Python OOPS Revision: Instance Methods & More

🐍 90 Days of Python – Day 13 Today, I learned about file handling in Python, which allows programs to read data from files and write data back to them. File handling is important because most real-world applications need to store, retrieve, and process data beyond just memory. Key concepts I explored today: • Opening files using different modes (read, write, append) • Reading data from text files • Writing and appending content to files • Understanding why closing files properly matters File handling helps bridge the gap between programs and persistent data storage. I’m practicing these basics to better understand how Python interacts with files in practical scenarios. 📌 Day 13 completed. Learning how programs work with data stored in files. 👉 Where do you think file handling is most useful in real-world applications? #90DaysOfPython #PythonLearning #LearningInPublic #ProgrammingBasics #BTechCSE #MachineLearning

Most Python programs fail not because the logic is wrong, but because the code is not prepared for unexpected situations. Users give wrong inputs. Files go missing. APIs fail. Systems behave unpredictably. If your code crashes in these scenarios, that is not bad luck. That is missing exception handling. Exception Handling is what separates code that works in notebooks from code that survives in real-world applications. It helps you write programs that are stable, readable, and production-ready, rather than fragile scripts that break at runtime. 🎯 That’s exactly what the new video covers. I have just launched a new video under my Python Programming playlist, where I explain Exception Handling in Python in depth. We go beyond syntax and focus on:  ✅Why exceptions exist and how Python handles them  ✅How try, except, else, and finally actually work  ✅Common mistakes learners make Practical, real-world examples you will face in projects and interviews If you are learning Python seriously or aiming to write professional-grade code, this is a topic you cannot skip. 📌 Watch the video here: https://lnkd.in/gxBUcce6 Be intentional about the fundamentals. Strong basics always compound faster. #PythonProgramming #ExceptionHandling #LearnPython #CodingFundamentals #SoftwareEngineering #YouTubeLaunch

🚀 Day 46 of My Python Learning Journey 🐍 Today, I learned Operator Overloading in Python, an important Object-Oriented Programming (OOP) concept. 🔹 Understood how Python uses magic (dunder) methods like: __add__(), __len__(), __eq__(), __gt__() 🔹 Learned how operators such as + and len() can be customized for user-defined classes 🔹 Practiced real-world examples: Adding two objects using __add__() Finding object length using __len__() Merging objects (ShoppingCart example) 💡 Key takeaway: Operator overloading helps write clean, readable, and object-oriented code, and it’s a favorite interview topic. 📈 Slowly building strong Python OOP foundations, one concept at a time! #Python #OOP #OperatorOverloading #MagicMethods #PythonLearning #DataAnalystJourney #CodingPractice #Day46

Most Python developers know dictionaries. Few actually use them effectively. When I started learning Python, I used dictionaries only for basic key-value storage. But real productivity came when I understood dictionary methods properly. These 12 Python dictionary methods are not “advanced”, they’re essential for writing clean, fast, interview-ready code. What you’ll find inside this infographic: • Safe key access without errors • Faster lookups & clean checks • Simple ways to merge, remove, and inspect data • Tools you’ll use in real projects, not just tutorials Mastering small methods will help so much in solving problems. If you’re learning Python or using it daily: - Save this - Revisit it - Apply 1–2 methods in your next script Which dictionary method do you use the most? #Python #PythonProgramming #Programming #Coding #LearnPython #BackendDevelopment #SoftwareDeveloper #DeveloperCommunity

Today I discovered that Python functions come in 5 different types 🐍 A function is a named block of code that performs a specific task. You can think of it as a mini-program inside your main program that helps keep code clean, reusable, and organized. Here are the 5 types: 1️⃣ Built-in Functions – print(), len(), abs(), range() 2️⃣ User-Defined Functions – created using the "def" keyword 3️⃣ Lambda Functions – small anonymous functions using "lambda" 4️⃣ Recursive Functions – functions that call themselves 5️⃣ Higher-Order Functions – functions that take other functions as input or return them (e.g., map(), filter(), reduce()) Still learning step by step, but understanding these basics makes Python feel much more powerful 💪 What was the first Python concept that confused you when you started? #Python #DataScience #LearningInPublic #Programming #100DaysOfCode #CareerSwitch

