Web Scraping vs Web Crawling

The term web scraping vs web crawling have been all over the place because of the role it plays in the web data extraction process. Various industries have been increasingly using web data extraction to leverage its benefits. But what we fail to realize is the difference between the two terms; people often confuse them for the same thing. This not only creates confusion but disrupts the whole process.

Here is an article that gives a brief about web scraping and web crawling and ultimately talks about the key difference between both two processes.

Quick Recap: Web Scraping & Web Crawling

Before we dive into the analysis of web scraping vs web crawling, it is crucial to gain insights into each process. This section will give you a quick recap of both the processes.

Web Scraping

Web scraping, also known as web harvesting, is a technique of extracting data from website(s) using tools known as web scrapers. These scrapers fetch data and information from targeted websites and pages and store the data in a structured format for further analysis and processing.

The process of web scraping involves 4 main steps: sending a request to the target page; getting a response from the target page; parsing and extracting data; and lastly, downloading the data in Excel, XML, or SQL format.

The whole process of web scraping is done manually and requires a crawl agent and parser for the successful completion of web scraping. One of the key applications of web scraping includes developing data for machine learning.

Web Crawling

Web crawling is a process that systematically browses the internet to discover, index, and analyze content on various websites and web pages. This process is done with the help of tools known as web scrapers or spiders. This process is done essentially by search engines to index pages and display them in relevant search results.

The process of web crawling involves analyzing a series of web pages via a spider bot (a crawling agent). Furthermore, the main reason behind doing this is to find out the relevant URLs and domains and collect data about each page the spiders visit.

One of the key applications of web crawling is search engine optimization or SEO. This process ensures that each website and web page is crawled and indexed properly to boost its visibility and to make sure it appears in the search results.

Table of Difference: Web Scraping vs Web Crawling

Factors of Differentiation

Several factors were considered while analyzing the web scraping vs web crawling. Some of the factors are given below to help you understand the parameters of differentiation better.

1. Purpose

The first and foremost factor of differentiation is the purpose you can use these processes for. The web scraping process is for extracting data from websites. On the other hand, the web crawling process is done to find links and URLs on the web.

2. End Result

The next factor of differentiation on the list is the end result or output received after the successful completion of the respective process. Both the processes of data extraction generate different results. The web scraping process is all about data and extracts data fields from specific websites in structured format. Whereas, the web crawling process generates a list of URLs and domains, which can then be used for web scraping.

3. Scale of Operation

This factor talks about the scale of operation on which you can carry out individual processes on. Web scraping is needed and performed on projects ranging from small-scale projects to large-scale projects. Contrary to web scraping, web scraping is carried out only on large-scale projects to index a vast number of websites at once.

4. ‘Robots.txt’ File

A robots.txt file is a document within the root directory of a website, clearly stating which pages and sections you can and cannot be crawl. While web scrapers disregard and don’t obey these ‘robots.txt’ files, web crawlers or spiders often obey and adhere to the instructions provided. Due to disregard for the instructions, the probability of web scrapers getting into legal trouble is high as compared to web spiders.

5. Applications

This factor of differentiation covers various applications of web crawlers and web scrapers across various industries. The key applications of web scraping are product data aggregation, market research for several different fields, and price monitoring. On the other hand, the key applications of web crawling include monitoring website changes, search engine indexing, and sentiment analysis.

6. Tools Used

The tools for web scraping are known as web scrapers and some of the popular web scrapers include ProWebScraper and Webscrape.io. On the contrary, the tools for web crawling are known as web crawlers or spiders. Some of the famous spiders are Scrapy and Apache Nut.

7. Data Deduplication

The last on the list of factors of differentiation is data duplication. Data deduplication is the process of eliminating duplicate copies of repetitive data to reduce storage usage and cost. Web scrapers don’t focus on data deduplication due to their focus on extracting specified data points. Whereas, web crawlers consider data deduplication an integral part of the process due to the presence of vast duplicate data.

Applications: Web Scraping vs Web Crawling

This section of the blog explores the various real-life applications of web scraping as well as web crawling.

Web Scraping

1. Price Monitoring

Users, especially retailers, can use web scrapers to scrape competitor’s pricing and product availability. You can then use this to adjust your pricing strategies.

2. Product Data Aggregation

You can leverage web scrapers to collect data like images, descriptions, reviews, etc from platforms like Amazon and eBay. This can further help in inventory management and enhance the customer experience.

3. Market Research

You can use web scraping tools for scraping data, for identifying market trends, understanding consumer preferences, and monitoring any competitive products.

4. Data collection for ML models

You can use web scraping to gather a diverse variety of datasets that you can then use for training machine learning models.

Web Crawling

1. Search Engine Indexing

You can use the web crawlers to systemically browse the internet, download pages, and extract relevant information. This helps improve result accuracy and efficiency.

2. Content Aggregation

Web crawlers go through multiple pages and compile all the content into a single database, you can then used this to create detailed reports and dashboards.

3. Monitoring Website Changes

Web crawlers revisit the same web pages after regular intervals to check for changes in the website. They crawl the web pages again and then compare them with the previous versions to identify any changes.

4. Sentiment Analysis

Users can use web crawlers to gauge public sentiments by analyzing social media and reviewing sites about an individual product or service. You can use these analyses to make efficient decisions and strategize marketing campaigns.

Conclusion

Web scraping and web crawling, when combined, form the very base of the data extraction process. While the sole purpose for doing this might differ, the end goal is the same. Without web crawling, the user can proceed further with the data extraction process.

The web crawlers go through each website or page and analyze them to segregate them into various categories. The web scrapers send requests to the target page to parse and extract data in XML/Excel/SQL format for further processing. Both processes are of great importance not just to the data extraction community but to other industries as well.

So, we can be conclude that instead of working against each other, the web scraping and web crawling processes work together to give you a smooth and efficient web data extraction process.