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Web scraping is a self-explanatory term.
It means scraping data from the web using bots or specialized software.
you could download the data as a spreadsheet or database for future reference.
Many website owners discourage scraping because malicious actors can abuse it to steal data or copyrighted content.
You should avoid scraping unauthorized information the owner explicitly asks not to scrape.
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How does web scraping work?
Web scraping relies on bots to automatically retrieve data from websites.
Youll first give the bot a target URL to scrape.
Web scraping bots are technically complex, but their developers have simplified the process for end users.
Some render the complete website; you might simply opt for data you want to retrieve.
Lets dive deeper into the process a web scraper undergoes to retrieve data from a website.
This request is akin to knocking on the target website’s door.
The web scraper asks for permission to reach the target website.
This part can get tricky, as some websites use sophisticated tools to block scrapers.
For example, some website owners monitor IP addresses used by scapers and block them en masse.
Thats why a scraper is often used alongside aproxy serverto counter such blocks.
Every website’s code determines its content structure, so scrapers must understand it.
Suppose you instruct a scraper to retrieve images from a website.
Itll first parse the websites code to understand where each element is placed.
Then, itll focus on extracting images and ignore the other elements.
Data extracted by web scrapers is downloaded on your local gadget in standard formats like CSV and JSON.
Then, you could seamlessly send these files to external devices or upload them online.
The above steps seem simple, but theres a catch.
Scraping is not a one-and-done process.
The web scraper repeats the above process until it scrapes all the required data.
Sometimes, it faces obstacles like an IP or usage restriction.
Some scrapers can send too many HTTP requests and crash a site, making it impossible to extract data.
It involves constant trial and error, and scraping large datasets can take a long time.
The data will be downloaded in CSV and other standard file formats.
online window extension scrapers are ideal if you dont want to download standalone software to extract data from websites.
However, they have significant limitations.
Most internet tool extension scrapers are built to scrape one page at a time.
Hence, they aren’t suitable for extracting large datasets.
These scrapers have user-friendly interfaces that the average layperson can quickly understand.
Software-based scrapers
These scrapers are standalone apps youll download on a desktop.
Theyre designed for scraping large datasets at robust speeds.
The drawback is that software-based scrapers can be technically complicated.
An average layperson might need external help to set up and run scraping tasks.
Some large-volume scraping tasks require programming knowledge to execute on software-based scrapers.
These scrapers have a steep learning curve, so youll likely need time to familiarize yourself with their interfaces.
Cloud-based scrapers
Cloud-based scrapers run on remote servers you’ve got the option to control via the internet.
First, youll sign up for the cloud-based scraping provider.
Then, you could rent servers to perform scraping tasks.
We mentioned earlier that proxy servers and web scrapers work hand in hand.
Unsurprisingly, many proxy platforms offer scraping servers for individuals and businesses.
These servers are suitable for massive scraping tasks that your desktop or laptop cant run locally.
Suppose you want to scrape all product descriptions on Amazon, the worlds biggest e-commerce marketplace.
Youre looking at thousands of pages with voluminous text, images, and videos.
A remote server works 24/7 while you pay attention to other activities.
Remote servers are convenient, but the drawback is that theyre often expensive.
In our previous example of scraping Amazon product descriptions, the target URL would be “Amazon.com.”
Step 2: Inspect the webpage
Inspect your target webpage to understand its structure.
Right-click anywhere on the webpage and selectinspect elementorview page source.
These options let you view the web page’s backend code, which is the scrapers focus.
For example, text is your desired data bang out if your goal is scraping pricing information.
Consider the legality of the data you want to scrape.
Generally, web scraping is legal if the data is publicly available.
However, scraping non-public data can be illegal and invite lawsuits.
The photos were publicly posted, yet the Dutch DPA considered it a privacy violation to scrape them.
Several European countries have similar laws that consider scraping public personal data illegal.
LinkedInprevailed in a six-year legal battle, helped by its user agreement that explicitly barred scraping profiles.
Before scraping any website where youre registered, peek if its terms of service explicitly disallow public scraping.
If so, its advisable not to scrape data from the site.
Most scraping bots use the Python programming language.
However, software-based and cloud-based scrapers often usually receive instructions via code.
Step 5: Execute the code/instructions
Execute the instructions and wait for the scraping job to complete.
Scraping jobs can take anywhere from a few minutes to a few days or weeks.
Raw scraped data often has errors, so its advisable to double-check and correct them.
you could play around with the data and learn how to tweak it to get the desired results.
Use cases of web scraping
1.
Price comparison websites
Many companies have built formidable businesses by helping shoppers find the best deals online.
They aggregate discounted deals and promote them to users, earning money via commissions and ads.
They use scraping bots to perform this task, usually high-performance servers built to extract massive data volumes quickly.
Without web scraping bots, price comparison sites would have to extract pricing data manually, which is cumbersome.
Web scrapers enable them to scrape accurate pricing data and show customers the best deals.
These scrapers power many successful price comparison sites likePriceRunnerandGetprice.
Google is the most popular search engine, but many other small players exist.
Website owners also depend on scraping to build internal search tools.
