Arosys Technologies (P) Ltd’s Post

🚀 Quick Experiment: Comparing Lines of Code Across Languages I recently did a small personal experiment to compare how many lines of code (LOC) are typically required to implement the same task in Python, Java, and C++. 📌 Assumption: Each new statement appears on its own line — no one-liners or compressed logic. Here are the results: 🐍 Python: 11 LOC ☕ Java: 36 LOC 💻 C++: 44 LOC Key Takeaways Python is very concise for implementing tasks. Java requires more structure and verbosity. C++ is the most verbose among the three. 💡 Note: This experiment considers Lines of Code only, not execution speed or efficiency. I’d love to hear your thoughts: Do you value code compactness over verbosity for readability and maintenance? Hashtags #Programming #Python #Java #CPlusPlus #CodeEfficiency #SoftwareDevelopment #CodingExperiment #DeveloperInsights #TechLearning #ProgrammingTips

⚡ 1 billion nested loop iterations — language speed test ⚡ Some take milliseconds (C, Rust, Java, Go)… Others take coffee break levels of time ☕🐢 (Python, R). It’s a great reminder: ✅ Choose the right tool for the job ✅ Performance matters for heavy computation ✅ But developer productivity matters too #Programming #Performance #Benchmarks #SoftwareEngineering #Developers #RustLang #GoLang #Java #Kotlin #Python #NodeJS

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.

🔥 Day 6 of 75 Days of Knowledge Theme: Operators & Expressions — Java | Python | JavaScript Operators are the tools that make logic work. They help us calculate, compare, and make decisions in code. Today’s focus was on mastering expressions — how data combines and transforms using operators. 💡 Concepts Covered Arithmetic, Comparison & Logical Operators Assignment & Bitwise Operators Operator Precedence Expressions & Evaluation 📚 Learn Operators in Each Language 📘 Python – Operators Made Simple 👉 https://lnkd.in/g9MTvK3F 👉 https://lnkd.in/gVgBrR4s 📗 Java – Operator Types & Precedence 👉 https://lnkd.in/gMJcCe9z 👉 https://lnkd.in/gBefza2s 📙 JavaScript – Expressions & Operators 👉 https://lnkd.in/gHjTpPk9 👉 https://lnkd.in/gjnhepYH 🧮 Mini Practice Ideas ✅ Try building a simple calculator ✅ Compare user inputs with logical operators ✅ Experiment with precedence using parentheses 💡 Practice online: https://replit.com/~ 💬 Reflection: Understanding operators builds the logic engine inside your brain 🧠 Every condition, loop, and algorithm you write relies on mastering these small but powerful symbols. #75DaysOfKnowledge #ProgrammingBasics #Operators #Expressions #Java #Python #JavaScript #LeetCode #CodingJourney #LearnToCode

From Python to C++: Building a Compiler for Performance and Parallelism Xavier Thompson from Nexedi shared a fascinating deep dive into how his team built a Python → C++ compiler, called Typon, designed to unlock true concurrency and performance - without abandoning Python’s simplicity. Python’s flexibility comes with trade-offs - the Global Interpreter Lock (GIL) and interpreter overhead often limit scalability for CPU-bound workloads. Nexedi, whose open-source ERP5 system generates over a million invoices per month, needed a way to scale further without rewriting everything in another language. Enter Typon: A subset of Python that compiles directly to C++, Typon offers: - Built-in concurrency primitives (fork and sync) for structured parallelism. - Automatic memory management and Python-like semantics. - Interoperability with Python libraries (e.g., NumPy) while avoiding GIL constraints. - Native performance through C++ compilation and async I/O handling. Xavier also shared how Typon’s scheduler enables massive parallelism - turning a simple Python web server into one capable of handling tens of thousands of concurrent connections. Under the hood: - The compiler is written in Python itself, leveraging the built-in ast module. - It performs type inference, supports generics, and generates C++ code that mimics Python’s object model. - The team is now building a Typon standard library, with C++ bindings and Python stubs for seamless integration. Typon is now available on PyPI - an exciting milestone for open-source compiler innovation. Learn more or try it out: https://lnkd.in/e9zgeTmt #Python #Cplusplus #CompilerDesign #OpenSource #PerformanceEngineering #Concurrency #ParallelComputing #EuroPython #MLOps #SoftwareEngineering

Introducing NumPy4J 1.0.0 — the first official release! After quite some long hours of development, I’ve officially released NumPy4J 1.0.0, a Java library inspired by Python’s NumPy. NumPy4J brings the power and flexibility of Python’s NumPy to the Java ecosystem, delivering ndarray support, broadcasting, slicing, arithmetic operations, and reshaping for high-performance numerical computing in pure Java. This release includes: - Core ndarray implementation - Element-wise and matrix operations - Broadcasting and slicing - Source and Javadoc bundles, all GPG-signed Available now on Maven Central: https://lnkd.in/eJ_jfkDq This project started from curiosity: Can Java have a NumPy-like ecosystem? Feedback and contributors are welcome as the goal is to make scientific Java code simpler and faster. More NumPy functionality will be migrated in coming versions. Check it out on GitHub: https://lnkd.in/eC4r3dBt Full documentation: https://lnkd.in/eA6Qnt8Z #Java #MachineLearning #OpenSource #NumPy4J #AI

The November TIOBE Index brings one of the biggest shifts in years. Python remains on top, but the spotlight has moved to the tightening battle between Java and C#. For the first time, C# is outpacing Java’s growth, powered by Microsoft’s momentum, modern language features, and cross-platform reach. Java still dominates enterprise systems, yet its long-held advantage is slipping fast. With less than 1% between the two, we may be witnessing a historic change in the rankings - one that could redefine the programming landscape in 2025. #ProgrammingTrends #SoftwareDevelopment #Python #CSharp #Java #TechIndustry #DevelopersCommunity #Innovation #Technology

🔥 My last post on why every Java Full Stack Developer should learn Python turned into a full-blown debate. Suddenly it was Java vs Python vs Go vs Rust everywhere! And honestly, I loved it. 💬 Because these debates aren’t about who’s right, they’re about how we think, build, and innovate. Keep debating, keep building, keep learning. That’s how we grow. 💡 So here’s the real question which one will truly dominate the next decade of backend innovation? Java’s reliability or Go’s simplicity or Python’s intelligence or Rust's speed or a powerful mix of them 👀 #Java #Python #GoLang #Rust #JavaFullStackDeveloper #SoftwareEngineering #USJobs #RemoteC2C #C2CJobs

📊 TypeScript has officially overtaken Python in popularity among developers this year. The growth of TypeScript continues as more teams adopt it for scalability and reliability in large projects. Source - https://lnkd.in/g6syMgJW

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