String Validators HackerRank Challenge

🚀Python Practice Update Today I solved the “String Validators”problem on HackerRank. Key learnings: • Practiced Python string validation methods 🔤 • Used functions like `isalnum()`, `isalpha()`, `isdigit()`, `islower()`, and `isupper()` ✅ • Learned how to check different character types in a string 🔍 • Improved logic-building with loops and conditions 💡 Each challenge is helping me get stronger in Python basics. 🚀 🔗Link: https://lnkd.in/dA4XRHmS #Python #HackerRank #StringValidators #CodingPractice #ProblemSolving #100DaysOfCode #LearningPython #Codegnan #Programming

𝗦𝗲𝗹𝗳 𝗜𝗺𝗽𝗿𝗼𝘃𝗶𝗻𝗴 𝗣𝘆𝘁𝗵𝗼𝗻 𝗦𝗰𝗿𝗶𝗽𝘁𝘀 𝗪𝗶𝘁𝗵 𝗟𝗟𝗠𝘀 I wanted code to fix itself. I used LLMs to make Python scripts improve their own logic. Here is the setup: - Python 3.8 or later - llm_groq - transformers The workflow is simple. The LLM writes a piece of code. A script runs the code to check for errors. If the code fails, the LLM receives the error. The LLM rewrites the code to fix the mistake. I faced problems. LLMs write wrong code sometimes. I built a strict evaluation function to catch these errors. I tested prompts to get better results. Self-improving code changes how you build software. Start building your own scripts. Source: https://lnkd.in/gcyzxwXz Optional learning community: https://t.me/GyaanSetuAi

🚀 Python Problem Solving Today I solved a beginner-friendly problem from HackerRank: ✅ Python If-Else (Conditional Statements) 📌 Problem: Given an integer n, print "Weird" or "Not Weird" based on conditions like: Odd / Even Range checks (2–5, 6–20, >20) 💡 Concepts I practiced today: 🔹 If-Else statements 🔹 Modulus operator (%) 🔹 Logical conditions (and, or) 🔹 Range-based decision making

👩🍳 "Python isn't programming. It's writing recipes that the computer follows. Exactly. Every time." That's what TryHackMe's Python: Simple Demo room showed me. The recipe structure: 📝 Variables → Ingredients. name = "Alice", age = 25, is_hacker = True 🥣 Functions → Steps in the recipe. def greet_user(): then print("Hello") 🔁 Loops → Repeat a step. for i in range(5): → do something 5 times ⚡ Conditionals → If this, do that. if temperature > 100: print("Too hot!") What I built in this room: python name = input("What is your name? ") print(f"Hello, {name}!") First program. Input. Output. It worked. Felt like magic. Why this matters for security: 🔐 Automate log analysis (read 10,000 lines in 1 second) 🔐 Build your own port scanner 🔐 Decode encoded data (Base64, hex, binary) 🔐 Reverse engineer simple malware The big takeaway: You don't need to be a developer. You need to be someone who can tell the computer what to do. Python is how you talk. Recipe written. Computer followed. Room complete. 🐍 #PythonSimpleDemo #TryHackMe #Python #CodingForSecurity #Automation #CyberSecurity #Infosec

🐍 asyncio.gather() might be the new goto of async Python. For years we used: asyncio.create_task() asyncio.gather() And accidentally created zombie tasks, coroutines still running long after the request finished. Python 3.11 introduced a different model: ⚙️ Structured Concurrency with asyncio.TaskGroup. Clear task lifecycles. Deterministic cancellation. No background chaos. I break down why this is one of the biggest shifts in Python async programming. 👉 https://lnkd.in/eBF_AkNe #python #asyncio #backend #softwaredevelopment #engineering

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

I’ve been actively practicing Python on HackerRank and recently completed a new set of challenges: ✔️ Mutations ✔️ Find a String ✔️ String Validators ✔️ Text Alignment These problems helped me dive deeper into string handling and formatting, which are fundamental in real-world applications. 💡 Key Learnings: Gained a better understanding of string immutability and how to work around it (Mutations) Improved logic for substring search and pattern counting Explored built-in validation methods like isalnum(), isalpha(), isdigit(), and more Practiced formatting techniques to create structured text outputs Working through these challenges is helping me strengthen my coding fundamentals and think more logically while writing efficient Python code. URL's: https://lnkd.in/gaDpyXmA https://lnkd.in/ghjRjXh9 https://lnkd.in/gGHCVukq https://lnkd.in/gRmrhQnx https://lnkd.in/gs8x-432

Python Tuples — Quick Guide with Examples A tuple in Python is an ordered, immutable collection that allows duplicate values. Once created, you cannot modify its elements. Creating a Tuple t = (10, 20, 30) Single element tuple (comma is required) t = (5,) Accessing elements t = (10, 20, 30) print(t[0]) # 10 Tuple slicing t = (1, 2, 3, 4) print(t[1:3]) # (2, 3) Tuple concatenation t1 = (1, 2) t2 = (3, 4) print(t1 + t2) Tuple unpacking person = ("John", 25, "Analyst") name, age, role = person Key Features: ✔ Ordered ✔ Immutable ✔ Allows duplicates ✔ Faster than lists ✔ Can store multiple data types When to use tuples? Use tuples when data should not change — like coordinates, database records, fixed configurations, etc. #Python #PythonBasics #DataStructures #Tuple #Coding #LearnPython #Programming #PythonForBeginners

Hi DataScientists, In Python i programmed a complete new integration of discriminant analysis , cluster analysis and factor analysis. 1. It is based on the following intuition: clustering the Fa - scores removes random noise and discriminant analysis is in fact a rotation technique. 2. So the best sequence is: A. factoranalyse a datamatrix, B. cluster the factorscores, C. use the clustervector to rotate the factorscores by discriminant analysis. 3. Now we have as outputs: F as factorscores, DA as discriminantscores, L as loading matrix of FA , and W as loading matrix of DA. 4. These four outputs can be further analyzed and compared Happy coding!

Your competitor just automated 3 months of data work in a weekend. They used a 30-line Python script. You spent those 3 months doing it manually. This isn't a talent gap. This is a tool gap. And the tool is learnable if someone teaches it in your language. Follow along. This is about to change for you.