Reading and Writing Files in Programming

Humbled to share, seeking wishes and blessings 🙏 My book "Python - Powered Excel" is now released! This book offers a practical guide to Excel (not necessarily 365) and Python users to automate tedious tasks, analyze data, and create dynamic reports. Whether you are a data professional versed in Python or a seasoned Excel user, this book will arm you with tools to harness Python's potential and Excel’s convenience. Combining the strengths of both Python and Excel will allow you to build scalable workflows that are accessible to everyone, whether you start in Excel or Python. Book Link in comments! #Excel_python #Data #Book

Copyright This document has been placed in the public domain. Typeshed repo https://lnkd.in/dpbtuzFs https://lnkd.in/dERgaqgj Donald Knuth's The TeXBook, pages 195 and 196. Hanging indentation is a type-setting style where all the lines in a paragraph are indented except the first line. In the context of Python, the term is used to describe a style where the opening parenthesis of a parenthesized statement is the last non-whitespace character of the line, with subsequent lines being indented until the closing parenthesis. Barry's GNU Mailman style guide https://lnkd.in/ddXsQvSs PEP: 8 Title: Style Guide for Python Code Author: Guido van Rossum <gu ido@python.org>, Barry Warsaw <barry@python.org>, Alyssa Coghlan <nc oghlan@gmail.com> Status: Active Type: Process Created: 05-Jul-2001 Post- History: 05-Jul-2001, 01-Aug-2013

Thinking in Blueprints (Classes & Constructors) Focus: Introduction to OOP and the __init__ method. Day 9(06-04-2026): Today, my perspective on coding shifted. I moved away from just writing "steps" and started thinking in Objects. In Python, everything can be modeled after the real world using Classes. The big breakthrough today: Classes vs. Objects: A Class is the blueprint (like a drawing of a car), and the Object is the actual thing (the car you can drive). The Constructor (__init__): I learned how to use the "dunder init" method to give my objects their initial data the moment they are created. The self Keyword It’s a bit more abstract than what I’ve done before, but it makes the code so much more organized and powerful. #OOP #PythonProgramming #Day9 #ObjectOriented #CodingConcepts

🧠 Python Concept: __all__ (Controlling Imports) Control what your module exposes 😎 ❌ Without __all__ # mymodule.py def public_func(): pass def _private_func(): pass from mymodule import * 👉 Imports everything 👉 Even internal functions ✅ With __all__ # mymodule.py __all__ = ["public_func"] def public_func(): pass def _private_func(): pass from mymodule import * 👉 Only public_func is imported 🧒 Simple Explanation Think of __all__ like a filter 🚫 ➡️ Controls what others can access ➡️ Hides internal stuff ➡️ Keeps code clean 💡 Why This Matters ✔ Better module design ✔ Cleaner APIs ✔ Avoids accidental usage ✔ Professional coding practice ⚡ Real-World Use ✨ Library development ✨ Package design ✨ Large codebases 🐍 Don’t expose everything 🐍 Control your module interface #Python #AdvancedPython #CleanCode #BackendDevelopment #SoftwareEngineering #Programming #DeveloperLife

I used to think Object-Oriented Programming (OOP) was overcomplicating things. I was wrong. 🛑 For a long time, I stuck to simple scripts. But as my projects grew, I realized that writing functional code is one thing—writing scalable code is another. Today, I sat down to master the Class structure in Python, and it finally clicked. By building this Animal class, I realized why OOP is a game-changer: ✅ Reusability: I can create 100 different objects without rewriting the logic. ✅ Organization: Data (attributes) and actions (methods) live together in one neat package. ✅ Readability: Anyone can look at dog.speak() and know exactly what is happening. It’s a simple script, but it’s a foundational step toward building more complex software. Small wins lead to big builds! 🚀 Question for the devs: What was the hardest part of OOP for you to wrap your head around when you first started? For me, it was definitely understanding self! 👇 Zakir Hussain #Python #SoftwareEngineering #CodingJourney #BuildInPublic #Programming #OOP #LearningToCode #PythonProgramming

