Tag: web scraping

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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

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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Challenge SaaS

My experience with Zyte AI spiders, part 2

I’ve described my initial experience with Zyte AI spiders leveraging Zype API and Scrapy Cloud Units. You might find it here. Now I’d share more sobering report of what happened with the data aggregator scrape.

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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

My experience of manual, no-code scrape of a bot-protected site

Recently we discovered a highly protected site — govets.com. Since the number of target brand items of the site was not big (under 3K), I decided to get target data using the handy tools for a fast manual scrape.

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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

Choosing the Best Proxies for Web Scraping

From eCommerce and market research to competitive analysis and more, web scraping has become an integral part of data collection. And for some, it’s the secret sauce for success.

But with great scraping power comes great responsibility. 

Web scraping can result in IP bans and other harsh restrictions. To avoid these issues, many turn to proxies, which act as intermediaries between your requests and the target website. In this article, we’ll explore the top 3 proxy types for web scraping and focus on the key benefits of each proxy. Let’s go!

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Challenge Development

Python, Selenium for custom browser automation scraper

Recently we’ve got the tricky website, its data being of dynamic nature. Yet we’ve applied the modern day scraping tools to fetch data. We’ve develop an effective Python scraper using Selenium library for browser automation.

About the project

We were asked to have a look at a retailer website.

And our task was to gather data on 210 products’ availability in 945 shops. The scrape resulted in about 200K data entries in a CSV format. Moreover, every line contained information about name, link, brand, store and the availability of a product. Below you can familiarise yourself with a small data sample we were able to gather.

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Challenge

Web Scraping: 5 pros and cons

Web scraping, also known as data mining or web harvesting, is the process of extracting data from websites automatically. The extracted data can be used for various purposes, such as market research, price monitoring, sentiment analysis, and many more. However, web scraping has both advantages and disadvantages. In this article, we will discuss the five main pros and cons of web scraping.

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Categories
Challenge Development

AirTable scrape challenge

I need to get info from AirTable, see a table example.

The problem is that data are loaded highly dynamically. HTML contains only the information that you currently see on the browser screen.

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If there are a lot of records then it is difficult to collect such a table. One of the possible ways is to calculate the size of the screen and rows in the table. Then using the browser automation and use to make a script that will scroll through it bit by bit and collect data.

Is there any other feasible way to get data of a table? For example there is a HTTP requests coding way to get dynamic data.

JS infinite scroll does not work for AirTable either.

Please comment down here if having some tips, hints.