How To Use Web Scraperprxcompass
How to Use Web Scraper Chrome Extension to Extract Data
This post is about DIY web scraping tools. If you are looking for a fully customizable web scraping solution, you can add your project on CrawlBoard.
How to Use Web Scraper Chrome Extension to Extract Data
Web scraping is becoming a vital ingredient in business and marketing planning regardless of the industry. There are several ways to crawl the web for useful data depending on your requirements and budget. Did you know that your favourite web browser could also act as a great web scraping tool?
You can install the Web Scraper extension from the chrome web store to make it an easy-to-use data scraping tool. The best part is, you can stay in the comfort zone of your browser while the scraping happens. This doesn’t demand much technical skills, which makes it a good option when you need to do some quick data scraping. Let’s get started with the tutorial on how to use web scraper chrome extension to extract data.
About the Web Scraper Chrome Extension
What You Need
Google Chrome browser
A working internet connection
A. Installation and setup
webscraper chrome extension by using link
For web scraper chrome extension download click on “Add”
Once this is done, you are ready to start scraping any website using your chrome browser. You just need to learn how to perform the scraping, which we are about to explain.
B. The Method
After installation, open the Google Chrome developer tools by pressing F12. (You can alternatively right-click on the screen and select inspect element). In the developer tools, you will find a new tab named ‘Web scraper’ as shown in the screenshot below.
Now let’s see how to use this on a live web page. We will use a site called for this tutorial. This site contains gif images and we will crawl these image URLs using our web scraper.
Step 1: Creating a Sitemap
Go to Open developer tools by right-clicking anywhere on the screen and then selecting inspect
Click on the web scraper tab in developer tools
Click on ‘create new sitemap’ and then select ‘create sitemap’
Give the sitemap a name and enter the URL of the site in the start URL field.
Click on ‘Create Sitemap’
To crawl multiple pages from a website, we need to understand the pagination structure of that site. You can easily do that by clicking the ‘Next’ button a few times from the homepage. Doing this on revealed that the pages are structured as, and so on. To switch to a different page, you only have to change the number at the end of this URL. Now, we need the scraper to do this automatically.
To do this, create a new sitemap with the start URL as 001-125]. The scraper will now open the URL repeatedly while incrementing the final value each time. This means the scraper will open pages starting from 1 to 125 and crawl the elements that we require from each page.
Step 2: Scraping Elements
Every time the scraper opens a page from the site, we need to extract some elements. In this case, it’s the gif image URLs. First, you have to find the CSS selector matching the images. You can find the CSS selector by looking at the source file of the web page (CTRL+U). An easier way is to use the selector tool to click and select any element on the screen. Click on the Sitemap that you just created, click on ‘Add new selector’. In the selector id field, give the selector a name. In the type field, you can select the type of data that you want to be extracted. Click on the select button and select any element on the web page that you want to be extracted. When you are done selecting, click on ‘Done selecting’. It’s easy as clicking on an icon with the mouse. You can check the ‘multiple’ checkbox to indicate that the element you want can be present multiple times on the page and that you want each instance of it to be scrapped.
Now you can save the selector if everything looks good. To start the scraping process, just click on the sitemap tab and select ‘Scrape’. A new window will pop up which will visit each page in the loop and crawl the required data. If you want to stop the data scraping process in between, just close this window and you will have the data that was extracted till then.
Once you stop scraping, go to the sitemap tab to browse the extracted data or export it to a CSV file. The only downside of such data extraction software is that you have to manually perform the scraping every time since it doesn’t have many automation features built-in.
If you want to crawl data on a large scale, it is better to go with a data scraping service instead of such free web scraper chrome extension data extraction tools like these. With the second part of this series, we will show you how to make a MySQL database using the extracted data. Stay tuned for that!
Is Web Scraping Illegal? Depends on What the Meaning of the Word Is
Depending on who you ask, web scraping can be loved or hated.
Web scraping has existed for a long time and, in its good form, it’s a key underpinning of the internet. “Good bots” enable, for example, search engines to index web content, price comparison services to save consumers money, and market researchers to gauge sentiment on social media.
“Bad bots, ” however, fetch content from a website with the intent of using it for purposes outside the site owner’s control. Bad bots make up 20 percent of all web traffic and are used to conduct a variety of harmful activities, such as denial of service attacks, competitive data mining, online fraud, account hijacking, data theft, stealing of intellectual property, unauthorized vulnerability scans, spam and digital ad fraud.
So, is it Illegal to Scrape a Website?
So is it legal or illegal? Web scraping and crawling aren’t illegal by themselves. After all, you could scrape or crawl your own website, without a hitch.
