🚀 Python Learning Journey – Day 3 📅 13/03/2026 Continuing my Python learning journey at Global Quest Technologies, today’s session focused on exploring Python implementations and understanding how it compares with Java. 🔍 Topics Covered: 🔹 Flavours of Python 🔹 Differences between Python and Java 💡 Key Takeaways: ✔️ Learned about different Python implementations: • CPython – Default and most widely used • Jython – Runs on the Java Virtual Machine (JVM) • IronPython – Works with the .NET framework • PyPy – Focused on performance using JIT compilation. ✔️ Understood key differences between Python and Java : 🔹 Python is interpreted and dynamically typed, while Java is compiled and statically typed 🔹 Python emphasizes simplicity and readability, whereas Java focuses on structure and performance 🔹 Python uses indentation, while Java uses braces {} 🔹 Java generally offers faster execution, while Python provides ease of development and debugging. This session helped me gain clarity on how Python works across different environments and how it stands in comparison with Java in real-world applications. Grateful for the continuous guidance from Global Quest Technologies and G.R NARENDRA REDDY Sir. Looking forward to applying these concepts and exploring more advanced topics ahead! #Python #LearningJourney #CorePython #Programming #Java #TechSkills #Upskilling #FullStackDevelopment 🚀

Several years ago I came accross the Python paradox by Paul Graham. He argues that lisp and Python programmers are among the ones who trutly care about programming 🐍… https://lnkd.in/eJjqEtPA

🚀 Learning Progress: Python OOP – Encapsulation Continuing my journey in mastering Object-Oriented Programming, I worked on a Python program to demonstrate Encapsulation. In this program: I used a private variable __bal with data mangling to restrict direct access Implemented controlled access through methods to safely read and modify data Ensured proper data hiding, which is the core idea of Encapsulation One interesting observation was how simple and flexible Python makes encapsulation compared to Java. Unlike Java, Python doesn’t require strict getter and setter methods—data protection can be achieved more concisely using naming conventions and built-in mechanisms like data mangling. This hands-on implementation helped me understand how Python balances readability and functionality, making it easier to write clean and maintainable code. Looking forward to exploring more OOP concepts and applying them in real-world scenarios! #Python #OOP #Encapsulation #LearningJourney #Programming #SoftwareDevelopment #TAP Academy # kshitij kenganavar

In Java, private means private. In Python, it means: “I trust you not to look.” I was exploring encapsulation and discovered something interesting. In Java, access is enforced. In Python, it’s… negotiated. A double underscore (__attr) doesn’t truly hide anything. It just renames it. Which means: You *can* still access it — if you know how. That realization changed how I think about class design. Java protects the code. Python trusts the developer. Two different philosophies. Which one do you prefer? 👇 Curious to hear your perspective #Python #Java #OOP #SoftwareEngineering #LearningInPublic

Understanding Python Encapsulation Encapsulation is a fundamental concept in object-oriented programming that restricts direct access to certain attributes or methods. In Python, this is achieved using private attributes, which are designated by a preceding double underscore (e.g., `__balance`). This convention indicates that the attribute should not be accessible outside the class, promoting data hiding and ensuring better control over how the data can be modified. In the provided code, the `BankAccount` class demonstrates encapsulation. The `__balance` attribute is a private variable, ensuring that it cannot be accessed directly from outside the class. Instead, public methods like `get_balance()`, `deposit()`, and `withdraw()` are provided to interact with this private variable safely. This structure helps to validate inputs and maintain integrity, as any changes to the balance must go through these methods, which can enforce rules like not allowing negative deposits or withdrawals exceeding the current balance. This becomes critical when managing sensitive data, such as financial information in the example. By masking the underlying implementation details, encapsulation allows you to change the internal workings of a class without affecting code that uses the class. This flexibility adds to the robustness and maintainability of your code. Quick challenge: How would you modify the `BankAccount` class to include a method that prevents the balance from going below zero? #WhatImReadingToday #Python #PythonProgramming #OOP #Encapsulation #Programming

Hit 5⭐ in Java & Python on HackerRank. Key takeaways from the journey: • Improved problem-solving and logical thinking • Focused on writing clean and efficient code • Got hands-on with arrays, strings, and recursion • Learned the importance of time & space complexity • Practiced consistency and pattern recognition Next step: deeper DSA and applying these skills to real-world projects. #Java #Python #DSA #ProblemSolving #CodingJourney #HackerRank

*Day 26 of my python learning journey* Today I learned about Getter, Setter, and 3 types of methods in Python OOP. *Getter & Setter methods:* Getters are used to access private data safely → `get_name()` Setters are used to update private data with validation → `set_age()` They help protect data and add control over how variables are read or changed. *3 Types of Methods in Python:* 1. *Instance method* → Uses `self`, works with object data. Called by objects. 2. *Class method* → Uses `@classmethod` and `cls`, works with class variables. Called by class. 3. *Static method* → Uses `@staticmethod`, doesn’t use `self` or `cls`. Like a normal function inside class. One more step toward writing clean, secure OOP code. Special thanks to the CEO G.R NARENDRA REDDY Sir for constant guidance and motivation. #Python #OOP #GetterSetter #LearningJourney #Programming

𝗨𝗻𝗱𝗲𝗿𝘀𝘁𝗮𝗻𝗱𝗶𝗻𝗴 𝗥𝗲𝗰𝘂𝗿𝘀𝗶𝗼𝗻 You want to learn about recursion. Here are some simple examples to help you understand it. - Reverse a number: You can use recursion to reverse a number. - Count digits: Recursion can also be used to count the digits in a number. - Even or odd: You can use recursion to check if a number is even or odd. - Sum of digits: Recursion can be used to calculate the sum of digits in a number. These examples will help you learn about recursion. You can practice them in different programming languages like Python, Java, and JavaScript. Source: https://lnkd.in/gMgTSgbs

Day 34 of my python learning journey Today’s Python topic: Abstract Class & Interface 🐍 🚀👩💻 1. Abstract Class→ A class we cannot make objects from. It’s only a plan. We use `ABC` and `@abstractmethod`. Child class must complete the empty methods. Ex: `class Shape(ABC): @abstractmethod def area(self): pass` 2. Interface→ Python has no separate `interface` keyword like Java. But we make it using an abstract class where _all methods are abstract_. It just tells what to do, not how to do it. Main idea:Abstract class = partial plan. Interface = full plan with only rules. Both help us write clean code and force every child class to follow the same structure. Special thanks to the CEO G.R NARENDRA REDDY Sir for constant guidance and motivation. #Python #OOP #Abstraction #Interface

⚡ Why Java Still Wins in 2026 (Performance Reality) Is Python really “too slow” for modern systems? We’ve all heard: • Python is easier • Python has better libraries • Developer speed > machine speed That’s true… until you hit production scale. 💥 At scale: • Latency becomes visible • Infrastructure costs increase • Concurrency becomes a real bottleneck This is where Java still has a strong edge. 🧠 JVM optimizations (like JIT compilation) allow Java to handle high-load systems far more efficiently — sometimes dramatically so, depending on the workload. That said — Python is still the right choice in many scenarios (especially AI, data, and rapid prototyping). The real question isn’t “Which is better?” 👉 It’s “When should you use which?” I break this down in detail here: https://lnkd.in/dVjP3x4S Curious — what are you using in production today? #Java #Python #SoftwareEngineering #Backend #SystemDesign