Python Web Scraping Essentials

Python vs Python 3: What Changed and Why You Should Care Python Today: Python 3 is the modern standard shaping how developers build today. Unicode By Default: Python 3 treats text as Unicode, fixing encoding pain from #marketing #seo #socialmedia #emailmarketing #digitalmarketing #sales

Day 193 of 200 Days of Code Challenge. #CCBP #NxtWave #React_Hooks #useEffect #Rivison_Python #ReactJS #HTML #CSS #Javascript #Python #SQL  #NodeJS #ExpressJS #Components #MongoDB 🔄 String Reverse in Python Sometimes the simplest tricks make the biggest impact. Reversing a string in Python can be done in just one line: ✨ This slice notation [::-1] is Python’s elegant way of stepping backwards through a sequence. It’s concise, powerful, and a reminder of how expressive Python can be.

https://lnkd.in/eH3B3jyh Learn how to add support for Python to your Bazel project in 5 minutes. In part 2, we will explore a bit deeper into what a real Python integration looks like. If you need help with Bazel projects like this one, ask us about how we can can add a senior or principal Bazel engineer to your Slack for Bazel guidance and advice.

🐍 Python Basics Challenge – Empty Data Types Concept While practicing Python, I found a small question related to empty data types. It looks easy, but many beginners get confused here. Python set = {} tup = () list = [] string = "" 📌 Question: Which of the following is NOT an appropriate empty data type in Python? A) set = {} B) tup = () C) list = [] D) string = "" 💬 Comment your answer (A / B / C / D) Think carefully before answering. This question checks your understanding of: ✔ Empty set vs empty dictionary ✔ Tuple syntax ✔ List syntax ✔ String syntax ✔ Python fundamentals I will reveal the correct answer after a few responses. Let’s see who gets it right 👇 #Python #PythonBasics #CodingChallenge #Programming #DataAnalytics #LearnInPublic #TechCommunity

I’ve wanted to write something in Rust for a while, and recently got a bit excited about the idea of a Python library in Rust. So I open-sourced fast-ordset - an ordered set for Python implemented in Rust (PyO3 + indexmap). In benchmarks it’s about 2–10× faster than the pure-Python ordered-set on various operations. The extension is thread-safe and doesn’t hold the GIL, so it works with free-threaded Python. One downside: iteration is noticeably slower - each element crosses the Rust→Python boundary (serialization/copying), so for x in s and list(s) are slower than the Python implementation. For indexing s[i] and bulk operations it’s fine. Install: uv sync --all-extras and uv run maturin develop --release. MIT license. Repo: https://lnkd.in/dXRXdWqY #Python #Rust #OpenSource

What if you could forecast any CSV without opening a single Python file? Getting a quick forecast usually means writing a full Python script first. Even for a simple dataset, you often need to load the data, configure a model, and run the code. TimeCopilot removes that setup by allowing you to forecast any public CSV directly from the terminal. Just run timecopilot forecast with a URL to the dataset and it handles the rest. You can also specify the LLM to use or ask a business question in plain English from the same command. After running it, you get: • A forecast generated automatically • The best model selected for your data • A plain-English answer to your question #TimeSeries #Forecasting #Python #CLI

Day 1/30 Why Python code looks so simple (especially to beginners) I wrote a few lines of Python today, and my first reaction was: “Why does this look… too easy?” Coming from C++, I’m used to writing things like: int x = 10; But in Python, it’s just: x = 10 No type. No semicolon. No extra syntax. At first, it feels great. Less to write, less to think about. But then I realized: Python isn’t removing complexity. It’s just hiding it. The language handles a lot behind the scenes, so you can focus on logic instead of types or memory. That’s probably why beginners find it easier to start with. But coming from C++, it feels different. I’m used to having more control. Python feels more like trusting the system to do the right thing. Still getting used to it, but I can already see why people move faster with it. Let’s see how this plays out over the next few days. #Python #cpp#LearningInPublic #30DaysOfCode

🐍📰 Jupyter Notebook: An Introduction In this tutorial, you learn how to get started with The Jupyter Notebook, an open source web app that you can use to create and share documents that contain live code, equations, visualizations, and text #python

📌 Installing and Importing BeautifulSoup in Python To start web scraping in Python, we first need to install the BeautifulSoup library. Installation command: pip install beautifulsoup4 After installation, we can import it in Python using: from bs4 import BeautifulSoup In most web scraping tasks, the requests library is also used to download the HTML content of a webpage. By combining requests and BeautifulSoup, we can download web pages and extract useful information from their HTML structure. Currently exploring more concepts in Python and Web Scraping as part of my learning journey. #Python #WebScraping #BeautifulSoup #DataAnalytics #LearningPython

Scraped real data from a Wikipedia page using Python—just BeautifulSoup, Requests, and Pandas. Turned raw HTML tables into a clean DataFrame.  #Python #WebScraping #Pandas https://lnkd.in/gU27k4Sp