Startups love it because it’s a cheap and powerful way to gather data without the need for partnerships. Big companies use web scrapers for their own gain but also don’t want others to use bots against them.
The general opinion on the matter does not seem to matter anymore because in the past 12 months it has become very clear that the federal court system is cracking down more than ever.
Let’s take a look back. Web scraping started in a legal grey area where the use of bots to scrape a website was simply a nuisance. Not much could be done about the practice until in 2000 eBay filed a preliminary injunction against Bidder’s Edge. In the injunction eBay claimed that the use of bots on the site, against the will of the company violated Trespass to Chattels law.
The court granted the injunction because users had to opt in and agree to the terms of service on the site and that a large number of bots could be disruptive to eBay’s computer systems. The lawsuit was settled out of court so it all never came to a head but the legal precedent was set.
In 2001 however, a travel agency sued a competitor who had “scraped” its prices from its Web site to help the rival set its own prices. The judge ruled that the fact that this scraping was not welcomed by the site’s owner was not sufficient to make it “unauthorized access” for the purpose of federal hacking laws.
Two years later the legal standing for eBay v Bidder’s Edge was implicitly overruled in the “Intel v. Hamidi”, a case interpreting California’s common law trespass to chattels. It was the wild west once again. Over the next several years the courts ruled time and time again that simply putting “do not scrape us” in your website terms of service was not enough to warrant a legally binding agreement. For you to enforce that term, a user must explicitly agree or consent to the terms. This left the field wide open for scrapers to do as they wish.
Fast forward a few years and you start seeing a shift in opinion. In 2009 Facebook won one of the first copyright suits against a web scraper. This laid the groundwork for numerous lawsuits that tie any web scraping with a direct copyright violation and very clear monetary damages. The most recent case being AP v Meltwater where the courts stripped what is referred to as fair use on the internet.
Previously, for academic, personal, or information aggregation people could rely on fair use and use web scrapers. The court now gutted the fair use clause that companies had used to defend web scraping. The court determined that even small percentages, sometimes as little as 4. 5% of the content, are significant enough to not fall under fair use. The only caveat the court made was based on the simple fact that this data was available for purchase. Had it not been, it is unclear how they would have ruled. Then a few months back the gauntlet was dropped.
Andrew Auernheimer was convicted of hacking based on the act of web scraping. Although the data was unprotected and publically available via AT&T’s website, the fact that he wrote web scrapers to harvest that data in mass amounted to “brute force attack”. He did not have to consent to terms of service to deploy his bots and conduct the web scraping. The data was not available for purchase. It wasn’t behind a login. He did not even financially gain from the aggregation of the data. Most importantly, it was buggy programing by AT&T that exposed this information in the first place. Yet Andrew was at fault. This isn’t just a civil suit anymore. This charge is a felony violation that is on par with hacking or denial of service attacks and carries up to a 15-year sentence for each charge.
In 2016, Congress passed its first legislation specifically to target bad bots — the Better Online Ticket Sales (BOTS) Act, which bans the use of software that circumvents security measures on ticket seller websites. Automated ticket scalping bots use several techniques to do their dirty work including web scraping that incorporates advanced business logic to identify scalping opportunities, input purchase details into shopping carts, and even resell inventory on secondary markets.
To counteract this type of activity, the BOTS Act:
Prohibits the circumvention of a security measure used to enforce ticket purchasing limits for an event with an attendance capacity of greater than 200 persons.
Prohibits the sale of an event ticket obtained through such a circumvention violation if the seller participated in, had the ability to control, or should have known about it.
Treats violations as unfair or deceptive acts under the Federal Trade Commission Act. The bill provides authority to the FTC and states to enforce against such violations.
In other words, if you’re a venue, organization or ticketing software platform, it is still on you to defend against this fraudulent activity during your major onsales.
The UK seems to have followed the US with its Digital Economy Act 2017 which achieved Royal Assent in April. The Act seeks to protect consumers in a number of ways in an increasingly digital society, including by “cracking down on ticket touts by making it a criminal offence for those that misuse bot technology to sweep up tickets and sell them at inflated prices in the secondary market. ”
In the summer of 2017, LinkedIn sued hiQ Labs, a San Francisco-based startup. hiQ was scraping publicly available LinkedIn profiles to offer clients, according to its website, “a crystal ball that helps you determine skills gaps or turnover risks months ahead of time. ”
You might find it unsettling to think that your public LinkedIn profile could be used against you by your employer.
