Python Web Scraping Tutorials and Techniques

Built a Web Scraper with Pagination using Python. Features: 1.Scrapes quotes and authors from multiple pages 2.Implements pagination to fetch data beyond a single page 3.Allows user to control the number of results 4.Handles invalid inputs and stops when pages end This helped me understand: 1.How pagination works in web scraping 2.Loop-based data collection across pages 3.Structuring scraped data for better readability.Cognifyz Technologies

🐍📈 Python Web Scraping — This learning path you’ll learn the core Python technologies and skills you need to build your own web scraper. Web scraping is about downloading structured data from the web and processing selected data. #python #learnpython

🐍📰 Altair: Declarative Charts With Python Build interactive Python charts the declarative way with Altair. Map data to visual properties and add linked selections. No JavaScript required https://lnkd.in/ghbuFY3H

Most learners do not explore beyond Python basics… the true beauty lies within👇 Today I dived deep into the following Python concepts: 🔹 Functional programming concepts ➡️ map(), filter(), lambda 🔹 Modules and Standard Library ➡️ built-in libraries of Python that make Python awesome. ➡️ I looked further into: 📦 The random module ➡️ generation of random data, simulations, sampling 📁 The os module ➡️ file handling and operating system path management 🧠 The array module ➡️ efficient memory usage for numeric data types  ✔ Regular Expressions (Re module)    → pattern-based text analysis  I created: ✔️  A Fake data generator(generates realistic fake user data) Link - https://lnkd.in/g69scMzy  ✔️ Log Analyzer(Parsed log files using regex)- Link - https://lnkd.in/gMiN3KF9 #Python #DataAnalytics #LearningInPublic #CodingJourney

The Hidden Cost of Inline Code in Claude Code Command Files Inline Python in Claude Code command files bloats token usage and hurts maintainability. Learn how to fix it with a proper CLI layer.... https://lnkd.in/exkTBynr

🚀 Exploring Web Scraping with Python These days, I’ve been working on web scraping using Python and trying out different scripts and tools to understand how data extraction works in real-world applications. Some of the tools I explored: 🐍 Python Scripts 🌐 BeautifulSoup 🎭 Playwright 🕷️ Scrapy ⚙️ Apify Among all of them, I was really impressed with the Scrapy framework. It feels powerful, structured, and beginner-friendly once you understand the basics. The built-in features like request handling, pagination, and data pipelines make scraping much more efficient. Still learning and improving step by step, but it’s exciting to see how easily we can collect and structure web data using Python. #Python #WebScraping #Scrapy #DataEngineering #LearningJourney

📘 Web Scraping with Python ✍️ Ryan Mitchell A great book to learn how to extract data from real-world websites using Python. It covers tools like BeautifulSoup, Scrapy, and Selenium, and explains how modern websites work, including APIs and JavaScript-based content. Perfect for anyone interested in automation, data collection, or building scraping tools. 🔗 Read here: https://lnkd.in/gKeQG8We⁠ #Python #WebScraping #Automation

Python List Methods Tip: append() and extend() Most Python Beginners Don’t Realize This List Mistake, append() and extend() look almost the same… But using the wrong one silently changes your data structure. Here’s the real difference: - append() adds the entire object as ONE element. - extend() adds each element individually. That means this: - append() → Creates nested lists - extend() → Keeps list flat Why This Matters: - This small mistake often causes unexpected bugs while looping, filtering, or processing data. - Many developers only notice it when their logic suddenly stops working. Simple Rule To Remember: - If you want to add one item → append() - If you want to merge items → extend() Small concepts like this make your Python code cleaner and easier to debug. Have you ever accidentally created a nested list using append()? #Python #LearnPython #PythonTips #Programming #Coding #SoftwareEngineering #PythonDeveloper

Async Web Scraping in Python: httpx + asyncio for 10x Faster Data Collection Created by Vhub Systems Async Web Scraping in Python: httpx + asyncio for 10x Faster Data Collection Synchronous scraping makes requests one at a time. While you wait for one response, you're doing nothing. Async scraping makes 10-50 requests simultaneously — same time, 10-50x the output. Here's how to actually implem... link https://lnkd.in/e6C3Ccfm pubDate Fri, 03 Apr 2026 03:09:55 +0000

Python Supply-Chain Compromise: This is news: A malicious supply chain compromise has been identified in the Python Package Index package litellm version 1.82.8. The published wheel contains a malicious .pth file (litellm_init.pth, 34,628 bytes) which is automatically executed by the Python interpreter on every startup, without requiring any explicit import of the litellm module. There are a lot of really boring things we need to do to help secure all of these critical libraries: SBOMs, SLSA, SigStore. But we have to do them.