Then, you’ll refine this data and upload it to a searchable database.
Search engines usually use remote, high-performance servers for scraping because they deal with massive data volumes.
Suppose you run a real estate site focused on the Florida market.
it’s possible for you to import data from an MLS listing database into your site using web scrapers.
Youll instruct the scraping bot to scrape URLs from MLSs Florida section and download them to a CVS file.
Then, you’re free to refine the data before uploading it to your website.
Lead generation
Many companies use scraping bots to gather information about potential clients.
This practice is widely adopted by companies that sell business-to-business (B2B) services.
Suppose youre a sales representative of a banking software provider.
you’ve got the option to scrape (publicly available) contact information of local banking executives.
The aim is to contact these executives to pitch your companys banking software.
Some companies also scrape public contact information of business executives and offer them for sale.
For example, ZoomInfo has built amulti-billion dollar businessby selling a commercial search engine of contact information.
It curates this information from numerous public sources and charges monthly or annual fees to access its vast database.
However, curating and monetizing public contact information can get tricky.
We earlier mentioned a LinkedIn lawsuit against hiQ Labs for scraping public LinkedIn data.
Many platforms prohibit users from scraping data even when its public.
Thus, confirm a platforms user agreement before scraping information from it.
Sentiment analysis
Many companies use web scraping bots to gather data that indicates customer sentiment.
For example, an apparel brand can scrape reviews from various sites and import them into a single database.
Then, the brands executives analyze this database to evaluate customer sentiment and know how to improve their products.
The owner can then refine or export this file for further evaluation.
However, legal experts often cite existing data privacy laws in web scraping cases.
Below are the relevant laws.
Scraping public personal data of EU residents requires complying with GDPR laws, with potential fines for violators.
Compliance includes:
Transparency.
Be transparent about how you intend to use the scraped data.
Respect requests from users who want to access, restrict, or delete their scraped data from your database.
Implement sophisticated security measures to prevent unauthorized access to scraped data.
Establish firm data protection policies and train employees on them.
Any data breaches should be swiftly reported to the local data supervisory authority.
Scraped data shouldnt be used for illegal purposes.
You should have a lawful basis for scraping data.
GDPR applies to all European Union (EU) countries.
The CCPA differs from GDPR in several ways, including what it considers personal information.
CCPA concerns personal data that the owner provides, while GDPR considers all personal information regardless of the source.
Complying with CCPA includes
Terms of use.
Adhere to a websites terms & conditions regarding scraping.
If a websites terms bar data scraping, obey their terms to prevent potential legal troubles.
Many websites have robots.txt files indicating the sections to avoid scraping; follow these directions.
Implement robust policies to protect scraped data from malicious actors.
Scrapers can be held responsible for misuse of data stolen from them.
Avoid scraping copyrighted material without the owners permission.
Have clear purposes for scraping data and be transparent about it if asked by the owner.
Violations of the CCPA can invite fines and lawsuits from data owners.
OpenAI can afford such lawsuits, but similar cases can sink small companies.
Many companies have invoked the CFAA in civil suits against web scrapers but with mixed results.
The Ninth Circuits ruling set a precedent discouraging companies from filing lawsuits alleging CFAA violations against scrapers.
Why do many websites limit web scraping?
Web scraping bots often encounter a common issue.
Many websites implement sophisticated techniques to prevent scrapers from accessing their data.
These include
Using cookies and Captchas to differentiate real visitors from scraping bots.
Setting limits on the number of requests to a page.
This action hinders your web scrapers from making repeated HTTP requests to extract data.
Obfuscating data to feed web scraping bots confusing information.
Detecting and blocking IP addresses tied to web scraping bots and proxy servers.
Publishing fictitious content or hidden links to trap web scraping bots.
Websites discourage scraping for many reasons.
Many other platforms have implemented stricter anti-scraping measures due to fears of being held liable.
Website owners dislike scraping because of privacy fears.
Thus, you should adhere to their terms regarding scraping copyrighted or personal data.
How to bypass anti-scraping blocks
1.
Rotation implies changing IP addresses frequently to avoid getting detected.
Many proxy server providers offer seamless IP rotation.
With their servers, you’re free to alternate IP addresses with each scraping request.
Yet, a few high-traffic sites use sophisticated proxy blocklists.
Besides, some proxy providers offer a virtually unlimited pool of IP addresses.
Keep random intervals between scraping requests
A web scraper works like a robot.
It sends scraping requests at regular intervals, a common pattern website owners use to detect scrapers.
Also, avoid sending too many requests within a short period.
Adhere to this directive where applicable.
Any IP address that visits these hidden links is marked as a bot and banned from the site.
They can also change the link text color to the background color to make it transparent.
you might avoid honeypot traps by creating well-defined rules for your scraping bots to avoid hidden links.
Then, youll instruct the scraping bot not to visit these links, preventing detection.
Final words
Web scraping has many legitimate use cases, such as market research and price comparison.
Yet, many websites discourage it, and legal battles often arise from this practice.
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The content of this article is entirely independent and solely reflects the editorial opinion of TechRadar Pro.