Today’s Python focus was 𝗠𝗼𝗱𝘂𝗹𝗲𝘀. I worked on understanding how Python lets you organize code into reusable files instead of writing everything in one script. 𝗪𝗵𝗮𝘁 𝗜 𝗽𝗿𝗮𝗰𝘁𝗶𝗰𝗲𝗱 𝘁𝗼𝗱𝗮𝘆: • Importing built in modules like math and calendar • Using functions from the math module such as sqrt() and ceil() • Working with the calendar module to generate month level calendars • Creating a custom module to store reusable functions • Importing and using functions from a user defined module • Separating logic into different files for better structure and readability 𝗞𝗲𝘆 𝘁𝗮𝗸𝗲𝗮𝘄𝗮𝘆𝘀: • Modules help break large programs into smaller, manageable pieces • Built in modules save time and prevent rewriting common logic • Custom modules make code reusable across multiple scripts • Organizing functions into modules improves maintainability Working with modules made it clear how real Python projects are structured. Code is written once, organized properly, and reused when needed. If you are learning Python, are you already using modules in your practice or still keeping everything in a single file? #Python #PythonLearning #PythonModules #ProgrammingBasics #LearningInPublic #DataAnalytics #Upskilling

Today’s Learning: File Handling in Python Today, I explored File Handling in Python, focusing on how programs interact with external files to store, read, and manage data efficiently. Key concepts covered: Understanding file handling and its real-world use cases File modes: r, w, a, x, r+, w+, a+ Reading data using read(), readline(), and readlines() Writing and appending content to files Best practices like closing files and using the with statement Hands-on practice helped me understand how persistent data storage works beyond variables and memory, which is a crucial concept for backend development and automation. GitHub repository for today’s practice: https://lnkd.in/gsdbxrzZ Consistent learning and daily practice continue to strengthen my Python fundamentals. #Python #PythonLearning #FileHandling #BackendDevelopment #ProgrammingBasics #CodingPractice #SoftwareDevelopment #DeveloperJourney #LearningEveryday #Consistency #CareerGrowth #TechSkills #GitHubProjects #ProblemSolving

👋 Welcome back! 📅 Python Learning – Day 22 (Python date and time) Today is about handling something every program deals with 22nd date and time. From logging events to tracking deadlines and showing timestamps, working with dates is a common real-world requirement. Python’s `datetime` module helps you work with dates and times in a clear and structured way. 📘 In this lesson, I’ve explained: 📆 How Python represents dates and times 🕰️ Creating, formatting, and comparing `datetime` values ⚠️ Common beginner mistakes with date formats and calculations Date and time bugs are often subtle and easy to miss. Once you understand `datetime`, your programs become more reliable and predictable. 🔗 Tutorial link is in the comments. ⏭️ Tomorrow: Day 23 — Python time #PythonDatetime #WorkingWithDates #LearnPythonDaily #ProgrammingSkills #PythonForBeginners #RealWorldPython #TechStudents #CodingConcepts #TimeAndDate #codepractice

Day 39 of Learning Python 🐍 | Exception Handling (Advanced) Today I explored Custom Exception Handling in Python 🔥 🔹 Created user-defined exceptions by inheriting from Exception 🔹 Understood how to raise exceptions using raise 🔹 Used try–except blocks to handle validation logic cleanly 🔹 Applied real-world logic (Age validation using DOB) 💡 Key Learning: Custom exceptions make code more readable, meaningful, and professional, especially in real-world applications where generic errors are not enough. Example use case: ✔ Input validation ✔ Business rule enforcement ✔ Clean error handling 📌 Python isn’t just about writing code — it’s about writing robust & reliable code