Web Scraping Companies

WebMonday, January 18, 2021

Web scraping (also termed web data extraction, screen scraping, or web harvesting) is a technique of extracting data from the websites. It turns unstructured data into structured data that can be stored into your local computer or a database.

It can be difficult to build a web scraper for people who don’t know anything about coding. Luckily, there are tools available for people with or without programming skills. Also, if you're seeking a job for big data developers, using web scraper definitely raises your working effectiveness in data collection, improving your competitiveness. Here is our list of 30 most popular web scraping tools, ranging from open-source libraries to browser extension to desktop software.

Table of Content

1. Beautiful Soup

Who is this for: developers who are proficient at programming to build a web scraper/web crawler to crawl the websites.

Why you should use it: Beautiful Soup is an open-source Python library designed for web-scraping HTML and XML files. It is the top Python parsers that have been widely used. If you have programming skills, it works best when you combine this library with Python.

Web Scrape - A Trusted by Fortune 500 Business & Enterprises Why Should you choose us as Your Outsourced Web Scraping Service Provider? We are one of the leading web scraping service providers based in the USA. Our data scraping services are best suited to clients who look for extensive data extraction from specific websites.

  • Web Scraping in R: rvest Tutorial Explore web scraping in R with rvest with a real-life project: extract, preprocess and analyze Trustpilot reviews with tidyverse and tidyquant, and much more! Trustpilot has become a popular website for customers to review businesses and services.
  • Research companies need to extract massive amounts of data from various sites to make sense of it. Such tasks can be carried out more effectively with web scraping software. Web Scraping Software is data scraping used for extracting data from websites. Web scraping a web page involves fetching it and extracting from it.

2. Octoparse

Who is this for: People without coding skills in many industries, including e-commerce, investment, cryptocurrency, marketing, real estate, etc. Enterprise with web scraping needs.

Why you should use it: Octoparse is free for life SaaS web data platform. You can use to scrape web data and turns unstructured or semi-structured data from websites into a structured data set. It also provides ready to use web scraping templates including Amazon, eBay, Twitter, BestBuy, and many others. Octoparse also provides web data service that helps customize scrapers based on your scraping needs.

3. Import.io

Who is this for: Enterprise looking for integration solution on web data.

Why you should use it: Import.io is a SaaS web data platform. It provides a web scraping solution that allows you to scrape data from websites and organize them into data sets. They can integrate the web data into analytic tools for sales and marketing to gain insight from.

4. Mozenda

Who is this for: Enterprise and business with scalable data needs.

Why you should use it: Mozenda provides a data extraction tool that makes it easy to capture content from the web. They also provide data visualization services. It eliminates the need to hire a data analyst.

5. Parsehub

Who is this for: Data analyst, Marketers, and researchers who lack programming skills.

Why you should use it: ParseHub is a visual web scraping tool to get data from the web. You can extract the data by clicking any fields on the website. It also has an IP rotation function that helps change your IP address when you encounter aggressive websites with anti-scraping techniques.

6. Crawlmonster

Who is this for: SEO and marketers

Why you should use it: CrawlMonster is a free web scraping tool. It enables you to scan websites and analyze your website content, source code, page status, etc.

7. ProWebScraper

Who is this for: Enterprise looking for integration solution on web data.

Why you should use it: Connotate has been working together with Import.io, which provides a solution for automating web data scraping. It provides web data service that helps you to scrape, collect and handle the data.

8. Common Crawl

Who is this for: Researchers, students, and professors.

Why you should use it: Common Crawl is founded by the idea of open source in the digital age. It provides open datasets of crawled websites. It contains raw web page data, extracted metadata, and text extractions.

9. Crawly

Who is this for: People with basic data requirements.

Why you should use it: Crawly provides automatic web scraping service that scrapes a website and turns unstructured data into structured formats like JSON and CSV. They can extract limited elements within seconds, which include Title Text, HTML, Comments, DateEntity Tags, Author, Image URLs, Videos, Publisher and country.

10. Content Grabber

Who is this for: Python developers who are proficient at programming.

Why you should use it: Content Grabber is a web scraping tool targeted at enterprises. You can create your own web scraping agents with its integrated 3rd party tools. It is very flexible in dealing with complex websites and data extraction.

11. Diffbot

Who is this for: Developers and business.

Why you should use it: Diffbot is a web scraping tool that uses machine learning and algorithms and public APIs for extracting data from web pages. You can use Diffbot to do competitor analysis, price monitoring, analyze consumer behaviors and many more.

