Web scraping, also known as web data extraction or web harvesting, refers to the automated process of extracting data from websites. While scraping can serve many useful purposes, it also raises concerns around privacy, data protection and intellectual property. Anyone looking to scrape data needs to carefully consider the legal and ethical implications.

What is Web Scraping

Scraping Data Bases involves using software tools, commonly known as scrapers or bots, to programmatically fetch and extract data from the web. The scraper will crawl from page to page, identifying and collecting relevant information. This data is then structured, stored and ready for analysis or usage in other applications.

Scrapers can extract all sorts of data – from product descriptions and pricing on ecommerce sites to contact details on business directories. The scale of scraping operations varies enormously too. A researcher may want to scrape a specific dataset from a single site. A price comparison site will continuously scrape pricing across thousands of online retailers.

Why Scrape Data

There are many legitimate reasons individuals or companies may want to scrape data:

• Competitor pricing research – Businesses will scrape competitor websites to benchmark pricing and identify opportunities.

• Product research – Researchers often scrape large volumes of ecommerce data to analyze market trends and demand.

• News monitoring – News sites and PR agencies scrape news sites and social media to monitor brand mentions.

• Recruitment – Job sites scrape listings from employer websites to aggregate vacancies in one place.

• Travel fare aggregation – Price comparison sites scrape airline and hotel sites to compare fares and rates.

• Search engine indexing – Search engines scrape web pages to intelligently index the web and serve relevant results.

Web Scraping Techniques

There are several technical approaches to scraping data:

API Access

Many websites provide APIs (Application Programming Interfaces) that allow limited programmatic access to their data. This is the easiest and most reliable way to get data. However, most sites restrict how much data you can extract via their API.

HTML Parsing

This involves identifying the relevant data within the HTML code of each webpage. The scraper will parse the HTML and extract the required data points into a structured format like CSV or JSON. This method works on any public website but is prone to breaking if site layouts change.

Text Pattern Matching

For scraping unstructured data like text blocks or reviews, scrapers can search for and extract matches based on defined text patterns like names, dates or ratings. This can be an imprecise method as matches depend heavily on the patterns defined.

Browser Automation

Browser automation tools like Selenium can drive an actual web browser to load pages and extract data. This approach is slower but can adapt to intricate websites where HTML parsing fails.

Is it Legal?

Web scraping inhabits a complex legal grey area that varies across jurisdictions. As a rule of thumb:

• Scraping publicly accessible data is generally legal with some exceptions. Private user data usually requires consent.

• Scrape responsibly – avoid overloading sites with requests and extract only what you need.

• Respect robots.txt files that indicate the website owner’s scraping policies.

• Understand copyright laws and data protection regulations applicable to your locale and usage.

Overly aggressive scraping without permission may break laws around computer intrusion, data protection and intellectual property. Websites can also employ technical countermeasures like IP blocking and CAPTCHAs to hinder scrapers.

When in doubt, it is best to seek legal counsel about your specific scraping needs. Many websites also provide APIs or data feeds to get data legitimately. Web scraping can generate immense value from the wealth of public data online, but should be approached thoughtfully and responsibly.

Scraping Responsibly

Here are some ethical guidelines to bear in mind when scraping:

• Avoid hitting sites excessively hard with scraping requests as this can affect server performance.

• Don’t claim scraped data as your own or republish it without permission where applicable.

• Use scraped data only for its intended lawful purpose – not for harassment or discrimination.

• Be transparent in allowing opt-outs if aggregating user data like emails and phone numbers.

• Implement adequate security controls when storing scraped data to prevent breaches.

• Do not scrape data protected behind logins or paywalls without permission.

• If possible, alert websites you will be scraping and accommodate any requests they have.

• Consider providing back to the site any enhancements or structured data from your scraping efforts.

Scraping need not be adversarial. By collaborating with websites, scrapers can actually help improve sites by alerting them to broken pages, errors and other issues detected during scraping.

Scraping Tools

There are many software tools available to build scrapers, from simple scripts anyone can run to robust enterprise-grade platforms.

Scripting Languages

• Python – Libraries like BeautifulSoup, Selenium, Scrapy and Pandas.

• JavaScript – Libraries like Puppeteer, Cheerio and Node Fetch.

• Ruby – Libraries like Mechanize and Anemone.

Visual Tools

Tools with graphical interfaces for building scrapers without coding:

• ParseHub

• Import.io

• Mozenda

• Kimonolabs

Managed Services

Services that provide data scraping as a fully managed solution:

• Scrapinghub

• ScrapeHero

• ProxyCrawl

• SerpApi

Scraping Best Practices

Here are some tips for executing scraping projects effectively and ethically:

• Research the site’s terms of use and scraping policies before beginning. Look for a robots.txt file with scraping instructions.

• Start small and expand the scrape gradually to avoid overloading the site. Monitor for rate limiting.

• Structure scraped data properly rather than dumping raw HTML. Plan how data will flow into other systems.

• Use proxies and random delays between requests to distribute load and appear more human-like.

• Check for and accommodate layout changes by continually sampling live pages versus just relying on your original scraper code.

• Avoid scraping data you do not fully understand or have no clear need for. It increases liability.

• Notify webmasters of your intentions and offer assistance to fix any issues caused by your scraper.

• Do not scrape personal user data like emails without consent. Anonymize any personal data inadvertently extracted.

• Delete scraped data that is no longer required – don’t hoard it indefinitely.

Scraping is a powerful technique but also comes with risks. Scrapers should continuously evaluate whether their scraping activity remains aligned with website policies, applicable laws, and ethical data sourcing practices.

Conclusion

Web scraping enables extracting massive value from the vast data available online. But it is also a double-edged sword. Scraping best practices boil down to scraping minimally, slowing down, communicating intent, and giving back. With conscientiousness and care, scraping can provide immense business and societal value in a responsible way.

joker

Professional data parsing via ZennoPoster, Python, creating browser and keyboard automation scripts. SEO-promotion and website creation: from a business card site to a full-fledged portal.