Yet a judge on Aug. 14, 2017 decided this is okay. Judge Edward Chen of the U. S. District Court in San Francisco agreed with hiQ’s claim in a lawsuit that Microsoft-owned LinkedIn violated antitrust laws when it blocked the startup from accessing such data. He ordered LinkedIn to remove the barriers within 24 hours. LinkedIn has filed to appeal.
The ruling contradicts previous decisions clamping down on web scraping. And it opens a Pandora’s box of questions about social media user privacy and the right of businesses to protect themselves from data hijacking.
There’s also the matter of fairness. LinkedIn spent years creating something of real value. Why should it have to hand it over to the likes of hiQ — paying for the servers and bandwidth to host all that bot traffic on top of their own human users, just so hiQ can ride LinkedIn’s coattails?
I am in the business of blocking bots. Chen’s ruling has sent a chill through those of us in the cybersecurity industry devoted to fighting web-scraping bots.
I think there is a legitimate need for some companies to be able to prevent unwanted web scrapers from accessing their site.
In October of 2017, and as reported by Bloomberg, Ticketmaster sued Prestige Entertainment, claiming it used computer programs to illegally buy as many as 40 percent of the available seats for performances of “Hamilton” in New York and the majority of the tickets Ticketmaster had available for the Mayweather v. Pacquiao fight in Las Vegas two years ago.
Prestige continued to use the illegal bots even after it paid a $3. 35 million to settle New York Attorney General Eric Schneiderman’s probe into the ticket resale industry.
Under that deal, Prestige promised to abstain from using bots, Ticketmaster said in the complaint. Ticketmaster asked for unspecified compensatory and punitive damages and a court order to stop Prestige from using bots.
Are the existing laws too antiquated to deal with the problem? Should new legislation be introduced to provide more clarity? Most sites don’t have any web scraping protections in place. Do the companies have some burden to prevent web scraping?
As the courts try to further decide the legality of scraping, companies are still having their data stolen and the business logic of their websites abused. Instead of looking to the law to eventually solve this technology problem, it’s time to start solving it with anti-bot and anti-scraping technology today.
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What is Web Scraping and How Does It Work | Octoparse
What is web scraping?
Web scraping, also known as web harvesting and web data extraction, basically refers to collecting data from websites via the Hypertext Transfer Protocol (HTTP) or through web browsers.
Table of Content
How does web scraping work?
How did web scraping all start?
How will web scraping be?
How is Web scraping done?
Generally, web scraping involves three steps:
first, we send a GET request to the server and we will receive a response in a form of web content.
Next, we parse the HTML code of a web site following a tree structure path.
Finally, we use the python library to search for the parse tree.
I know what you think — web scraping looks good on paper but actually more complex in practice. We need coding to get the data we want, which makes it the privilege of who’s master of programming. As an alternative, there are web scraping tools automating web data extraction at fingertips.
A web scraping tool will load the URLs given by the users and render the entire website. As a result, you can extract any web data with simple point-and-click and file in a feasible format into your computer without coding.
For example, you might want to extract posts and comments from Twitter. All you have to do is to paste the URL to the scraper, select desired posts and comments and execute. Therefore, it saves time and efforts from the mundane work of copy-and-paste.
Though to many people, it sounds like a brand-new concept, the history of the web scraping can be dated back to the time when the World Wide Web was born.
At the very beginning, the Internet was even unsearchable. Before search engines were developed, the Internet was just a collection of File Transfer Protocol (FTP) sites in which users would navigate to find specific shared files. To find and organize distributed data available on the Internet, people created a specific automated program, known as the web crawler/bot today, to fetch all pages on the Internet and then copy all content into databases for indexing.
Then the Internet grows, eventually becoming the home to millions of web pages that contain a wealth of data in multiple forms, including texts, images, videos, and audios. It turns into an open data source.
As the data source became incredibly rich and easily searchable, people started to find it simple to seek the information they want, which often spread across a large number of websites, but the problem occurred when they wanted to get data from the Internet—not every website offered download options, and copying by hand was obviously tedious and inefficient.
And that’s where web scraping came in. Web scraping is actually powered by web bots/crawlers that function the same way those used in search engines. That is, fetch and copy. The only difference could be the scale. Web scraping focuses on extracting only specific data from certain websites whereas search engines often fetch most of the websites around the Internet.
1989 The birth of the World Wide Web
Technically, the World Wide Web is different from the Internet. The former refers to the information space, while the latter is the network made up of computers.
Thanks to Tim Berners-Lee, the inventor of WWW, he brought the following 3 things that have long been part of our daily life:
Uniform Resource Locators (URLs) which we use to go to the website we want;
embedded hyperlinks that permit us to navigate between the web pages, like the product detail pages on which/where we can find product specifications and lots of other things like “customers who bought this also bought”;
web pages that contain not only texts but also images, audios, videos and software components.
