Niaz Chowdhury, PhD’s Post

💡 Why does Python sometimes say “variable not defined”? Because variables have boundaries — and Python strictly follows them. Let’s talk about Variable Scope in Python 🐍 🔍 What is Variable Scope? It defines where a variable lives and who can access it. Think of it like Wi-Fi 📶 👉 Some signals are available everywhere 👉 Some work only inside a room z = 5 def change(): global z z *= 2 change() print(z) #Python #LearningPython #Programming #Coding #PythonTips #LinkedInLearning #Developer 🚀

Today I learned about Lambda Functions in Python 🐍 A lambda function is a small, anonymous function written in a single line using the lambda keyword. It’s mainly used for: ✅ Short and simple operations ✅ Writing compact code ✅ Using inside functions like map(), filter(), and sorted() Example idea: Instead of writing a full function to square a number, we can do it in one line with a lambda function. Less code. Same logic. Cleaner style. Understanding these small tools really helps in writing more Pythonic and efficient code. Learning one concept every day 🚀 #Python #DataScience #LearningInPublic #Programming #100DaysOfCode #CareerSwitch

Day 15 of Python on HackerRank 🐍 Today’s learning was all about itertools.product() — a powerful tool to compute the Cartesian product of iterables. ✨ Key takeaway: itertools.product() helps generate all possible combinations between two or more lists, making nested loops cleaner, faster, and more readable. 📌 What I learned: How Cartesian products work Replacing complex nested loops with elegant Python code Writing concise and efficient solutions using built-in modules Consistency over perfection. One day, one concept, steady progress 💪 #Day15 #Python #HackerRank #itertools #LearningInPublic #CodingJourney

🚀 Day 9 – Python Functions and Recursion 🐍 Today I explored Python Functions and Recursion, focusing on how real problems can be solved step by step. For example: 🔹 Using a function to avoid repeating the same logic again and again 🔹 Using recursion to break a problem into smaller versions of itself—until a base case is reached Seeing how a function can call itself made the logic behind problems like factorials and number series much clearer. It’s not just about writing code anymore, it’s about thinking logically and structuring solutions. 📌 Consistency over speed. Learning with practice. #Python #Day9 #Functions #Recursion

Understanding Strings & Immutability As I continue building my Python fundamentals, I have been learning how strings work and why they are immutable in Python. - Strings are sequences of characters enclosed in single or double quotes both work the same in Python. - Learned how to create multi-line strings, handle quotes inside strings, and check for characters using the in operator. - Explored string length using len() and accessed characters through indexing (including negative indexing). - An important concept: strings are immutable, meaning individual characters cannot be changed once a string is created only reassigned. Understanding string behaviour is essential when cleaning, validating, and analyzing text-based data. #PythonBasics #StringsInPython #Immutability #DataAnalyticsJourney #LearningInPublic #Upskilling

How Python Manages Memory: Mutable vs Immutable One concept that silently affects performance, bugs, and behavior in Python is mutability. Immutable objects 👉 int, float, str, tuple Their value cannot be changed in place Any “modification” creates a new object in memory Safer, predictable, hashable (used as dict keys) Mutable objects 👉 list, dict, set Can be modified without changing memory reference Faster updates, but risk of unexpected side effects Changes reflect across all references Why this matters in real projects - Unexpected bugs when modifying lists passed to functions - Memory inefficiency when repeatedly modifying strings - Confusing behavior in function arguments & shared data #Python #MemoryManagement #Mutable #Immutable #PythonInternals #SoftwareEngineering

Do you really understand how Python iteration works? Not just how to use for loops — but what actually happens when Python reads a file, processes a stream, or runs an infinite sequence? I just published a deep dive on Python Iterators & Generators that explains: - the iterator protocol - yield vs return - lazy evaluation - yield from - and why generators power files, pipelines, and async foundations If you want to understand how Python moves data through time, this article is for you. Read here: https://lnkd.in/gyvqZXxh I would really appreciate if you leave a comment or share it with your network! #Python #Programming #SoftwareEngineering

🌙 Day 14/100 | #100DaysOfCode 🚀 Continuing my Python learning journey — one concept at a time 🐍💻 📌 Today’s Topic: Type of Conversion in Python Today I learned how Python converts one data type into another, which is super helpful while working with user input and calculations. 🔹 Implicit Conversion Python automatically converts one data type to another. Example: int → float during calculations. 🔹 Explicit Conversion (Type Casting) We manually convert data types using functions like: int(), float(), str(), list() etc. This helped me understand how to avoid errors and handle data properly in real programs. Slow progress, but strong foundation 💪 Learning daily and trusting the process ✨ 👉 Tomorrow again, with a new concept! #Python #LearningPython #CodingJourney #DeveloperInMaking #Consistency #DailyLearning #TechSkills #FromBasicsToAdvanced

Day 19: Top Learning 🧠 | Built-in Functions in Python Built-in functions are Python’s superpower ⚡ Instead of writing long logic, Python gives ready-made tools to work faster, cleaner, and smarter. From string methods like lower(), strip(), replace() to list functions like append(), sort(), len() and number functions like round(), abs(), sum() - 👉 This is how real Data Analysts save time and write efficient code. Less code. More clarity. Better analysis. 🚀 Python is becoming more practical and powerful. Satish Dhawale SkillCourse #Python #DataAnalytics #LearningJourney #BuiltInFunctions

🐍 Day 30 — Common Python Errors Day 30 of #python365ai 🐞 Some errors you’ll see often: SyntaxError NameError TypeError ValueError Example: print(x) # NameError if x is not defined 📌 Why this matters: Understanding error messages saves hours of debugging. 📘 Practice task: Intentionally create a small error and read Python’s message carefully. #python365ai #Debugging #PythonErrors #LearnCoding