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How to Extract Data from A Website?

Iveta Vistorskyte

2021-11-29
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We live in an era when making data-driven business decisions is the number one priority for many companies. To fuel these decisions, companies track, monitor, and record relevant data 24/7. Fortunately, there is a lot of public data stored on servers across websites that can help businesses to stay sharp in the competitive market. 

It has become common for various companies to extract data for their business purposes. However, this is not one of those processes that you can implement in your day to day operations before getting informed. For this reason, in this article, we shall go through how web data extraction works, its main challenges, and introduce you to several solutions that can help you as you go further up the data scraping path.

Extracting data: how it works

If you are a not-that-tech-savvy person, understanding how to extract data can seem like a very complex and incomprehensible matter. However, it is not that complicated to comprehend the entire process.

The process of extracting data from websites is called web scraping. Sometimes you can find it referred to as web harvesting as well. The term typically refers to an automated process that is created with intention to extract data using a bot or a web crawler. Sometimes the concept of web scraping is confused with web crawling. For this reason, we have covered this issue in our other blog post about the main differences between web crawling and web scraping.

Now, we will discuss the whole process to fully understand how to extract web data.

What makes data extraction possible

Nowadays, the data we scrape is mostly represented in HTML, a text-based mark-up language. It defines the structure of the website’s content via various components, including tags such as <p>, <table>, and <title>. Developers are able to come up with scripts that pull data from any manner of data structures.

Building data extraction scripts

Programmers skilled in programming languages like Python can develop web data extraction scripts, so-called scraper bots. Python advantages such as diverse libraries, simplicity, and active community make it the most popular programming language for writing web scraping scripts. These scripts can scrape data in an automated way. They send a request to a server, visit the chosen URL, go through every previously defined page, HTML tag, and components. Then they pull data from them.

Developing various data crawling patterns

Scripts that are used to extract data can be custom-tailored to extract data from only specific HTML elements. The data you need to get extracted depends on your business goals and objectives. There is no need to extract everything when you can specifically target just the data you need. This will also put less strain on your servers, reduce storage space requirements, and make data processing easier.

Setting up the server environment

To continually run your web scrapers, you need a server. So the next step in this process is investing in server infrastructure or renting servers from an established company. Servers are a must-have as they allow you to run your previously written scripts 24/7 and streamline data recording and storing.

Ensuring there is enough storage space

The deliverable of data extraction scripts is data. Large scale operations come with high storage capacity requirements. Extracting data from several websites translates into thousands of web pages. Since the process is continuous, you will end up with huge amounts of data. Ensuring there is enough storage space to sustain your scraping operation is very important.

Data processing

Acquired data comes in raw form and may be hard to comprehend to the human eye. Therefore, parsing and creating well-structured data is the next important part of any data gathering process.

How to extract data from the web

There are several ways to extract public data from a webpage – building an in-house tool or using ready-to-use web scraping solutions. Both options come with their own strengths; let’s look at each to help you easily decide what suits your business needs best.

In-house solution

To develop in-house web data extraction tools, you’ll need a dedicated web scraping stack. Here’s what it’ll include:

Proxies. Many websites differentiate content they display based on the IP address location. You might need another country’s proxy, depending on where your servers and targets are.

A large proxy pool will also aid in avoiding IP blocks and CAPTCHAs.

Headless browsers. An increasing number of websites are using frontend frameworks like Vue.js or React.js. Such frameworks employ backend APIs to fetch data and rendering to draw the DOM (Document Object Model). Regular HTML client wouldn’t render the Javascript code; thus, without a headless browser, you’d get an empty page.

Also, websites often detect if HTTP clients are bots. In this case, headless browsers can aid in accessing the target HTML page.

The most popular APIs for headless browsers are Selenium, Puppeteer, and Playwright.

Extraction rules. It’s a set of rules that you’ll use to choose HTML elements and extract data. The simplest ways to select these components are XPath and CSS selectors.

Websites are continuously updating their HTML code. As a result, extraction rules are the aspect on which developers spend most of their time. 

Job scheduling. This allows you to schedule when you’d like to, let’s say, monitor specific data. It also aids in error handling: it’s essential to track HTML changes, target website’s or your proxy server’s downtime, and blocked requests.

Storage. Once you extract the data, you’ll need to store it somewhere, like in an SQL database. Standard formats for saving gathered data are JSON, CSV, and XML.

Monitoring. Especially extracting data at scale might cause multiple issues. To avoid them, you need to make sure your proxies are always working properly. Logs analysis, dashboard, and alerts can aid you in monitoring data. 

Here are the main stages of how to extract data from a web: 

1. Decide the type of data you want to fetch and process.

2. Find where the data is displayed and build a scraping path. 

3. Import and install the required prerequisites.

4. Write a data extraction script and implement it.

Imitating the behavior of a regular internet user is essential in order to avoid IP blocks. This is where proxies step in and make the entire process of any data harvesting task easier. We will come back to this later.

Web Scraper API

One of the main benefits of ready-to-use web data extraction tools like Web Scraper API is its ability to help you extract public data from challenging targets without additional resources. Large e-commerce web pages make use of sophisticated anti-bot algorithms. Therefore, scraping them requires extra development time.

In-house solutions would have to create workarounds through trial and error, which means inevitable slowdowns, blocked IP addresses, and an unreliable flow of pricing data. With our web scraping tool, Web Scraper API, the process is entirely automatic. Instead of endlessly copy-pasting, your employees will be able to focus on more pressing matters and move straight to data analysis.

Which one to choose?