1990 The first web browser
Also invented by Tim Berners-Lee, it was called WorldWideWeb (no spaces), named after the WWW project. One year after the appearance of the web, people had a way to see it and interact with it.
1991 The first web server and the first web page
The web kept growing at rather mild speed. By 1994, the number of HTTP servers was over 200.
1993-June First web robot – World Wide Web Wanderer
Though functioned the same way web robots today do, it was intended only to measure the size of the web.
1993-December First crawler-based web search engine – JumpStation
As there were not so many websites available on the web, search engines at that time used to rely on their human website administrators to collect and edit the links into a particular format. JumpStation brought a new leap. It is the first WWW search engine that relies on a web robot.
Since then, people started to use these programmatic web crawlers to harvest and organize the Internet. From Infoseek, Altavista, and Excite, to Bing and Google today, the core of a search engine bot remains the same: find a web page, download (fetch) it, scrape all the information presented on the web page, and then add it to the search engine’s database.
As web pages are designed for human users, and not for ease of automated use, even with the development of the web bot, it was still hard for computer engineers and scientists to do web scraping, let alone normal people. So people have been dedicated to making web scraping more available. In 2000, Salesforce and eBay launched their own API, with which programmers were enabled to access and download some of the data available to the public. Since then, many websites offer web APIs for people to access their public database. APIs offer developers a more friendly way to do web scraping, by just gathering data provided by websites.
2004 Python Beautiful soup
Not all websites offer APIs. Even if they do, they don’t provide all the data you want. So programmers were still working on developing an approach that could facilitate web scraping. In 2004, Beautiful Soup was released. It is a library designed for Python.
In computer programming, a library is a collection of script modules, like commonly used algorithms, that allow being used without rewriting, simplifying the programming process. with simple commands, Beautiful Soup makes sense of site structure and helps parse content from within the HTML container. It is considered the most sophisticated and advanced library for web scraping, and also one of the most common and popular approaches today.
2005-2006 Visual web scraping software
In 2006, Stefan Andresen and his Kapow Software (acquired by Kofax in 2013) launched Web Integration Platform version 6. 0, something now understood as visual web scraping software, which allows users to simply highlight the content of a web page and structure that data into a usable excel file, or database.
Finally, there’s a way for the massive non-programmers to do web scraping on their own. Since then, web scraping is starting to hit the mainstream. Now for non-programmers, they can easily find more than 80 out-of-box data extraction software that provides visual processes.
We collect data, process data, and turn data into actionable insights. It’s proven that business giants like Microsoft and Amazon invest a lot of money on data collection about their consumers so as to target people with personalized ads. whereas, small businesses are muscled out of the marketing competition as they’re lack of spare capital to collect data.
Thanks to web scraping tools, any individual, company, and organization are now able to access web data for analysis. When searching “web scraping” on, you can get 10, 088 search results, which means more than 10, 000 freelancers are offering web scraping services on the website.
The rising demands in web data by companies across industry prosper the web scraping marketplace, and that brings new jobs and business opportunities.
Meanwhile, like any other emerging industry, web scraping brings legal concerns as well. The legal landscape surrounding the legitimacy of web scraping continues to evolve. Its legal status remains highly context-specific. For now, many of the most interesting legal questions emerging from this trend remain unanswered.
One way to get around potential legal consequences of web scraping is to consult professional web scraping service providers. Octoparse stands as the best web scraping company that offers both scraping services and web data extraction tool. Both individual entrepreneurs or big companies will reap the benefits at their advanced scraping technology.
Artículo en español: Web Scraping: Cómo Comenzó y Qué Sucederá en El FuturoTambién puede leer artículos de web scraping en el Website Oficial
Frequently Asked Questions about how to use web scraper
Step 1: Creating a SitemapOpen developer tools by right-clicking anywhere on the screen and then selecting inspect.Click on the web scraper tab in developer tools.Click on ‘create new sitemap’ and then select ‘create sitemap’Give the sitemap a name and enter the URL of the site in the start URL field.More items…
So is it legal or illegal? Web scraping and crawling aren’t illegal by themselves. After all, you could scrape or crawl your own website, without a hitch. … Big companies use web scrapers for their own gain but also don’t want others to use bots against them.
Walkthrough: Scraping a website with the Scraper extensionOpen Google Chrome and click on Chrome Web Store.Search for “Scraper” in extensions.The first search result is the “Scraper” extension.Click the add to chrome button.Now let’s go back to the listing of UK MPs.More items…•Sep 2, 2013