Week 3 of #100DaysOfCode — done! 🎉 This week I started thinking in objects. Topics covered: 🧱 Classes & Objects → What OOP actually is (and why it matters) → Classes, instances, attributes, methods → public, _protected, and __private attributes → __init__, self, and how Python works under the hood 🔒 Properties → @property — the Pythonic way to write getters & setters → No more get_age() / set_age() — just person.age ✅ ⚙️ More Classes → __str__ vs __repr__ — and why both matter → Class attributes vs instance attributes → @classmethod and @staticmethod → __dict__, getattr, dynamic attributes I’ve structured my learning into notes and practical examples to better understand the concepts : https://lnkd.in/epaBymnJ 21 days down. 79 to go. 💻 #100DaysOfCode #Python #LearningInPublic #Programming

I built my first real Python project today. 🐍 A fully functional Contact Book — runs in the terminal, no frameworks, no tutorials to copy from. What it does: → ➕ Add multiple contacts at once → 📋 View all saved contacts → ❌ Delete contacts by number → 🔁 Keeps running until you choose to exit What I used to build it: → Dictionary — to store name + phone pairs → While loop — to keep the app running → Functions — to avoid repeating code → Enumerate — to number contacts cleanly 3 weeks ago I didn't know what a dictionary was. Today I built an app with one. That's what consistent learning looks like. 💪 #Python #LearningInPublic #DataAnalytics #PythonProject #BBA #buildinpublic

🚀 Python Mini Project: Matrix Operations Tool (NumPy) I built a Matrix Operations Tool using Python and NumPy that performs essential matrix computations efficiently. This project focuses on simplifying mathematical operations on matrices while ensuring accuracy and performance using optimized NumPy functions. It is designed to handle different matrix sizes and provide reliable results through proper input validation. 🔧 Key Features :- • Matrix Addition, Subtraction, and Multiplication • Transpose of a Matrix • Determinant Calculation • Handles multiple matrix sizes • Input validation to prevent runtime errors 💻 Tech Used :- • Python • NumPy This project helped me strengthen my understanding of linear algebra concepts and improved my ability to work with numerical data efficiently. It also gave me practical experience in writing optimized and clean code using NumPy instead of manual implementations. 🔗 GitHub Repository :- https://lnkd.in/g2mT5Zj2 I am continuously working on improving my skills and building projects that solve real-world problems. Feedback and suggestions are always welcome. #Python #NumPy #Projects #SoftwareDevelopment #BackendDeveloper #CodingJourney #OpenToWork

🐍 Which Python package manager should you actually use in 2025? I just published a deep-dive guide covering everything from the classics to the tools reshaping the ecosystem right now: → pip, pipenv, Poetry, conda, and the blazing-fast uv → Python version managers: pyenv, asdf, and why uv is doing it all → A decision flowchart so you never have to Google this again → Migration paths between tools → Where Python packaging is headed next Whether you're a solo dev tired of dependency hell or a team lead trying to standardize your stack — this one's for you. 🔗 https://lnkd.in/gd43kMfp Would love to hear what your team is using these days. Still on pip? Already moved to uv? Drop it in the comments 👇 #Python #SoftwareDevelopment #DevTools #Programming #OpenSource

Built something small but meaningful: 👉 https://lnkd.in/gSMyZXF8 py-in-bloom is my way of learning Python fundamentals properly — not just syntax, but thinking clearly through problems. My code here might not look “beginner-level.” That’s intentional — I’m new to Python, not new to programming. I’m focusing on writing structured, predictable, and well-thought-out solutions from the start. What’s inside: Clean implementations of core programming problems Focus on input validation, edge cases, and logic clarity Gradual progression from basic → structured problem-solving Why I made this: Most beginners (including me) write code that works, but isn’t thought through. This repo is my attempt to fix that — one problem at a time. If you're learning Python: Try solving the problems yourself first Then compare approaches Focus on why the solution works, not just the answer Feedback or better approaches are welcome.