Web Scraping Challenges
9 Web Scraping Challenges You Should Know | Octoparse
Web Scraping Challenges
Bot access
Web page structures
IP blocking
Captcha
Honeypot traps
Slow/unstable load speed
Dynamic content
Login requirement
Real-time data scraping
Web scraping has become a hot topic among people with the rising demand for big data. More and more people hunger for extracting data from multiple websites to help with their business development. However, many challenges, such as blocking mechanisms, will rise when scaling up the web scraping processes, which can hinder people from getting data. Let’s look at the challenges in detail.
Web scraping may not work because:
1. Bot access
The first thing to check is that if your target website allows for scraping before you start it. If you find it disallows for scraping via its, you can ask the web owner for scraping permission, explaining your scraping needs and purposes. If the owner still disagrees, it’s better to find an alternative site that has similar information.
2. Complicated and changeable web page structures
Most web pages are based on HTML (Hypertext Markup Language). Web page designers can have their own standards to design the pages, so web page structures are widely divergent. When you need to scrape multiple websites, you need to build one scraper for each website.
Moreover, websites periodically update their content to improve the user experience or add new features, which often leads to structural changes on the web page. Since web scrapers are set up according to a certain design of the page, they would not work for the updated page. Sometimes even a minor change in the target website requires you to adjust the scraper.
Octoparse uses customized workflow to simulate human behaviors so that to deal with different pages. You can modify the workflow easier to adapt to the new pages.
3. IP blocking
IP blocking is a common method to stop web scrapers from accessing data of a website. It typically happens when a website detects a high number of requests from the same IP address. The website would either totally ban the IP or restrict its access to break down the scraping process.
There are many IP proxy services like Luminati, that can be integrated with automated scrapers, saving people from such blocking.
Octoparse Cloud extraction utilizes multiple IPs to scrape one website at the same time to not only make sure one IP would not request too many times but also keep the high speed.
4. CAPTCHA
CAPTCHA(Completely Automated Public Turing test to tell Computers and Humans Apart) is often used to separate humans from scraping tools by displaying images or logical problems that humans find easy to solve but scrapers don’t.
Many CAPTCHA solvers can be implemented into bots to ensure non-stopping scrapes. Although the technologies to overcome CAPTCHA can help acquire continuous data feeds, they could still slow down the scraping process a bit.
5. Honeypot traps
Honeypot is a trap the website owner puts on the page to catch scrapers. The traps can be links that are invisible to humans but visible to scrapers. Once a scraper falls into the trap, the website can use the information it receives(e. g. its IP address) to block that scraper.
Octoparse uses XPath to precisely locates items to click or to scrape, which largely reduces the chance of falling into the trap.
6. Slow/unstable load speed
Websites may respond slowly or even fail to load when receiving too many access requests. That is not a problem when humans browse the site as they just need to reload the web page and wait for the website to recover. But scraping may be broke up as the scraper does not know how to deal with such an emergency.
Octoparse allows users to set up auto-retry or retry loading when certain conditions are met to solve the issues. It can even execute customized workflow under preset situations.
7. Dynamic content
Many websites apply AJAX to update dynamic web content. Examples are lazy loading images, infinite scrolling and show more info by clicking a button via AJAX calls. It is convenient for users to view more data on such kind of websites but not for scrapers.
Octoparse can easily scrape those websites with different functions like scrolling down the page or AJAX Load.
8. Login requirement
Some protected information may require you to log in first. After you submit your login credentials, your browser automatically appends the cookie value to multiple requests you make the way most sites, so the website knows you’re the same person who just logged in earlier. So when scraping websites requiring a login, be sure that cookies have been sent with the requests.
Octoparse can simply help users to log in to a website and save the cookies just like a browser does.
9. Real-time data scraping
Real-time data scraping is essential when it comes to price comparison, inventory tracking, etc. The data can change at the blink of an eye and may lead to huge capital gains for a business. The scraper needs to monitor the websites all the time and scrape data. Even so, it still has some delay as the requesting and data delivery take time. Furthermore, acquiring a large amount of data in real-time is a big challenge, too.
Octoparse scheduled Cloud extraction can scrape websites at the minimum interval of 5 minutes to achieve nearly real-time scraping.
There will certainly be more challenges in web scraping in the future but the universal principle for scraping is always the same: treat the websites nicely. Do not try to overload it. What’s more, you can always find a web scraping tool or service such as Octoparse to help you handle the scraping job.
Artículo en español: 9 Desafíos de Web Scraping que Debes ConocerTambién puede leer artículos de web scraping en El Website Oficial
Artikel auf Deutsch: 9 Herausforderungen beim Web ScrapingSie können unsere deutsche Website besuchen.
9 Web Scraping Challenges You Should Know | Octoparse
Web Scraping Challenges
Bot access
Web page structures
IP blocking
Captcha
Honeypot traps
Slow/unstable load speed
Dynamic content
Login requirement
Real-time data scraping
Web scraping has become a hot topic among people with the rising demand for big data. More and more people hunger for extracting data from multiple websites to help with their business development. However, many challenges, such as blocking mechanisms, will rise when scaling up the web scraping processes, which can hinder people from getting data. Let’s look at the challenges in detail.
