Utilizing ML for Better Scraping, Data Extraction With a Headless Browser, and More

Utilizing ML for Better Scraping, Data Extraction With a Headless Browser, and More

Hi there! Thanks for stopping by. Here, in Scraping Digest, we share top news on everything tech & public data gathering. If you’re new to the community, make sure to subscribe and join the conversation by sharing your thoughts and ideas for future editions in the comments below.


?? Video tutorials?

How to utilize Machine Learning for better web scraping

In rule-based web scraping, the slightest change in website layout breaks the process, prompting the script overhaul to adapt to a new layout. Luckily, there’s a solution – Machine Learning, and in this presentation, we discover its power in web scraping. We delve into the intricacies of ML-based parsing, shedding light on integrating LLMs like ChatGPT into the web scraping landscape.

??For your convenience, code examples are provided in our GitHub repository.

Puppeteer Tutorial: Scraping With a Headless Browser

Want to know how to use Puppeteer for web scraping? In this tutorial, we demonstrate how to use Puppeteer to extract several types of data: a single or several elements from a website or a whole hotel listings page.?

Combining Rust and Python: The Best of Both Worlds?

Learn how to seamlessly integrate Rust and Python using Pyo3. This library allows you to write Python modules with Rust, which means you get the speed and safety of Rust along with Python's easy-to-use features!


??? Code & tools

ultrafunkamsterdam/nodriver: The official successor of Undetected-Chromedriver

Providing a blazing fast framework for web scraping, web automation, bots, and any other creative ideas that are usually obstructed by antibot systems using a relatively simple interface.

rmax/scrapy-redis: Redis-based components for Scrapy?

Redis-based components for Scrapy providing a range of features: distributed crawling/scraping, distributed post-processing, Scrapy plug-and-play components, Json supported data in Redis.

jawah/niquests: Simple, yet elegant, HTTP library, a replacement for Requests

Niquests – a drop-in replacement for Requests, which is under a feature freeze. The safest, fastest, easiest, and most advanced Python HTTP client. Production ready!

alexandermalyga/poltergeist: Rust-like error handling in Python

Rust-like error handling in Python, with type-safety in mind. Learn how to quickly install and use poltergeist on a few examples.

sugawarayuuta/refloat: Float parser faster than standard float parsing libraries

Float parser that sacrifices nothing! Accurate, compatible, and fast parser that converts strings to floating point numbers.?


Oxylabs is Europe's Fastest-Growing Web Data Collection Company for the Third Consecutive Year

We’re excited to announce that Oxylabs has once again secured its position as one of the fastest-growing companies in Europe!

“Oxylabs making the list for the third time in a row indicates that the need for reliable public data extraction is still on an upward trend. It also shows that ethical business practices are perfectly compatible with growth. Leading by example, we expect to actively foster a responsible mindset in the wider web data community.”

Julius ?erniauskas, CEO of Oxylabs


Last week, our developer, Tadas, introduced an open-source library - Oxy? Parser. The library automates HTML parsing with LLMs to parse websites automatically with little or no human intervention. It uses Pydantic models to describe the structure of the HTML and then automatically parses the HTMLs into the Pydantic models.?

All discussions about the open-source library happens in #┠??-oxyparser-discussions channel. Join us!


On April 16th, we're hosting our very first Discord live event with Senior Golang Developer, Denis Zyk. The session will be about overcoming blocks in large-scale web scraping.?Don‘t miss the chance to tap into Denis's expertise.

Join our Discord server and secure your spot!


Have questions or suggestions for future issues? Reach out to me via LinkedIn.?

Looking forward to hearing from you!

Cheers,

Liza

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