Java vs Python: Choosing the Right Tool

Most Python developers think they understand encapsulation. They don’t, and honestly, Python intentionally breaks what most of us were taught in Java/C++. No private No protected No compiler enforcement Yet… senior engineers still build safe, maintainable, encapsulated systems in Python. The real problem isn’t “public attributes”. It’s shared mutable state, reference leaks, and uncontrolled mutation. In this article I break down: - Why _ and __ are not about privacy - How encapsulation actually fails in real Python code - Why @property, defensive copies, immutability, and __slots__ matter - The mental model seniors use: ownership > visibility If you’ve ever said “Python has weak encapsulation”, this one might change your mind. 👉 Read here: https://lnkd.in/gYnqnefQ #python #softwarearchitecture #backend #engineering

Most Python developers think they understand encapsulation. They don’t, and honestly, Python intentionally breaks what most of us were taught in Java/C++. No private No protected No compiler enforcement Yet… senior engineers still build safe, maintainable, encapsulated systems in Python. The real problem isn’t “public attributes”. It’s shared mutable state, reference leaks, and uncontrolled mutation. In this article I break down: - Why _ and __ are not about privacy - How encapsulation actually fails in real Python code - Why @property, defensive copies, immutability, and __slots__ matter - The mental model seniors use: ownership > visibility If you’ve ever said “Python has weak encapsulation”, this one might change your mind. 👉 Read here: https://lnkd.in/gTpdybv5 #python #softwarearchitecture #backend #engineering

Python Daily Tip #2 Python is dynamically typed. You don’t declare variable types explicitly. Java style: int count = 10 Kotlin (type inference, still static): val count: Int = 10 Python style: count = 10 Key difference: • Java & Kotlin → types are checked at compile time • Python → types are checked at runtime Dynamic typing adds flexibility, but errors can appear later. Use type hints to improve readability: count: int = 10 Like and comment if this helped. Follow for daily Python tips. #Python #AndroidDevelopers #Kotlin #Java #SoftwareEngineering #ProgrammingTips

Stop learning Java / Python the wrong way Stop running behind tutorials endlessly. Tutorials can show you syntax — but they can’t teach you thinking. Instead, do this 👇 ✔ Write small programs ✔ Break them on purpose ✔ Fix the errors yourself ✔ Read error messages carefully Because real learning doesn’t happen when code works. It happens when code breaks. 💡 Mistakes don’t slow you down. They build you. The moment you stop fearing errors — you start thinking like a real programmer. Are you currently learning to code? Comment YES 👇 #LearningToCode #Java #Python #ProgrammingMindset

Python Daily Tip #1 Python uses indentation to define code blocks, not braces {}. This will raise an error: if x > 0: print("Positive") This works: if x > 0: print("Positive") Why? Indentation is part of Python’s syntax, not just a formatting convention. If you’re coming from Java or Kotlin, think of indentation as mandatory braces. If this was helpful, like the post and leave a comment. Follow for daily Python tips. #Python #AndroidDevelopers #JavaDevelopers #SoftwareEngineering #ProgrammingTips

Most Java vs Python discussions stop at syntax. But syntax is only the surface outcome. What actually matters is why the language looks the way it does. This carousel is part of a longer learning thread where I’m breaking down how internal design decisions show up in day-to-day code. No “which is better”. Just understanding how things work under the hood. More deep dives coming. #LearningInPublic #Java #Python #SoftwareEngineering #ProgrammingLanguages #DeveloperJourney

Stop writing Python like Java/C++! Many Python newcomers approach list creation with loops and .append() – a familiar pattern from other languages, but not the most efficient or readable way in Python. The "Pythonic" way to think about lists is through list comprehensions. They're a concise and expressive syntax for creating lists based on existing iterables. Instead of imperative steps, you declare what you want the list to contain. Okay: squares = [] for x in range(10): squares.append(x2) Best: squares = [x2 for x in range(10)] Insight: * Conciseness: List comprehensions reduce code lines significantly. * Readability: For simple transformations, they often make intent clearer. * Performance: Generally, they are faster than for loops with .append(). Mastering list comprehensions is a key step in writing more idiomatic and effective Python code. #Python #CodingTips

CppCon, The C++ Conference 2025 Alex Dathskovsky ☕ Dathskovsky: "C++ ♥ Python" youtu.be/9uwDMg_ojdk As C++ programmers, many of us have embraced Python as our second language due to its versatility and ease of use, particularly for algorithm development (Maybe we should change the false writing of C/C++ to C++/Python because its more accurate :)). However, one major challenge we encounter is Python's inherent slowness as an interpreted language. In this talk, we propose a paradigm shift by redefining our approach as C++/Python, emphasizing the symbiotic relationship between the two languages. By leveraging various binding tools, we can significantly accelerate Python's performance and unlock its true potential. We will explore many binding tools and understand the advantages and disadvantages of each one. We will explore CPython and understand GIL pitfalls. By the end of this talk, attendees will have a comprehensive understanding of various binding tools available for accelerating Python and their respective advantages and disadvantages. Armed with this knowledge, C++ programmers will be empowered to bridge the gap between the two languages, enhance their algorithm development process, and unlock the full potential of Python. --- Alex Dathskovsky Alex has over 18 years of software development experience, working on systems, low-level generic tools and high-level applications. Alex has worked as an integration/software developer at Elbit, senior software developer at Rafael, technical leader at Axxana, Software manager at Abbott Israel and now a group manager a technical manager at Speedata.io an Exciting startup the will change Big Data and analytics as we know it .On His current Job Alex is developing a new CPU/APU system working with C++20, Massive metaprogramming and development of LLVM to create the next Big thing for Big Data. Alex is a C++ expert with a strong experience in template meta-programming. Alex also teaches a course about the new features of modern C++, trying to motivate companies to move to the latest standards.

Choosing your first programming language is a rite of passage for every developer! 🚀 Whether you prefer the rigid structure of Java or the "plain English" readability of Python, understanding these core differences is key to building your tech foundation. At Rookies World, we break down the complexities: Syntax: Java’s structured, verbose approach vs. Python’s human-readable design. Typing: Static typing in Java vs. Dynamic typing in Python. Execution: Java’s dual compiled/interpreted nature vs. Python’s purely interpreted flow. Which side are you on? Let us know in the comments! 👇 #Java #Python #Programming #TechEducation #RookiesWorld #CodingLife #SoftwareDevelopment

Single Dispatch Generic Functions in Python #programming #python #coding Stop writing massive if-else chains to check data types! There is a cleaner way built right into the Python standard library. It’s called singledispatch and it allows you to register different logic for different types (like function overloading in Java or C++). It keeps your code clean, readable, and open for extension.