Scrapy
Apify
Octoparse
import.io
ParseHub
ScrapingBee
Portia
Scraper API
KubeMastery
KodeKloud
I wanted to learn Kubernetes, but the options were either "build a local lab" or pay for expensive classes built around cloud environments. I wanted something you could just open and learn from. So I built a browser-based cluster simulation with lessons to follow along.
It behaves like Kubernetes, but it's just JavaScript under the hood. Enough to run kubectl commands, create resources, and watch their lifecycle play out. There's also a live cluster visualizer so you can see your nodes, Pods, and containers in real time.
Once you've covered the concepts, you can jump into CKA drills. Each drill is a standalone, time-boxed scenario that mirrors the real exam format: a broken cluster state, a concrete task, and a pass-or-fail outcome.
The goal isn't to simulate the exam. It's to build the reflex of diagnosing and fixing things quickly, so that when you sit the real exam, the commands and the reasoning are already automatic.
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Scrapy is recommended for developers, data scientists, and businesses that need to gather data from websites efficiently. It's particularly useful for projects involving data aggregation, market research, competitive analysis, and monitoring pricing changes across various platforms.
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Based on our record, Scrapy seems to be more popular. It has been mentiond 101 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Think about what a mature scraping project already contains. There is a schema that every item must validate against. There are field coverage thresholds, because a run where only 60% of products have prices is a failed run no matter what the exit code says. There are expected item counts, error rate ceilings, and finish reason checks. In the Scrapy world we even have a dedicated framework for all of this, and I... - Source: dev.to / 2 months ago
This guide walks through the full process using uv, a fast, modern Python toolchain that replaces pip, virtualenv, pip-tools, twine, and build with a single tool. We will write a reusable Scrapy download handler, structure it as a proper Python package, test it, and publish it to PyPI. - Source: dev.to / 3 months ago
In Scrapy, Zyte API integrates via the scrapy-zyte-api package:. - Source: dev.to / 3 months ago
Scrapy is the standard Python framework for web scraping. It handles crawling, scheduling, and data pipelines. rs-trafilatura plugs into Scrapy as an item pipeline โ your spider yields items with HTML, and the pipeline adds structured extraction results automatically. - Source: dev.to / 4 months ago
One might ask, what about Scrapy? I'll be honest: I don't really keep up with their updates. But I haven't heard about Zyte doing anything to bypass TLS fingerprinting. So out of the box Scrapy will also be blocked, but nothing is stopping you from using curl_cffi in your Scrapy Spider. - Source: dev.to / almost 2 years ago
Apify - Apify is a web scraping and automation platform that can turn any website into an API.
KodeKloud - We are a fast growing EdTech startup on trending technologies in IT and Cloud Computing.
Octoparse - Octoparse provides easy web scraping for anyone. Our advanced web crawler, allows users to turn web pages into structured spreadsheets within clicks.
import.io - Import. io helps its users find the internet data they need, organize and store it, and transform it into a format that provides them with the context they need.
ParseHub - ParseHub is a free web scraping tool. With our advanced web scraper, extracting data is as easy as clicking the data you need.
ScrapingBee - ScrapingBee is a Web Scraping API that handles proxies and Headless browser for you, so you can focus on extracting the data you want, and nothing else.