Data Instant Scraper

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Instant Data Scraping Extension – Web Robots

Instant Data Scraping Extensionnicerobot2020-12-18T08:31:47+02:00We created a browser extension which uses AI to detect tabular or listing type data on web pages. Such data can be scraped into CSV or Excel file, no coding skills required. Our extension can also click on the “Next” page links or buttons and retrieve data from multiple pages into one file. The extension runs completely in user’s browser and does not send data to Web Robots. When testing it we benchmarked that this tool would work with the Amazon, Ebay, Bestbuy, Craigslist, Walmart, Etsy, Home Depot, Yellow Pages, etc. – it works on all of Instant Data from Chrome Webstore! Get Instant Data from Microsoft Edge Webstore! How to use it:
Open the first page of listing results (products, directory, etc) in your browser
Activate the extension
Extension will guess where your data is. If not happy use “Try another table” button to guess again.
Download CSV or Excel from the first page if that is all you need. Or click to locate “Next” button to mark the “Next” link/button on a website.
Click “Start crawling” to start crawling through multiple pages a website. Extension will show statistics on what is being collected.
Download Excel or CSV file at any time during the crawl.
Clean up Excel or CSV files – it will most likely have some unwanted additional fields that were extracted from the page. Most likely column names will have to be renamed as another table – AI guesses an alternative table if the initial guess was not what you “Next” button – press this and mark the location of “Next” button or linked on a website. This will be used to scrape data from multiple pages into one delay – time in seconds before going to the next page. Default value is 1 second. it can be increased when pages load information and XLSX – file download buttons. They are active right away when any data is finite Scroll – extension can scroll down on pages where more data is loaded dynamically. It automatically detects when loading new data stops.
What Is Data Scraping And How Can You Use It? | Target Internet

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What Is Data Scraping And How Can You Use It? | Target Internet

