Gaddala Anjani’s Post

Today I learned about Sets in Python 🔥 A set is an unordered collection of unique elements — no duplicates allowed! 🔹 Key Points ✔ Create: s = {1, 2, 3} ✔ copy() – duplicate set ✔ update() – add multiple elements ✔ pop() – remove random item ✔ remove() – remove specific item ✔ discard() – remove without error 🔗 Operations 🔸 Union | → combine 🔸 Intersection & → common values 🔸 Difference - → unique values 🔸 Symmetric Difference ^ → uncommon values 🧠 Set Comprehension {x*x for x in range(5)} 💡 Why use sets? ✅ No duplicates ✅ Fast operations ✅ Easy comparisons 📌 Conclusion: Sets make handling unique data simple and efficient. Global Quest Technologies #Python #LearnPython #DataStructures #CodingJourney #100DaysOfCode #Programming #Developers #PythonDeveloper #TechLearning

🔥 I asked 20 developers this Python question. Only 3 got it right. Let’s see if you’re one of them 👇 a = (1, 2, [3, 4]) a[2] += [5, 6] print(a) 💡 What happens? A. (1, 2, [3, 4, 5, 6]) B. TypeError C. (1, 2, [3, 4]) D. TypeError BUT list still changes ⚠️ Most people get this WRONG. Take 10 seconds. Think carefully. 💬 Drop your answer below (no cheating, no running code ) I’ll reply with the correct answer + explanation. #Python #Programming #Developers #CodingChallenge #TechInterview #LearnPython #SDET #AutomationTesting #DeveloperCommunity #AI

Python's Global Interpreter Lock (GIL) has been both a blessing and a curse. The GIL prevented true multi-threaded parallelism in CPython — one of the biggest complaints from developers building CPU-intensive Python applications. But Python is finally removing it. Here's what that means: → True multi-threading: No more being forced to use multiprocessing for CPU-bound tasks just to bypass the GIL → Better multicore utilization: Threads can actually run in parallel across cores → Simpler code: Less complexity around process spawning, shared memory, and serialization → Hybrid approaches work: You can still use asyncio for I/O, threads for cleanup, and multiprocessing where needed The GIL was a pragmatic solution that let Python dominate in scripting, data science, and web development. Removing it is an admission that the ecosystem has grown up. Python is becoming the language that can do everything well — and removing the GIL is a big step in that direction. What's your take? Is this the right move or are you team multiprocessing? 👇 #Python #GIL #Multithreading #Programming #Performance

Most developers think generators are just about saving memory. That’s true, but it misses the more interesting part. Generators give you control over when work happens. Nothing runs until the next value is requested. That small detail changes how you design data flows, especially when you’re dealing with streams, pipelines, or external systems. In this week’s video, I show how generators act as small state machines, how to build clean data pipelines with them, and how features like `send()` and async generators extend that model even further. If you want to get better at designing data flows in Python, this is worth understanding properly. 👉 Watch the full video here: https://lnkd.in/eHrPzaQJ. #python #softwaredesign #cleancode #generators #developers #arjancodes

Most developers think generators are just about saving memory. That’s true, but it misses the more interesting part. Generators give you control over when work happens. Nothing runs until the next value is requested. That small detail changes how you design data flows, especially when you’re dealing with streams, pipelines, or external systems. In this week’s video, I show how generators act as small state machines, how to build clean data pipelines with them, and how features like `send()` and async generators extend that model even further. If you want to get better at designing data flows in Python, this is worth understanding properly. 👉 Watch the full video here: https://lnkd.in/eztrHhmx. #python #softwaredesign #cleancode #generators #developers #arjancodes

DAY-12 PYTHON SERIES What is Polymorphism? Polymorphism means “many forms.” In Python, it allows the same function or method to behave differently depending on the object or context. 🔹 Why is it useful? ✔ Makes code flexible and reusable. ✔ Improves readability. ✔ Allows different classes to use the same method name. 🔹 Example in Python: class Dog: def sound(self): print("Dog barks") class Cat: def sound(self): print("Cat meows") for animal in (Dog(), Cat()): animal.sound() 🔹 Real-world example: A person can be a student, employee, or teacher — same person, different roles. 💡 Key Idea: Same method name, different implementations. #Python #OOP #Polymorphism #Coding #Programming #LearnPython #Developer #SoftwareEngineering #100DaysOfCode #Tech

🚀 Excited to share a mini project I built using Python and Pandas! In this project, I created a simple data cleaning and analysis tool that allows users to: ✅ View all columns in a dataset ✅ Select a specific column to work with ✅ Explore unique values in that column ✅ Replace keywords dynamically ✅ Count how many times a specific value appears 💡 This project helped me understand how important data preprocessing is in real-world data analysis. Even small scripts like this can make handling datasets faster and more efficient. 🛠️ Tools & Technologies: Python 🐍 | Pandas 📊 #Python #Pandas #DataScience #DataAnalysis #DataCleaning #MachineLearning #Coding #Programming #BeginnerProjects #Tech #LearnPython #Analytics.

🚀 Getting Started with Python Sets 🐍 In Python, a set is an unordered collection of unique elements. It’s perfect when you want to remove duplicates or perform mathematical operations like union, intersection, and difference. 🔹 Example: numbers = {1, 2, 3, 3, 4} print(numbers) # Output: {1, 2, 3, 4} ✨ Key Features: *) No duplicate values *) Fast membership testing *) Supports set operations 📌 Use sets when you need clean, unique data and efficient operations. #Python #Coding #Programming #PythonLearning #Developers

Exploring the Python ecosystem 🐍 It’s amazing how one language can be used for: ✔ Data Analysis ✔ Machine Learning ✔ Web Development ✔ Automation Sharing this quick guide of popular Python libraries and their uses 📊 #PythonJourney #Coding #LearnToCode #Tech

The true beauty of Python lies in its simple syntax and powerful libraries 1: Whether it’s Machine Learning or Data Science 2: Web Development or Automation 3: Image Processing or Game Development Python offers amazing tools for every field like NumPy, TensorFlow, Django, Flask, OpenCV, and many more! Python is not just a programming language, it’s a complete ecosystem that makes developers’ lives easier. That’s the real beauty of Python #Python #BeautyOfPython #Coding #Programming #Developers #Tech