Web scraping may not work because:
1. Bot access
The first thing to check is that if your target website allows for scraping before you start it. If you find it disallows for scraping via its, you can ask the web owner for scraping permission, explaining your scraping needs and purposes. If the owner still disagrees, it’s better to find an alternative site that has similar information.
2. Complicated and changeable web page structures
Most web pages are based on HTML (Hypertext Markup Language). Web page designers can have their own standards to design the pages, so web page structures are widely divergent. When you need to scrape multiple websites, you need to build one scraper for each website.
Moreover, websites periodically update their content to improve the user experience or add new features, which often leads to structural changes on the web page. Since web scrapers are set up according to a certain design of the page, they would not work for the updated page. Sometimes even a minor change in the target website requires you to adjust the scraper.
Octoparse uses customized workflow to simulate human behaviors so that to deal with different pages. You can modify the workflow easier to adapt to the new pages.
3. IP blocking
IP blocking is a common method to stop web scrapers from accessing data of a website. It typically happens when a website detects a high number of requests from the same IP address. The website would either totally ban the IP or restrict its access to break down the scraping process.
There are many IP proxy services like Luminati, that can be integrated with automated scrapers, saving people from such blocking.
Octoparse Cloud extraction utilizes multiple IPs to scrape one website at the same time to not only make sure one IP would not request too many times but also keep the high speed.
4. CAPTCHA
CAPTCHA(Completely Automated Public Turing test to tell Computers and Humans Apart) is often used to separate humans from scraping tools by displaying images or logical problems that humans find easy to solve but scrapers don’t.
Many CAPTCHA solvers can be implemented into bots to ensure non-stopping scrapes. Although the technologies to overcome CAPTCHA can help acquire continuous data feeds, they could still slow down the scraping process a bit.
5. Honeypot traps
Honeypot is a trap the website owner puts on the page to catch scrapers. The traps can be links that are invisible to humans but visible to scrapers. Once a scraper falls into the trap, the website can use the information it receives(e. g. its IP address) to block that scraper.
Octoparse uses XPath to precisely locates items to click or to scrape, which largely reduces the chance of falling into the trap.
6. Slow/unstable load speed
Websites may respond slowly or even fail to load when receiving too many access requests. That is not a problem when humans browse the site as they just need to reload the web page and wait for the website to recover. But scraping may be broke up as the scraper does not know how to deal with such an emergency.
Octoparse allows users to set up auto-retry or retry loading when certain conditions are met to solve the issues. It can even execute customized workflow under preset situations.
7. Dynamic content
Many websites apply AJAX to update dynamic web content. Examples are lazy loading images, infinite scrolling and show more info by clicking a button via AJAX calls. It is convenient for users to view more data on such kind of websites but not for scrapers.
Octoparse can easily scrape those websites with different functions like scrolling down the page or AJAX Load.
8. Login requirement
Some protected information may require you to log in first. After you submit your login credentials, your browser automatically appends the cookie value to multiple requests you make the way most sites, so the website knows you’re the same person who just logged in earlier. So when scraping websites requiring a login, be sure that cookies have been sent with the requests.
Octoparse can simply help users to log in to a website and save the cookies just like a browser does.
9. Real-time data scraping
Real-time data scraping is essential when it comes to price comparison, inventory tracking, etc. The data can change at the blink of an eye and may lead to huge capital gains for a business. The scraper needs to monitor the websites all the time and scrape data. Even so, it still has some delay as the requesting and data delivery take time. Furthermore, acquiring a large amount of data in real-time is a big challenge, too.
Octoparse scheduled Cloud extraction can scrape websites at the minimum interval of 5 minutes to achieve nearly real-time scraping.
There will certainly be more challenges in web scraping in the future but the universal principle for scraping is always the same: treat the websites nicely. Do not try to overload it. What’s more, you can always find a web scraping tool or service such as Octoparse to help you handle the scraping job.
Artículo en español: 9 Desafíos de Web Scraping que Debes ConocerTambién puede leer artículos de web scraping en El Website Oficial
Artikel auf Deutsch: 9 Herausforderungen beim Web ScrapingSie können unsere deutsche Website besuchen.
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 web scraping challenges
What are some challenges with web scraping?
Web scraping may not work because:Bot access. The first thing to check is that if your target website allows for scraping before you start it. … Complicated and changeable web page structures. … IP blocking. … CAPTCHA. … Honeypot traps. … Slow/unstable load speed. … Dynamic content. … Login requirement.More items…•Jan 22, 2021
Can you get in trouble for web scraping?
Web scraping and crawling aren’t illegal by themselves. … 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.
Is web scraping a good idea?
There’s a lot of demand for useful web scraping tools in the SEO industry. If you are interested in using your tech skills in digital marketing, this is an excellent project. It will make you familiar with the applications of data science in online marketing as well.