What Is Data Scraping? Data scraping, also known as web scraping, is the process of importing information from a website into a spreadsheet or local file saved on your computer. It’s one of the most efficient ways to get data from the web, and in some cases to channel that data to another website. Popular uses of data scraping include:Research for web content/business intelligencePricing for travel booker sites/price comparison sitesFinding sales leads/conducting market research by crawling public data sources (e. g. Yell and Twitter)Sending product data from an e-commerce site to another online vendor (e. Google Shopping)And that list’s just scratching the surface. Data scraping has a vast number of applications – it’s useful in just about any case where data needs to be moved from one place to basics of data scraping are relatively easy to master. Let’s go through how to set up a simple data scraping action using Scraping with dynamic web queries in Microsoft ExcelSetting up a dynamic web query in Microsoft Excel is an easy, versatile data scraping method that enables you to set up a data feed from an external website (or multiple websites) into a this excellent tutorial video to learn how to import data from the web to Excel – or, if you prefer, use the written instructions below:Open a new workbook in ExcelClick the cell you want to import data intoClick the ‘Data’ tabClick ‘Get external data’Click the ‘From web’ symbolNote the little yellow arrows that appear to the top-left of web page and alongside certain contentPaste the URL of the web page you want to import data from into the address bar (we recommend choosing a site where data is shown in tables)Click ‘Go’Click the yellow arrow next to the data you wish to importClick ‘Import’An ‘Import data’ dialogue box pops upClick ‘OK’ (or change the cell selection, if you like)If you’ve followed these steps, you should now be able to see the data from the website set out in your great thing about dynamic web queries is that they don’t just import data into your spreadsheet as a one-off operation – they feed it in, meaning the spreadsheet is regularly updated with the latest version of the data, as it appears on the source website. That’s why we call them configure how regularly your dynamic web query updates the data it imports, go to ‘Data’, then ‘Properties’, then select a frequency (“Refresh every X minutes”). Automated data scraping with toolsGetting to grips with using dynamic web queries in Excel is a useful way to gain an understanding of data scraping. However, if you intend to use data regularly scraping in your work, you may find a dedicated data scraping tool more are our thoughts on a few of the most popular data scraping tools on the market:Data Scraper (Chrome plugin)Data Scraper slots straight into your Chrome browser extensions, allowing you to choose from a range of ready-made data scraping “recipes” to extract data from whichever web page is loaded in your tool works especially well with popular data scraping sources like Twitter and Wikipedia, as the plugin includes a greater variety of recipe options for such tried Data Scraper out by mining a Twitter hashtag, “#jourorequest”, for PR opportunities, using one of the tool’s public recipes. Here’s a flavour of the data we got back:As you can see, the tool has provided a table with the username of every account which had posted recently on the hashtag, plus their tweet and its URLHaving this data in this format would be more useful to a PR rep than simply seeing the data in Twitter’s browser view for a number of reasons: It could be used to help create a database of press contactsYou could keep referring back to this list and easily find what you’re looking for, whereas Twitter continuously updatesThe list is sortable and editableIt gives you ownership of the data – which could be taken offline or changed at any momentWe’re impressed with Data Scraper, even though its public recipes are sometimes slightly rough-around-the-edges. Try installing the free version on Chrome, and have a play around with extracting data. Be sure to watch the intro movie they provide to get an idea of how the tool works and some simple ways to extract the data you want. WebHarvyWebHarvy is a point-and-click data scraper with a free trial version. Its biggest selling point is its flexibility – you can use the tool’s in-built web browser to navigate to the data you would like to import, and can then create your own mining specifications to extract exactly what you need from the source is a feature-rich data mining tool suite that does much of the hard work for you. Has some interesting features, including “What’s changed? ” reports that can notify you of updates to specified websites – ideal for in-depth competitor are marketers using data scraping? As you will have gathered by this point, data scraping can come in handy just about anywhere where information is used. Here are some key examples of how the technology is being used by marketers:Gathering disparate dataOne of the great advantages of data scraping, says Marcin Rosinski, CEO of FeedOptimise, is that it can help you gather different data into one place. “Crawling allows us to take unstructured, scattered data from multiple sources and collect it in one place and make it structured, ” says Marcin. “If you have multiple websites controlled by different entities, you can combine it all into one feed. “The spectrum of use cases for this is infinite. ”FeedOptimise offers a wide variety of data scraping and data feed services, which you can find out about at their website. Expediting researchThe simplest use for data scraping is retrieving data from a single source. If there’s a web page that contains lots of data that could be useful to you, the easiest way to get that information onto your computer in an orderly format will probably be data finding a list of useful contacts on Twitter, and import the data using data scraping. This will give you a taste of how the process can fit into your everyday work. Outputting an XML feed to third party sitesFeeding product data from your site to Google Shopping and other third party sellers is a key application of data scraping for e-commerce. It allows you to automate the potentially laborious process of updating your product details – which is crucial if your stock changes often. “Data scraping can output your XML feed for Google Shopping, ” says Target Internet’s Marketing Director, Ciaran Rogers. “ I have worked with a number of online retailers retailer who were continually adding new SKU’s to their site as products came into stock. If your E-commerce solution doesn’t output a suitable XML feed that you can hook up to your Google Merchant Centre so you can advertise your best products that can be an issue. Often your latest products are potentially the best sellers, so you want to get them advertised as soon as they go live. I’ve used data scraping to produce up-to-date listings to feed into Google Merchant Centre. It’s a great solution, and actually, there is so much you can do with the data once you have it. Using the feed, you can tag the best converting products on a daily basis so you can share that information with Google Adwords and ensure you bid more competitively on those products. Once you set it up its all quite automated. The flexibility a good feed you have control of in this way is great, and it can lead to some very definite improvements in those campaigns which clients love. ”It’s possible to set up a simple data feed into Google Merchant Centre for yourself. Here’s how it’s done:How to set up a data feed to Google Merchant CentreUsing one of the techniques or tools described previously, create a file that uses a dynamic website query to import the details of products listed on your site. This file should automatically update at regular details should be set out as specified this file to a password-protected URLGo to Google Merchant Centre and log in (make sure your Merchant Centre account is properly set up first)Go to ProductsClick the plus buttonEnter your target country and create a feed nameSelect the ‘scheduled fetch’ optionAdd the URL of your product data file, along with the username and password required to access itSelect the fetch frequency that best matches your product upload scheduleClick SaveYour product data should now be available in Google Merchant Centre. Just make sure you Click on the ‘Diagnostics’ tab to check it’s status and ensure it’s all working dark side of data scrapingThere are many positive uses for data scraping, but it does get abused by a small minority most prevalent misuse of data scraping is email harvesting – the scraping of data from websites, social media and directories to uncover people’s email addresses, which are then sold on to spammers or scammers. In some jurisdictions, using automated means like data scraping to harvest email addresses with commercial intent is illegal, and it is almost universally considered bad marketing web users have adopted techniques to help reduce the risk of email harvesters getting hold of their email address, including:Address munging: changing the format of your email address when posting it publicly, e. typing ‘patrick[at]’ instead of ‘’. This is an easy but slightly unreliable approach to protecting your email address on social media – some harvesters will search for various munged combinations as well as emails in a normal format, so it’s not entirely ntact forms: using a contact form instead of posting your email address(es) on your if your email address is presented in image form on your website, it will be beyond the technological reach of most people involved in email Data Scraping FutureWhether or not you intend to use data scraping in your work, it’s advisable to educate yourself on the subject, as it is likely to become even more important in the next few are now data scraping AI on the market that can use machine learning to keep on getting better at recognising inputs which only humans have traditionally been able to interpret – like improvements in data scraping from images and videos will have far-reaching consequences for digital marketers. As image scraping becomes more in-depth, we’ll be able to know far more about online images before we’ve seen them ourselves – and this, like text-based data scraping, will help us do lots of things there’s the biggest data scraper of all – Google. The whole experience of web search is going to be transformed when Google can accurately infer as much from an image as it can from a page of copy – and that goes double from a digital marketing you’re in any doubt over whether this can happen in the near future, try out Google’s image interpretation API, Cloud Vision, and let us know what you think. get your free membership now – absolutely no credit card requiredThe Digital Marketing ToolkitExclusive live video learning sessionsComplete library of The Digital Marketing PodcastThe digital skills benchmarking toolsFree online training courses FREE MEMBERSHIP
Is Web Scraping Illegal? Depends on What the Meaning of the Word Is

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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Frequently Asked Questions about data instant scraper

Instant Data Scraper is an automated data extraction tool for any website. It uses AI to predict which data is most relevant on a HTML page and allows saving it to Excel or CSV file (XLS, XLSX, CSV).Jan 28, 2021

How to use it:Open the first page of listing results (products, directory, etc) in your browser.Activate the extension.Extension will guess where your data is. … Download CSV or Excel from the first page if that is all you need. … Click “Start crawling” to start crawling through multiple pages a website.More items…•Dec 18, 2020

Data scraping, also known as web scraping, is the process of importing information from a website into a spreadsheet or local file saved on your computer. … It’s one of the most efficient ways to get data from the web, and in some cases to channel that data to another website.

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