History and Techniques of Web Scraping
– Web scraping dates back to the birth of the World Wide Web in 1989.
– The first web robot, World Wide Web Wanderer, was created in June 1993.
– In December 1993, the first crawler-based web search engine, JumpStation, was launched.
– In 2000, the first Web API and API crawler were created.
– Salesforce and eBay launched their own API in 2000, allowing access to public data.
– Web scraping is the process of automatically mining data from the World Wide Web.
– It shares a common goal with the semantic web vision.
– Breakthroughs in text processing, semantic understanding, AI, and human-computer interactions are needed.
– Techniques include human copy-and-paste, text pattern matching, HTTP programming, HTML parsing, and DOM parsing.
– Some websites set up barriers to prevent machine automation, requiring manual examination and copy-and-paste.
– Manual copying and pasting data from a web page is the simplest form of web scraping.
– Sometimes, even the best web-scraping technology cannot replace human intervention.
– Barriers set up by websites may require manual examination and copy-and-paste.
– Machine automation may be prevented in these cases.
– Human copy-and-paste may be the only workable solution.
– UNIX grep command or regular expression-matching facilities can extract information from web pages.
– Programming languages like Perl or Python can be used for this approach.
– Patterns are matched to extract desired data.
– Text pattern matching is a simple yet powerful approach.
– It can be used to retrieve specific data from web pages.
– Static and dynamic web pages can be retrieved by posting HTTP requests.
– Socket programming is used to send HTTP requests to remote web servers.
– Web pages are retrieved using HTTP programming.
– Both static and dynamic web pages can be accessed.
– HTTP programming allows for the retrieval of web page content.
Software for Web Scraping
– Many software tools available for web scraping.
– Software can automatically recognize the data structure of a page.
– Some software provides a recording interface to avoid manual coding.
– Scripting functions can be used to extract and transform content.
– Database interfaces can store scraped data in local databases.
Legal Issues of Web Scraping (United States)
– Web scraping legality varies worldwide.
– Terms of service may prohibit web scraping on some websites.
– Enforceability of terms is unclear.
– Legal claims in the United States to prevent web scraping: copyright infringement, violation of the Computer Fraud and Abuse Act (CFAA), and trespass to chattel.
– Case law on web scraping is still evolving.
– Website owners can use legal claims to prevent web scraping.
– Copyright law allows duplication of facts.
– Users of scrapers may be held liable for trespass to chattels.
– American Airlines successfully obtained an injunction against FareChase for web scraping.
– Southwest Airlines also challenged screen-scraping practices.
Legal Issues of Web Scraping (European Union)
– Danish court ruled against systematic crawling and deep linking by a portal site.
– Case involved crawling and indexing of a real estate site.
– Ruling highlights legal issues surrounding web scraping in the EU.
– Laws regarding web scraping vary across EU member states.
– European Court of Justice has made some rulings on web scraping.
Case Studies and Legality of Web Scraping
– Craigslist successfully sued 3Taps for violating the Computer Fraud and Abuse Act.
– American Airlines obtained an injunction against FareChase for web scraping.
– Southwest Airlines filed a legal claim against screen-scraping practices.
– QVC objected to Resultly’s excessive crawling of their site.
– Facebook sued Power Ventures for scraping Facebook pages.
– Web scraping does not conflict with Danish law or the database directive of the European Union.
– In the case of Ryanair Ltd v Billigfluege.de GmbH, Ireland’s High Court ruled that Ryanair’s click-wrap agreement was legally binding.
– The French Data Protection Authority (CNIL) released guidelines stating that publicly available data is still personal data and cannot be repurposed without consent.
– The Spam Act 2003 in Australia outlaws some forms of web harvesting, specifically related to email addresses.
– Indian courts have not expressly ruled on the legality of web scraping, but violating terms of use prohibiting data scraping would be a violation of contract law and the Information Technology Act, 2000.
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Web scraping, web harvesting, or web data extraction is data scraping used for extracting data from websites. Web scraping software may directly access the World Wide Web using the Hypertext Transfer Protocol or a web browser. While web scraping can be done manually by a software user, the term typically refers to automated processes implemented using a bot or web crawler. It is a form of copying in which specific data is gathered and copied from the web, typically into a central local database or spreadsheet, for later retrieval or analysis.
Scraping a web page involves fetching it and extracting from it. Fetching is the downloading of a page (which a browser does when a user views a page). Therefore, web crawling is a main component of web scraping, to fetch pages for later processing. Once fetched, extraction can take place. The content of a page may be parsed, searched and reformatted, and its data copied into a spreadsheet or loaded into a database. Web scrapers typically take something out of a page, to make use of it for another purpose somewhere else. An example would be finding and copying names and telephone numbers, companies and their URLs, or e-mail addresses to a list (contact scraping).
As well as contact scraping, web scraping is used as a component of applications used for web indexing, web mining and data mining, online price change monitoring and price comparison, product review scraping (to watch the competition), gathering real estate listings, weather data monitoring, website change detection, research, tracking online presence and reputation, web mashup, and web data integration.
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. As a result, specialized tools and software have been developed to facilitate the scraping of web pages.
Newer forms of web scraping involve monitoring data feeds from web servers. For example, JSON is commonly used as a transport mechanism between the client and the web server.
There are methods that some websites use to prevent web scraping, such as detecting and disallowing bots from crawling (viewing) their pages. In response, there are web scraping systems that rely on using techniques in DOM parsing, computer vision and natural language processing to simulate human browsing to enable gathering web page content for offline parsing