Understanding Python Literals and Collections

Python 3.14 dropped a few days back. It's not super sexy, but it has a few non-avoidable features. My favourite is removing the GIL (not completely) and allowing multi-threading. It's less performant in single-threaded scenarios as they claim, but it's far better than 3.13. This will be a game changer for Python. Python is no more single-threaded. :) https://lnkd.in/grTHHNNj #Python314 #PythonDevelopment #GIL #FreeThreading #MultiThreading #Performance #CPython

🐍 Week 3: Python Foundations In Python, variables and data types are the building blocks of every program. They aren’t scary — they’re powerful! ✨ Common Data Types in Python: 🔢 int → Whole numbers (e.g., x = 10) ➗ float → Decimal numbers (e.g., pi = 3.14) 🔤 str → Text strings (e.g., name = "John") ✅ bool → True/False values (e.g., is_active = True) 💡 Tip: Python automatically detects the type when you assign a value — no need to declare it! 👉 Mastering these basics is your first step to solving real problems with Python. #LearnPython #Coding #PythonProgramming #DataScience

🐍 Understanding Lists in Python In Python, a List is one of the most powerful and commonly used data structures. It helps you store multiple items in a single variable — even if they are of different data types! ✅ Key Features of Lists: ▪️ Ordered → Items have a defined order that won’t change. ▪️ Mutable → You can modify, add, or remove elements after creation. ▪️ Allow Duplicates → Lists can contain repeated values. ▪️ Heterogeneous → Store multiple data types (e.g., integers, strings, floats) in one list. 🚀 Lists are the backbone of Python programming — simple, flexible, and incredibly powerful! #Python #PythonProgramming #DataStructures #Coding #LearnPython #PythonDeveloper #TechLearning #LinkedInLearning

The newly released Python 3.14 brings support to free-threading, in simpler terms it lets python scripts get more done, faster, with less impact on the machine. If you're interested in trying the free-threading capabilities you will have to compile a version of python with the necessary --disable-gil flag. If that sounds daunting (it's not at all really) you may find my latest blog post useful https://lnkd.in/gYkQaT6g . #python #async #asynchronous The image used here is courtesy of : W.carter, CC BY-SA 4.0 <https://lnkd.in/gFSAXQpH>, via Wikimedia Commons

#Problem-Write a Python program to convert a given #dictionary into a list of lists. #Solution: my_dict = {1: 'red', 2: 'green', 3: 'black', 4: 'white', 5: 'black'} result = list(map(list, my_dict.items())) print(result) #another #way: result1 = [] for item in my_dict.items():     result1.append(list(item)) #print(result1)

📝 Python Copy Methods Explained! 🐍 Understanding how data is copied in Python is crucial, especially when working with lists, dictionaries, or other complex objects. Here’s a simple way to visualize it: * Assignment (=) → Both variables reference the same object. Changes in one affect the other. * Shallow Copy → Creates a new top-level object, but nested objects are still shared. * Deep Copy → Creates a completely independent copy, including all nested objects. #Python #Programming #PythonTips #LearnPython #DeveloperEducation #Coding

🔍 Understanding Object References in Python 🐍 Ever wondered how variable assignments work under the hood in Python? Here’s a simple visual breakdown of object referencing and how Python handles memory: ✅ x = 5 → x points to the value 5 ✅ y = x → both x and y point to the same object (5) ✅ x = "Geeks" → x now points to a new object ("Geeks"), while y still points to 5 ✅ y = "Computer" → y now points to "Computer", and the value 5 becomes unreferenced (eligible for garbage collection) 🧠 This is a great example of how Python manages memory and object references—especially useful when working with mutable and immutable types. 💬 Have you encountered unexpected behavior due to object references in your code? Share your experience below! #Python #Programming #ObjectReference #MemoryManagement #LearningByDoing #TechTips #AIReady #ManualToAutomation #CareerTransition #Learning #SumitShrivastav

#Day94 of #100DaysOfCode 🚀 Today, I focused on Nested Lists and String Formatting in Python 🐍. 📘 Nested Lists: I explored how to create and access multi-dimensional lists — perfect for representing data like matrices or tables. It was interesting to see how indexing works within multiple layers of lists! 🧩 String Formatting: I learned different ways to format strings using techniques like f-strings, format(), and % formatting, which make displaying data more readable and dynamic. Every new concept is strengthening my foundation and helping me write cleaner, more efficient Python code. 💪✨ #Nxtwave #ccbp #100DaysOfCode #Python #NestedLists #StringFormatting #LearningEveryday #CodingJourney #ProblemSolving #Consistency