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Challenge Development

Playwright Scraper Undetected: Strategies for Seamless Web Data Extraction

Web scraping has become an essential tool for many businesses seeking to gather data and insights from the web. As companies increasingly rely on this method for analytics and pricing strategies, the techniques used in scraping are evolving. It is crucial for scrapers to simulate human-like behaviors to avoid detection by sophisticated anti-bot measures implemented by various websites.

Understanding the importance of configuring scraping tools effectively can make a significant difference in acquiring the necessary data without interruptions. The growth in demand for such data has led to innovations in strategies and technology that assist scrapers in navigating these challenges. This article will explore recent developments in tools and libraries that help enhance the functionality of web scraping procedures.

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Challenge Development

Oxylabs’ Web Scraper API – Experience & more

Experience

We’ve succesfully tested the Web-Scraper-API of Oxylabs. It did well to get data off the highly protected sites. One eg. is Zoro.com protected with Akamai, DataDome, CloudFlare and ReCaptcha! See the numerical results here.

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Development Monetize

Web Scraping: contemporary business models

In the evolving world of web data, understanding different business models can greatly benefit you. Since 2010’s, the growth of web scraping has transformed from a niche interest into a widely used practice. As the demand for public data increases, you may find new opportunities in various approaches to data collection and distribution.

In the post we’ll take a look of 4 business model in the data extraction business:

  • Conventional data providers
  • SaaS providers
  • Data / market intelligence tools
  • Data marketplace (multiple buyers & multiple sellers)
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Development

Importance of using proxies for web scraping

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Development

AI Usage in Web Scraping: Optimizing Data Collection and Analysis

The rise of artificial intelligence has transformed various industries, and web scraping is no exception. AI enhances web scraping by increasing efficiency, accuracy, and adaptability in data extraction processes. As businesses increasingly rely on data to drive their decisions, understanding how AI-powered techniques can optimize these scraping efforts becomes crucial for success.

Our exploration of AI in web scraping will cover various techniques and algorithms that enhance traditional methods. We’ll also delve into the challenges organizations face, from ethical concerns to technical limitations, and discuss innovative solutions that can overcome these hurdles. Real-world applications showcase how companies leverage AI to gather insights quickly and effectively, providing a practical lens through which we can view this technology.

By the end of the post, we’ll have a clearer understanding of not only the fundamentals of AI in web scraping but also its potential implications for the future of data collection and usage.

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Development SaaS

My experience with Zyte AI spiders, part 1

Recently I was given a bunch of sites to scrape, most of them being simple e-commerce. I decided to try Zyte AI powered spiders. To utilize it, I had to apply for a Zyte API subscription and access to Scrapy Cloud. Zyte AI proved to be a good choice for the fast data extraction & delivery thru spiders that are Scrapy Spiders. Below you can see my experience and the results.
I have done another “experience” post on the Zyte platform usage.

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Challenge Development

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Development

Crawling web pages with Netpeak Spider in conjunction with MarsProxies, NetNut and IPRoyal proxies

NS-owl

Agree, it’s hard to overestimate the importance of information – “Master of information, master of situation”. Nowadays, we have everything to become a “master of situation”. We have all needed tools like spiders and parsers that could scrape various data from websites. Today we will consider scraping the Amazon with a web spider equipped with proxy services.

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Development

Merge files in Windows cmd & Power Shell

Windows cmd

cmd /c 'copy /y /b *.json output.json' 

Windows Power Shell

2 options are here:

Get-Content *.json | Set-Content result.json
Copy-Item *.json output.json

How to wrap joined lines into valid JSON

After merging json files we append commas to the end of each line and bracket around the whole content with [ ] using eg. Notepadd++ for that. Thus we get a valid JSON:

[
{ "Full Year Tax":"145,26$"… },
{ "Full Year Tax":"139,00$"… },
{ "Full Year Tax":"100,00$"… }
]

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Development

Amazon scrape tip

Recently we’ve met requirements to scrape Amazon data in big quantities. So, first of all I’ve tested the data aggregator for being bot-proof or anti-bot protection. For that I used the Discord server Scraping Enthusiasts, namely Anti-bot channel.

Since Amazon is a hige data aggregator we recommend readers to get acquainted with the post Tips & Tricks for Scraping Business Directories.