also ensure to only scrap data that is publicly available and use it without in the copyright rules. 

Alternatives to web scraping

If web scraping is not the best option for your use case, here are some alternatives you use to reliably collect data: 

• APIs: There are several platforms such as social media and e-commerce websites that give developers APIs that they can use to access some of their data. APIs provide structured data directly from the platform without having to parse HTML.
• Open Datasets: Governments, research institutions, and large organizations publish open datasets that anyone can use to collect data. Data offered on such databases include topics like demographics, transportation, finance, health, and environmental trends.
• Data Partnerships: You may also choose to partner with the companies whose data you need. Alternatively, businesses can buy data from trusted data providers. Buying data from data providers can often be more expensive, but it gives businesses access to more clean data without going through the struggles of web scraping it yourself. 

Final Thoughts

Web scraping is an effective strategy that many businesses use to collect data from the internet quickly and at scale. It allows them to gather information they can feed into different systems for insights that lead to better decisions, or use directly for tasks like sales campaigns and promotions. 

However, it is crucial for businesses web scraping data to do it responsibly to avoid ending up on the wrong side of the law. Finally, businesses must also consider the cost efficiency of data scraping and whether they can use other methods to access cleaner data, even if it comes at an extra cost.

FAQs

Is web scraping detectable by websites?

Yes. Websites can detect web scraping by tracking parameters like unusual traffic spikes, missing browser headers or seeing a lot of blocked IPs trying to access their servers. Using web scraping proxies may be necessary to minimize the chances of detection and IP blocks. 

How can I scrape a website for free?

There are several open source software tools that you can use to scrape data. Some of the popular ones include BeautifulSoup, Requests, or several browser extensions. The tools available for web scraping will continue to get better and smarter in the coming years thanks to the progress being made in the AI space. 

What is the safest way to scrape data legally?

By web scraping only public pages, respective websites’ terms of services, and using the web scraps with the copyright laws in mind. 

What programming languages besides Python can be used for web scraping?

JavaScript (Node.js), Ruby, PHP, Go, and Java all offer robust web scraping libraries that developers can use to write their web scraping scripts. 

What’s the difference between web scraping and data mining?

Web scraping primarily involves collecting raw data from websites whereas data mining focuses on analyzing large datasets to find patterns and insights.