How to Use Deep Copy in Python with `deepcopy()`

🚀 Access Modifiers in Python: Naming Conventions for Encapsulation (Oop Concepts) Python doesn't have explicit access modifiers like 'private' or 'protected'. Instead, it relies on naming conventions to indicate the intended visibility of class members. Attributes and methods with a single leading underscore ('_') are considered 'protected' (meant for internal use within the class and subclasses), while those with a double leading underscore ('__') are name-mangled to make them harder to access directly from outside the class. However, these are conventions, not enforced restrictions. #oopconcepts #programming #coding #tech #learning #professional #career #development

💻 I wrote a simple Python program to check whether a number is prime or not. The program asks for input and outputs True if the number is prime, otherwise False. Here's the code 👇 num = int(input("Enter a number: ")) if num > 1:   for i in range(2, int(num ** 0.5) + 1):     if num % i == 0:       print(False)       break   else:     print(True) else:   print(False) https://lnkd.in/gaXhBG3Y #Python #Coding #Learning #Programming #Tech

💡 Understanding Python’s Global Interpreter Lock (GIL) Ever wondered why Python threads don’t always run in parallel? I recently explored this concept and created a short PDF guide “PYTHON-GIL” that breaks down what the Global Interpreter Lock is, why it exists, and how it affects multithreading. 🔍 Inside the PDF: [*] What the GIL actually does [*] Why Python uses it (and how it simplifies memory management) [*] How it impacts CPU-bound vs I/O-bound tasks [*] Ways to bypass it using multiprocessing or C extensions If you’ve ever been confused about why your multi-threaded Python code isn’t speeding up, this guide is for you. #Python #Programming #Multithreading #Developers #GIL #Learning #PythonTips

💡 Understanding Arrays in Python In Python, arrays are powerful data structures that allow you to store multiple values of the same type in a single variable. They make data handling faster and more efficient — especially for numerical or large datasets. ⚙️ 🔹 Key Highlights: Store multiple values under one name Access items using index positions (starting from 0) Great for performance in numeric operations Use the array module or go advanced with NumPy 💻 Example: import array as arr nums = arr.array('i', [10, 20, 30, 40]) print(nums) 📊 Output: array('i', [10, 20, 30, 40]) Arrays help keep your code clean and efficient — a must-know concept for every Python learner! 🐍 #Python #Coding #Learning #DataStructure #Programming #Developers #PythonTips

Today of My Python Learning Journey Continuing my exploration of Operators in Python ⚙️ — today I covered the remaining types that make Python logic powerful and dynamic 💡 ✨ Topics I learned: 🔹 Comparison Operators – to compare values and make decisions 🔹 Logical Operators – to combine conditions (like “and”, “or”, “not”) 🔹 Bitwise Operators – to work with data at the binary level (bit by bit!) 🔹 Membership Operators – to check if an item exists in a list or string 🔹 Identity Operators – to check whether two variables point to the same object in memory Each operator acts like a decision-maker, helping Python decide what to do next — just like how we make daily choices based on conditions and logic! #Python #CodingJourney #Operators #Programming #LearningEveryday #PythonForBeginners #CodingBasics

🚀 Understanding Python Lists: Mutability and Dynamic Typing Python lists are fundamental data structures that store an ordered collection of items. They are mutable, meaning their contents can be changed after creation. Lists can hold items of different data types within the same list, showcasing Python's dynamic typing. This flexibility makes lists versatile for various programming tasks, from storing user inputs to manipulating data sets. Understanding list methods like append, insert, remove, and pop is crucial for effective list manipulation. #Python #PythonDev #DataScience #WebDev #professional #career #development

🚀 Understanding Python Lists: Mutability and Dynamic Typing Python lists are fundamental data structures that store an ordered collection of items. They are mutable, meaning their contents can be changed after creation. Lists can hold items of different data types within the same list, showcasing Python's dynamic typing. This flexibility makes lists versatile for various programming tasks, from storing user inputs to manipulating data sets. Understanding list methods like append, insert, remove, and pop is crucial for effective list manipulation. #Python #PythonDev #DataScience #WebDev #professional #career #development

Today, I practiced creating a simple Python calculator using loops and conditional statements. 💻 This small project helped me understand: 🔹 How to take user input in Python 🔹 How to use while loops for continuous execution 🔹 How to apply if-elif conditions for different operations (+, -, *, /) 🔹 And how to break the loop using a quit command (q) Here’s what the program does: It asks the user to enter two numbers Then takes an operator (+, -, *, /) Displays the result instantly Keeps running until you press q to quit This might look simple, but every small program builds a strong foundation. Step by step, I’m getting more comfortable with logic building in Python. 🚀 #Python #CodingJourney #Programming #LearningByDoing #Tech #Developer

🐍📈 Python Concurrency & Parallel Programming With this learning path you'll gain a deep understanding of concurrency and parallel programming in Python. You can use these newfound skills to speed up CPU or IO-bound Python programs #python #learnpython

🐍 Exploring Python Operators! 💻 Today, I learned about some of the most important operators in Python — the building blocks that bring logic and functionality to every program. Here’s what I explored 👇 🔹 Arithmetic Operators → (+, -, *, /, %, **) 🔹 Assignment Operators → (=, +=, -=, *=, /=) 🔹 Logical Operators → (and, or, not) 🔹 Relational / Comparison Operators → (==, !=, >, <, >=, <=) Every operator helps me understand how Python thinks and processes data — step by step, I’m getting closer to mastering it. #Python #Learning #Programming #DataAnalytics #KeepGrowing