Boost Python Code Speed with functools.lru_cache

A circular reference happens when two or more objects reference each to other. For example: list A contains a reference to list B and B contains ref back to list A. This creates a cycle. The problem is that Python mainly uses reference counting to delete Objects. An object is removed only when it's reference count becomes 0. In a circular reference, each object still has at least one reference form the other, so their reference count never reaches 0, and they are automatically deleted. This can cause memory to stay used longer than needed. How can python delete this circular reference ? the solution is Python's Garbage collector (GC). It can delect groups of objects that are no longer reachable from the program, even if they reference each other, and it removes them to free memory very simple example : import GC a = [] b = [] a.append(b) b.append(a) del a del b GC.collect() #python #garbageCollector #(GC) #dev #deeplearning #programmation #pythonDev

Using Elif Statements for Conditional Logic The `elif` statement in Python enhances conditional logic by allowing multiple branches in decision-making processes. Using `if`, `elif`, and `else`, you can create a clear and scalable structure for controlling program flow based on varying conditions. This feature is crucial in numerous applications, from simple scripts to complex software. When an `if` condition is evaluated to be `True`, the associated code runs, and the entire block is finished. If that first condition is `False`, Python checks the next `elif` condition. This evaluation continues through all `elif` blocks until a `True` condition is found or it reaches the `else` block. This approach avoids deeply nested `if` statements, thus improving code readability and maintainability. In our example, we check the temperature and suggest appropriate clothing based on its value. This allows for versatile responses to user input or environmental changes, making it easier to adapt the program as conditions fluctuate. Understanding how to use `elif` effectively not only helps streamline your coding practices but also enhances your programs' interactivity and responsiveness. Quick challenge: What output would this yield if the temperature were set at 50, and why? #WhatImReadingToday #Python #PythonProgramming #ControlFlow #LearnPython #Programming

>>> import this The Zen of Python, by Tim Peters Beautiful is better than ugly. Explicit is better than implicit. Simple is better than complex. Complex is better than complicated. Flat is better than nested. Sparse is better than dense. Readability counts. Special cases aren't special enough to break the rules. Although practicality beats purity. Errors should never pass silently. Unless explicitly silenced. In the face of ambiguity, refuse the temptation to guess. There should be one-- and preferably only one --obvious way to do it. Although that way may not be obvious at first unless you're Dutch. Now is better than never. Although never is often better than *right* now. If the implementation is hard to explain, it's a bad idea. If the implementation is easy to explain, it may be a good idea. Namespaces are one honking great idea -- let's do more of those! . . The Zen of Python is a: Listing of Python design principles and philosophies that are helpful in understanding and using the language. The listing can be found by typing “import this” at the interactive prompt. (Source) . #DataScience #MachineLearning #ArtificialIntelligence #Tech #Programming #SoftwareEngineer #datos #datasets

🧠 Python Concept That Helps Memory Management: weakref Sometimes… you want to reference an object without owning it 🧠💡 🤔 What Is weakref? A weak reference lets you point to an object without preventing it from being garbage collected. In short: 💻 Normal reference → keeps object alive 💻 Weak reference → lets Python delete it when unused 🧪 Example import weakref class User: pass u = User() r = weakref.ref(u) print(r()) # <__main__.User object> del u print(r()) # None 👀 The object is gone when nothing else needs it. 🧒 Simple Explanation Imagine borrowing a toy 🧸 💫 A normal reference = you keep the toy forever 💫 A weak reference = you only remember the toy 💫 If the owner takes it back, your memory disappears too. 💡 Why This Is Useful ✔ Prevents memory leaks ✔ Used in caches & observers ✔ Helps large applications ✔ Advanced Python concept ⚠️ When to Use 🖱️ Caching systems 🖱️ Event listeners 🖱️ Circular references 🖱️ Long-running apps 🐍 Python doesn’t just manage memory for you… 🐍 It gives you tools to manage it intelligently 🐍 weakref is one of those tools you don’t need every day — until you really do. #Python #PythonTips #PythonTricks #Weakref #AdvancedPython #CleanCode #LearnPython #Programming #DeveloperLife #DailyCoding #100DaysOfCode

I’ll admit it: early in my Python journey, I spent hours debugging code that looked fine. Functions returning the wrong value, variables mysteriously “disappearing,” and weird side effects… all because I didn’t fully understand Python variable scope. Once I got it, my code became cleaner, easier to debug, and way more predictable. I turned that hard-earned lesson into a short, practical guide that walks you through local, global, and nonlocal variables with real examples. 👉 Check it out here: https://lnkd.in/djp6HJdD If you’re serious about improving your Python fundamentals, this guide is a simple way to save hours of frustration. #Python #LearnPython #CodingTips

