Comparing LOC in Python, Java, and C++: A Quick Experiment

Some languages did not get the class implementations right. In Rust and Python, you need to access class/struct fields through "self". In Go language, you usually access struct fields using a single letter variable like "s" for Server struct. All this is unnecessary, you should be able to access class/struct fields like you would access local variables. This is how it is done in Java and C++. Cluttering the class/struct code with "self" makes the code less readable.

A comment I saw recently, along with a debate among my classmates, highlighted a key misunderstanding beginner developers often have: "If a programmer manages Python, why do they still think C++ is so much harder?" The most honest and relatable response sums up the C++ pain perfectly: "Because the syntax error annoys you when you are on 110 lines, the compiler shows an error on line 6, and after an hour of debugging you find out it was just one extra or missing bracket or semicolon." The difficulty isn't about understanding the logic that transfers between languages. It's about how the language is processed. Python (Interpreted): It runs code line-by-line, uses simple indentation for structure, and offers quick feedback. C++ (Compiled): It demands that your entire program be syntactically perfect before it can run. Moving from Python to C++ isn't just swapping keywords; it's transitioning from a friendly environment to a rigorous one. #programming #softwaredevelopment #python #cplusplus #codinglife #students #TechEd

Day 8 – Strong Number (Factorial Sum of Digits) – Java & Python 💡 Problem: A number is called a Strong Number (or Factorion) if the sum of the factorial of its digits equals the number itself. Examples: 145 → 1! + 4! + 5! = 145 ✅ 2 → 2! = 2 ✅ 40585 → 4! + 0! + 5! + 8! + 5! = 40585 ✅ 123 → 1! + 2! + 3! = 9 ❌ 🧠 Approach: 1️⃣ Extract each digit of the number. 2️⃣ Find the factorial of that digit and add it to a running sum. 3️⃣ Compare the final sum with the original number. Optimization Tip: Precompute factorials of digits 0–9 once and reuse them — avoids repetitive calculations. Time Complexity: O(d) Space Complexity: O(1) where d = number of digits. our Turn: Did you know there are only four Strong Numbers (1, 2, 145, 40585) under 1 million? Try running the code and share your results 👇 #CodeWithTanseer #DSA #Java #Python #CodingChallenge #ProblemSolving #Numbers #MathInCode #SoftwareEngineer #BackendDeveloper #InterviewPrep #LogicalThinking #Factorial

Lately, I've been playing with Python and noticed how it handles multiple inheritance. honestly, it’s much simpler compared to C#. In C#, we can’t inherit from multiple classes (the compiler just stops us). But in Python, it works smoothly using something called MRO (Method Resolution Order). A small example of the diamond problem Python just figures out the order (D → B → C → A). C# avoids it altogether, no diamond problem, no confusion. 👉 And yes, I know we have interfaces in C#, but they don’t really solve the diamond problem, they just avoid it by not carrying implementation. Two different philosophies. Both make sense. But Python’s flexibility here felt refreshing 😊 #CSharp #Python #Developers #LearningEveryday #OOP

🤔 Python or Java for your next backend project in 2025? The debate rages on, but which one aligns with your goals—rapid prototyping with Python's simplicity or Java's rock-solid enterprise scalability? In our latest blog, we break it down: From syntax showdowns (Python's 3 lines vs. Java's 10) and performance edges (Java's JIT speed for high-traffic apps) to real-world wins like Netflix's AI magic with Python and LinkedIn's billion-user backbone in Java. Discover strengths, drawbacks, use cases, and when to pick each to future-proof your tech stack. Dive in: https://lnkd.in/dcqu87jS Python fan or Java loyalist? Drop your pick and why below! 👇 #PythonVsJava #BackendDevelopment #ProgrammingLanguages #TechTrends #SoftwareEngineering

Why are so many new Python libraries secretly written in Rust? Because Rust gives developers speed without sacrificing safety. For years, high performance Python libraries were written in C or C++. They were fast but hard to maintain and easy to break. One memory leak or pointer bug could crash everything. Rust changed that. It offers: • Memory safety without a garbage collector • C level performance (or even better in many cases) • Seamless integration with Python through tools like PyO3 and maturin • Safer concurrency and fewer runtime crashes That is why libraries like Polars, orjson, and Ruff are built on Rust. They are faster, safer, and easier to maintain while keeping Python’s friendly interface. Is Rust quietly becoming the new C for Python? If you have used any Rust powered Python library, I would love to hear your experience.

The new PyEditor brings #Python to #Java. It embeds the modern GraalPython runtime and exposes a pythonic wrapper of the #ESA_SNAP Java API called SnapKit. This lets you build graphs, read/write products, compute new bands, and even interact with SNAP views from Python. #EarthObservation Check out the SnapKit API: https://buff.ly/1VLvobC

In today’s class, I learned about different programming types and the differences between Strongly & Weakly Typed and Statically & Dynamically Typed languages....And now I’m explaining what I understood from it. • Strongly Typed: Languages that don’t allow type conversions(e.g., Python, Java). • Weakly Typed: Languages that allow type conversions easily(Automatically allow)(e.g., C). • Statically Typed: Type checking happens during compile time (e.g., C, C++, Java). • Dynamically Typed: Type checking happens at runtime (e.g., Python, Ruby) ✨ Why C is both Statically and Weakly Typed: C is statically typed because every variable’s type is known and checked at compile time. But it’s also weakly typed since it allows implicit conversions between data types — like converting a float to an int automatically Just like C, other languages also have their own type systems combining these properties in different ways. For example, Java is strongly and statically typed, while Python is strongly and dynamically typed. #CLanguage #Programming #CodingJourney #ComputerScience #Developers

Day 16 – Find the Second Largest Element in an Array (Java & Python) > 💡 Problem: Given an array of integers, find the second largest element. Example: Input → [10, 25, 3, 99, 56, 77] Output → 77 Approach – Single Pass (Optimized O(n)): Initialize two variables:   first = second = -∞ Traverse the array:   If current > first → update second = first, then first = current.   Else if current > second and current != first → update second = current. One traversal, no sorting needed! Your Turn: Can you modify this to find both smallest and second smallest elements? Drop your version below 👇 #CodeWithTanseer #DSA #Java #Python #CodingChallenge #ProblemSolving #Arrays #Optimization #SoftwareEngineer #BackendDeveloper #InterviewPrep

Python is complicated if someone is coming from other programming languages such as C++, Java or JavaScript. It takes time to get familiar with the syntax. Yes the person knows the fundamental concepts of programming but implementing them in python then that becomes a headache. Python syntax is oversimplified making it easier for beginners but complicated for someone who already writes code in other languages. I think python is easier to learn the fundamentals for someone who is learning it as their first language. But it will be sad knowing that they will not relate to the popular semicolon humor.😂 Imagine coming from C++ to python, where a semicolon is a syntax error😂😂 #Django #Python