Whether it’s better to build an in-house solution yourself or get a ready-to-use data extraction tool closely depends on the size of your business.

If you’re an enterprise willing to collect data at a large scale, tools like Web Scraper API are the right choice: they’ll save you time and provide real-time quality results. On top of that, you’ll save your expenses on code maintenance and integration.

However, smaller businesses scraping the web only at times might fully benefit from developing their own in-house data extraction tool.

Benefits of web data collection

Big data is a new buzz word in the business world. It encompasses various processes done on data sets with a few goals – gaining meaningful insights, generating leads, identifying trends and patterns, and forecasting economic conditions. For example, web scraping real estate data helps to analyze essential influences in this industry. Similarly, alternative data can help fund managers to reveal investment opportunities.

Another field where web scraping can be useful is the automotive industry. Businesses collect automotive industry data such as users and auto parts reviews, and much more.

Various companies extract data from websites to make their data sets more relevant and up-to-date. This practice often extends to other websites as well, so that the data set can be complete. The more data, the better, as it provides more reference points and renders the entire data set more valid.

Which data do businesses target for extraction?

As we mentioned earlier, it is understandable that not all online data is the target of extraction. Your business goals, needs, and objectives should serve as main guidelines when deciding which data to pull.

There can be loads of data targets that could be of interest to you. You can extract product descriptions, prices, customer reviews and ratings, FAQ pages, how-to guides, and more. You can also custom-tailor your scripts to target new products and services. Just make sure that you are scraping public data and not breaching any third party rights before conducting any scraping activities.

Web scraping for business is highly needed to stay competitive in the market

Common data collection challenges

Extracting data doesn’t come without challenges. The most common ones are:

  • Resources and knowledge. Data gathering requires a lot of resources and professional skills. If companies decide to start web scraping, they need to develop a particular infrastructure, write scraper code, and oversee the entire process. It requires a team of developers, system administrators, and other specialists.

  • Maintaining data quality. Maintaining data quality across the board is of vital importance. At the same time, it becomes challenging in large-scale operations due to data amounts and different data types.

  • Anti-scraping technologies. To ensure the best shopping experience for their consumers, e-commerce websites implement various anti-scraping solutions. In web scraping, one of the most important parts is to mimic organic user behavior. If you send too many requests in a short time interval or forget to handle HTTP cookies, there is a chance that servers will detect the bots and block your IP.

  • Large-scale scraping operations. E-commerce websites regularly update their structure, requiring you to update your scripts constantly. Prices and inventory are also subject to constant change, and you need to keep the scripts going always running.

Best practices of data scraping

The challenges related directly to web data collection can be solved with a sophisticated web data extraction script developed by experienced professionals. However, this still leaves you exposed to the risk of getting picked up and blocked by anti-scraping technologies. This calls for a game-changing solution – proxies. More precisely, rotating proxies.

Rotating proxies will provide you with access to a large pool of IP addresses. Sending requests from IPs located in different geo regions will trick servers and prevent blocking. Additionally, you can use a proxy rotator. Instead of manually assigning different IPs, the proxy rotator will use the IPs in the proxy data center pool and automatically assign them.

If you do not have the resources and team of experienced developers to start web scraping, it is time to consider a ready-to-use solution such as a Web Scraper API. It ensures high data delivery success rates from most websites, streamlines data management, and aggregates data for easier understanding.

While many businesses rely on big data, the demand has grown significantly. According to research by Statista, the big data market is increasing enormously every year and is forecasted to reach 103 billion U.S. dollars by 2027. It leads to more and more businesses adopting web scraping as one of the most common data collection methods. Such popularity evokes a widely discussed question of whether web scraping is legal. 

Since this complex topic has no definite answer, one must ensure that any carried out web scraping does not breach any laws surrounding the said data. It is important to note that before engaging in any scraping activity, we firmly suggest seeking professional legal consultation regarding the specific situation.

Also, we strongly urge you to stay away from scraping any data that is non-public unless you have explicit permission from the target website. For clarity, nothing that was written in this article should be interpreted as advice of scraping any non-public data.

If you want to learn more about web scraping legality, read our article Is web scraping legal?  where we have covered the topic in detail from the ethical and technical side.

Conclusion

To sum it up, you will need a data extraction script to extract data from a website. As you can see, building those scripts can be challenging due to the scope of operation, complexity, and changing website structures. Since web scraping has to be done in real-time to get the most recent data, you will have to avoid getting blocked. This is why major scraping operations run on rotating proxies.

If you feel that your business requires an all-in-all solution that makes data collection effortless, you can contact us at hello@oxylabs.io.

About the author

Iveta Vistorskyte

Lead Content Manager

Iveta Vistorskyte is a Lead Content Manager at Oxylabs. Growing up as a writer and a challenge seeker, she decided to welcome herself to the tech-side, and instantly became interested in this field. When she is not at work, you'll probably find her just chillin' while listening to her favorite music or playing board games with friends.

All information on Oxylabs Blog is provided on an "as is" basis and for informational purposes only. We make no representation and disclaim all liability with respect to your use of any information contained on Oxylabs Blog or any third-party websites that may be linked therein. Before engaging in scraping activities of any kind you should consult your legal advisors and carefully read the particular website's terms of service or receive a scraping license.

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IN THIS ARTICLE


  • Extracting data: how it works

  • How to extract data from the web

  • Benefits of web data collection

  • Which data do businesses target for extraction?

  • Common data collection challenges

  • Best practices of data scraping

  • Is it legal to extract data from websites?

  • Conclusion

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