12. Dexi.io

Who is this for: People with programming and scraping skills.

Why you should use it: Dexi.io is a browser-based web crawler. It provides three types of robots — Extractor, Crawler, and Pipes. PIPES has a Master robot feature where 1 robot can control multiple tasks. It supports many 3rd party services (captcha solvers, cloud storage, etc) which you can easily integrate into your robots.

13. DataScraping.co

Who is this for: Data analysts, Marketers, and researchers who're lack of programming skills.

Web Scraping Companies

Why you should use it: Data Scraping Studio is a free web scraping tool to harvest data from web pages, HTML, XML, and pdf. The desktop client is currently available for Windows only.

14. Easy Web Extract

Who is this for: Businesses with limited data needs, marketers, and researchers who lack programming skills.

Why you should use it: Easy Web Extract is a visual web scraping tool for business purposes. It can extract the content (text, URL, image, files) from web pages and transform results into multiple formats.

15. FMiner

Who is this for: Data analyst, Marketers, and researchers who're lack of programming skills.

Why you should use it: FMiner is a web scraping software with a visual diagram designer, and it allows you to build a project with a macro recorder without coding. The advanced feature allows you to scrape from dynamic websites use Ajax and Javascript.

16. Scrapy

Who is this for: Python developers with programming and scraping skills

Why you should use it: Scrapy can be used to build a web scraper. What is great about this product is that it has an asynchronous networking library which allows you to move on to the next task before it finishes.

17. Helium Scraper

Who is this for: Data analysts, Marketers, and researchers who lack programming skills.

Why you should use it: Helium Scraper is a visual web data scraping tool that works pretty well especially on small elements on the website. It has a user-friendly point-and-click interface which makes it easier to use.

18. Scrape.it

Who is this for: People who need scalable data without coding.

Why you should use it: It allows scraped data to be stored on the local drive that you authorize. You can build a scraper using their Web Scraping Language (WSL), which is easy to learn and requires no coding. It is a good choice and worth a try if you are looking for a security-wise web scraping tool.

19. ScraperWiki

Who is this for: A Python and R data analysis environment. Ideal for economists, statisticians and data managers who are new to coding.

Why you should use it: ScraperWiki consists of 2 parts. One is QuickCode which is designed for economists, statisticians and data managers with knowledge of Python and R language. The second part is The Sensible Code Company which provides web data service to turn messy information into structured data.

20. Scrapinghub

Who is this for: Python/web scraping developers

Why you should use it: Scraping hub is a cloud-based web platform. It has four different types of tools — Scrapy Cloud, Portia, Crawlera, and Splash. It is great that Scrapinghub offers a collection of IP addresses covering more than 50 countries. This is a solution for IP banning problems.

21. Screen-Scraper

Who is this for: For businesses related to the auto, medical, financial and e-commerce industry.

Why you should use it: Screen Scraper is more convenient and basic compared to other web scraping tools like Octoparse. It has a steep learning curve for people without web scraping experience.

22. Salestools.io

Who is this for: Marketers and sales.

Why you should use it: Salestools.io is a web scraping tool that helps salespeople to gather data from professional network sites like LinkedIn, Angellist, Viadeo.

23. ScrapeHero

Who is this for: Investors, Hedge Funds, Market Analysts

Why you should use it: As an API provider, ScrapeHero enables you to turn websites into data. It provides customized web data services for businesses and enterprises.

24. UniPath

Web Scraping Companies Inc

Who is this for: Bussiness in all sizes.

Why you should use it: UiPath is a robotic process automation software for free web scraping. It allows users to create, deploy and administer automation in business processes. It is a great option for business users since it helps you create rules for data management.

25. Web Content Extractor

Who is this for: Data analysts, Marketers, and researchers who're lack of programming skills.

Why you should use it:Web Content Extractor is an easy-to-use web scraping tool for individuals and enterprises. You can go to their website and try its 14-day free trial.

26. WebHarvy

Who is this for: Data analysts, Marketers, and researchers who lack programming skills.

Why you should use it: WebHarvy is a point-and-click web scraping tool. It’s designed for non-programmers. They provide helpful web scraping tutorials for beginners. However, the extractor doesn’t allow you to schedule your scraping projects.

Web Scraping Companies Near Me

27. Web Scraper.io

Who is this for: Data analysts, Marketers, and researchers who lack programming skills.

Why you should use it: Web Scraper is a chrome browser extension built for scraping data from websites. It’s a free web scraping tool for scraping dynamic web pages.

28. Web Sundew

Who is this for: Enterprises, marketers, and researchers.