🐍 Ever wondered what REALLY happens when you run a Python program? You type: 👉 python app.py But behind the scenes… a LOT is happening 👀 🔹 1. Python Interpreter Starts Python launches the interpreter (CPython for most of us). It reads your file line by line. 🔹 2. Code → Bytecode Your Python code is converted into **bytecode** (.pyc files). 👉 This makes execution faster next time. 🔹 3. Python Virtual Machine (PVM) The bytecode runs inside the PVM. This is where loops, conditions, functions actually execute. 🔹 4. Memory Management Python automatically: ✔ allocates memory ✔ tracks object references ✔ clears unused objects (Garbage Collection ♻️) 🔹 5. C Under the Hood Most Python operations are powered by **C code** That’s why Python feels simple but still powerful 💪 ✨ That’s the magic: Simple syntax on the surface, serious engineering underneath. 💡 Knowing this helps you: • Write faster code • Debug better • Understand performance issues #Python #BackendDevelopment #SoftwareEngineering #Programming #LearnPython #TechSimplified

⚠️ Python Gotcha: Defining the Same Method Twice in a Class Did you know that Python does NOT support method overloading by definition order inside a class? Consider this scenario 👇 You define the same method name twice inside a class, expecting both to exist… Only the LAST definition survives. What actually happens? Python reads the class top to bottom When it sees the second func1, it completely overwrites the first one The first method is lost and ignored No warning. No error. Just replacement. Example outcome Nirmal.func1(2, 4) Runs the second version only Output: Good Morning Result is: 6 🚨 Key Takeaways Python does not support traditional method overloading Method names inside a class must be unique If you need different behaviors: Use different method names Or use default parameters / *args / conditional logic 🧠 Pro Tip If your logic seems to “mysteriously change” — check whether a method name was accidentally redefined. Learning these small details makes a big difference in writing clean, predictable Python code 🐍 #Python #OOP #ProgrammingTips #LearningPython #Developers #CodeSmart

🧠 Python Feature That Makes Attribute Access Clean: operator.attrgetter Think of it as itemgetter for objects 👌 ❌ Common Way users.sort(key=lambda u: u.age) Works… but gets noisy in big codebases 😬 ✅ Pythonic Way from operator import attrgetter users.sort(key=attrgetter("age")) Cleaner. Faster. More readable ✨ 🧒 Simple Explanation Imagine pointing at a toy 🧸 👉 “Sort by age, not the whole toy.” That’s attrgetter. 💡 Why This Is Useful ✔ Cleaner sorting ✔ Faster than lambda ✔ Reads like English ✔ Used in real-world code ⚡ Bonus Trick Get multiple attributes: attrgetter("age", "name")(user) 🐍 Python has tools that remove noise from code. 🐍 attrgetter is one of those features you don’t notice at first… 🐍 until you can’t live without it #Python #PythonTips #PythonTricks #AdvancedPython #CleanCode #LearnPython #Programming #DeveloperLife #DailyCoding #100DaysOfCode

The only Python tool you need in 2026? 🐍 The Python ecosystem has been fragmented for years. We used pyenv for versions, venv for isolation, pip for packages, and pip-tools for locking. uv changes everything. Here is your quick command guide: 📦 Start a project: uv init ➕ Add a library: uv add requests 🏃 Run a script: uv run main.py 🐍 Install Python 3.13: uv python install 3.13 🛠 Run a tool (like Ruff): uvx ruff check It’s a drop-in replacement for pip, so you can even use uv pip install -r requirements.txt for an immediate speed boost. The Verdict: If you value your time, uv is a non-negotiable upgrade to your workflow. #PythonProgramming #CodingTips #DevOps #BackendDevelopment #uvPython

I recently contributed to keon/algorithms, one of the most popular algorithm repositories on GitHub that helps developers worldwide learn data structures and algorithms through clean Python implementations. 🔍 My Contribution I implemented a Generalized Binary Search algorithm that works over a numeric range using a monotonic boolean predicate, instead of searching for a fixed value in an array. 💡 Why this enhancement matters: • Flexible Input – Operates on a range [low, high] with a predicate function f(x) • Smart Output – Finds the smallest value x where f(x) becomes True • Optimal Performance – O(log N) time, O(1) space • Broader Applications – Ideal for optimization problems, boundary detection, and non-array search spaces • Backward Compatible – Existing implementations remain untouched This abstraction makes binary search far more powerful and reusable, enabling real-world problem solving beyond traditional array searches. 🔗 Repository: https://lnkd.in/daS_m-dM #OpenSource #GitHub #Algorithms #BinarySearch #Python #DataStructures #SoftwareEngineering #Coding #TechCommunity #OpenSourceContribution