Why you should use it: WebSundew is a visual scraping tool that works for structured web data scraping. The Enterprise edition allows you to run the scraping projects at a remote server and publish collected data through FTP.

29. Winautomation

Who is this for: Developers, business operation leaders, IT professionals

Why you should use it: Winautomation is a Windows web scraping tool that enables you to automate desktop and web-based tasks.

30. Web Robots

Who is this for: Data analysts, Marketers, and researchers who lack programming skills.

Why you should use it: Web Robots is a cloud-based web scraping platform for scraping dynamic Javascript-heavy websites. It has a web browser extension as well as desktop software, making it easy to scrape data from the websites.

Closing Thoughts

To extract data from websites with web scraping tools is a time-saving method, especially for those who don't have sufficient coding knowledge. There are many factors you should consider when choosing a proper tool to facilitate your web scraping, such as ease of use, API integration, cloud-based extraction, large-scale scraping, scheduling projects, etc. Web scraping software like Octoparse not only provides all the features I just mentioned but also provides data service for teams in all sizes - from start-ups to large enterprises. You can contact usfor more information on web scraping.

Ashley is a data enthusiast and passionate blogger with hands-on experience in web scraping. She focuses on capturing web data and analyzing in a way that empowers companies and businesses with actionable insights. Read her blog here to discover practical tips and applications on web data extraction

日本語記事:スクレイピングツール30選|初心者でもWebデータを抽出できる
Webスクレイピングについての記事は 公式サイトでも読むことができます。
Artículo en español: Los 30 Mejores Software Gratuitos de Web Scraping en 2021
También puede leer artículos de web scraping en el Website Oficial

Data scraping is a technique in which a computer program extracts data from human-readable output coming from another program.

Description[edit]

What is web scraping

Normally, data transfer between programs is accomplished using data structures suited for automated processing by computers, not people. Such interchange formats and protocols are typically rigidly structured, well-documented, easily parsed, and minimize ambiguity. Very often, these transmissions are not human-readable at all.

Thus, the key element that distinguishes data scraping from regular parsing is that the output being scraped is intended for display to an end-user, rather than as an input to another program. It is therefore usually neither documented nor structured for convenient parsing. Data scraping often involves ignoring binary data (usually images or multimedia data), display formatting, redundant labels, superfluous commentary, and other information which is either irrelevant or hinders automated processing.

Data scraping is most often done either to interface to a legacy system, which has no other mechanism which is compatible with current hardware, or to interface to a third-party system which does not provide a more convenient API. In the second case, the operator of the third-party system will often see screen scraping as unwanted, due to reasons such as increased system load, the loss of advertisementrevenue, or the loss of control of the information content.

Data scraping is generally considered an ad hoc, inelegant technique, often used only as a 'last resort' when no other mechanism for data interchange is available. Aside from the higher programming and processing overhead, output displays intended for human consumption often change structure frequently. Humans can cope with this easily, but a computer program will fail. Depending on the quality and the extent of error handling logic present in the computer, this failure can result in error messages, corrupted output or even program crashes.

Technical variants[edit]

Screen scraping[edit]

A screen fragment and a screen-scraping interface (blue box with red arrow) to customize data capture process.
Web Scraping Companies

Although the use of physical 'dumb terminal' IBM 3270s is slowly diminishing, as more and more mainframe applications acquire Web interfaces, some Web applications merely continue to use the technique of screen scraping to capture old screens and transfer the data to modern front-ends.[1]

Screen scraping is normally associated with the programmatic collection of visual data from a source, instead of parsing data as in Web scraping. Originally, screen scraping referred to the practice of reading text data from a computer display terminal's screen. This was generally done by reading the terminal's memory through its auxiliary port, or by connecting the terminal output port of one computer system to an input port on another. The term screen scraping is also commonly used to refer to the bidirectional exchange of data. This could be the simple cases where the controlling program navigates through the user interface, or more complex scenarios where the controlling program is entering data into an interface meant to be used by a human.

As a concrete example of a classic screen scraper, consider a hypothetical legacy system dating from the 1960s—the dawn of computerized data processing. Computer to user interfaces from that era were often simply text-based dumb terminals which were not much more than virtual teleprinters (such systems are still in use today, for various reasons). The desire to interface such a system to more modern systems is common. A robust solution will often require things no longer available, such as source code, system documentation, APIs, or programmers with experience in a 50-year-old computer system. In such cases, the only feasible solution may be to write a screen scraper that 'pretends' to be a user at a terminal. The screen scraper might connect to the legacy system via Telnet, emulate the keystrokes needed to navigate the old user interface, process the resulting display output, extract the desired data, and pass it on to the modern system. A sophisticated and resilient implementation of this kind, built on a platform providing the governance and control required by a major enterprise—e.g. change control, security, user management, data protection, operational audit, load balancing, and queue management, etc.—could be said to be an example of robotic process automation software, called RPA or RPAAI for self-guided RPA 2.0 based on artificial intelligence.

In the 1980s, financial data providers such as Reuters, Telerate, and Quotron displayed data in 24×80 format intended for a human reader. Users of this data, particularly investment banks, wrote applications to capture and convert this character data as numeric data for inclusion into calculations for trading decisions without re-keying the data. The common term for this practice, especially in the United Kingdom, was page shredding, since the results could be imagined to have passed through a paper shredder. Internally Reuters used the term 'logicized' for this conversion process, running a sophisticated computer system on VAX/VMS called the Logicizer.[2]

More modern screen scraping techniques include capturing the bitmap data from the screen and running it through an OCR engine, or for some specialised automated testing systems, matching the screen's bitmap data against expected results.[3] This can be combined in the case of GUI applications, with querying the graphical controls by programmatically obtaining references to their underlying programming objects. A sequence of screens is automatically captured and converted into a database.

Another modern adaptation to these techniques is to use, instead of a sequence of screens as input, a set of images or PDF files, so there are some overlaps with generic 'document scraping' and report mining techniques.

There are many tools that can be used for screen scraping.[4]

Web scraping[edit]

Web pages are built using text-based mark-up languages (HTML and XHTML), and frequently contain a wealth of useful data in text form. However, most web pages are designed for human end-users and not for ease of automated use. Because of this, tool kits that scrape web content were created. A web scraper is an API or tool to extract data from a web site. Companies like Amazon AWS and Google provide web scraping tools, services, and public data available free of cost to end-users.Newer forms of web scraping involve listening to data feeds from web servers. For example, JSON is commonly used as a transport storage mechanism between the client and the webserver.

Recently, companies have developed web scraping systems that rely on using techniques in DOM parsing, computer vision and natural language processing to simulate the human processing that occurs when viewing a webpage to automatically extract useful information.[5][6]

Large websites usually use defensive algorithms to protect their data from web scrapers and to limit the number of requests an IP or IP network may send. This has caused an ongoing battle between website developers and scraping developers.[7]

Report mining[edit]

Report mining is the extraction of data from human-readable computer reports. Conventional data extraction requires a connection to a working source system, suitable connectivity standards or an API, and usually complex querying. By using the source system's standard reporting options, and directing the output to a spool file instead of to a printer, static reports can be generated suitable for offline analysis via report mining.[8] This approach can avoid intensive CPU usage during business hours, can minimise end-user licence costs for ERP customers, and can offer very rapid prototyping and development of custom reports. Whereas data scraping and web scraping involve interacting with dynamic output, report mining involves extracting data from files in a human-readable format, such as HTML, PDF, or text. These can be easily generated from almost any system by intercepting the data feed to a printer. This approach can provide a quick and simple route to obtaining data without the need to program an API to the source system.

See also[edit]

References[edit]

  1. ^'Back in the 1990s.. 2002 ... 2016 ... still, according to Chase Bank, a major issue. Ron Lieber (May 7, 2016). 'Jamie Dimon Wants to Protect You From Innovative Start-Ups'. The New York Times.
  2. ^Contributors Fret About Reuters' Plan To Switch From Monitor Network To IDN, FX Week, 02 Nov 1990
  3. ^Yeh, Tom (2009). 'Sikuli: Using GUI Screenshots for Search and Automation'(PDF). UIST.
  4. ^'What is Screen Scraping'. June 17, 2019.
  5. ^'Diffbot aims to make it easier for apps to read Web pages the way humans do'. MIT Technology Review. Retrieved 1 December 2014.
  6. ^'This Simplemw-data:TemplateStyles:r999302996'>''Unusual traffic from your computer network' - Search Help'. support.google.com. Retrieved 2017-04-04.
  7. ^Scott Steinacher, 'Data Pump transforms host data', InfoWorld, 30 August 1999, p55

Further reading[edit]

  • Hemenway, Kevin and Calishain, Tara. Spidering Hacks. Cambridge, Massachusetts: O'Reilly, 2003. ISBN0-596-00577-6.
Retrieved from 'https://en.wikipedia.org/w/index.php?title=Data_scraping&oldid=1019697296'