Python Foundations: Functions & Error Handling

Day 17 Learning | Python Sets & Dictionaries 🚀 Today, I explored Sets in Python, focusing on their core properties, operations, and built-in functions such as: Union, Intersection, Difference, Symmetric Difference I also practiced adding, removing, and updating elements, and understand how sets help manage unique data efficiently. To apply these concepts practically, I built a small Library Management System using Sets and Dictionaries, where I worked on: Managing unique book records Efficient data handling using set operations Structuring and accessing data effectively with dictionaries This hands-on project strengthened my understanding of data structures, logic building, and real-world problem-solving in Python. 🔗 GitHub Repository: https://lnkd.in/gPTy4_Xz Consistent learning and implementation are key steps toward becoming a better developer. Looking forward to learning more and building stronger projects. #Python #PythonLearning #DataStructures #SetsInPython #DictionariesInPython #LibraryManagementSystem #HandsOnLearning #CodingPractice #LogicBuilding #SoftwareDevelopment #ProgrammingJourney #LearningByDoing #CareerGrowth #SkillDevelopment #Consistency #TechCareers #FutureDeveloper

Day 24 Learning | Python Polymorphism & OOP Concepts 🚀 Today, I explored the concept of Polymorphism in Python, another fundamental pillar of Object-Oriented Programming. I focused on how polymorphism allows the same interface or method name to behave differently based on the object or context. I studied and practiced key forms of polymorphism, including: Method Overriding Method Overloading (using default arguments) Operator Overloading Through hands-on coding examples, I understood how different classes can implement the same method name with different behaviour, enabling flexible and scalable program design. This learning strengthened my understanding of dynamic behaviour in OOP, abstraction, and designing adaptable software components in Python. 🔗 GitHub Repository: https://lnkd.in/g3CrHbUt Consistent learning and implementation are key steps toward becoming a better developer. #Python #PythonLearning #OOP #Polymorphism #HandsOnLearning #CodingPractice #ProgrammingJourney #LearningByDoing #Consistency

Just discovered "Pydantic" today and it's a game-changer! If you're building APIs in Python or dealing with data management, this library makes life so much easier. What I learned: -> Automatic data validation - no more manual checks -> Works perfectly with FastAPI -> Clean settings and config management You get validation, error handling, and type safety automatically. If you work with APIs(FastAPI) or external data, definitely check it out. Perfect Source: Chai Aur Code-Pydantic Crash Course(YouTube) #Python #Pydantic #API

Day 5 of my #100DaysOfCode challenge 🚀 Today I worked on a Python program to rotate a list by k positions. List rotation means shifting elements so that items moved out from the front reappear at the end of the list. What the program does: • Takes a list and a value k from the user • Handles edge cases like an empty list • Uses modulo (k % length) to avoid unnecessary rotations • Rotates the list efficiently using slicing How the logic works: 1) If the list is empty, it is returned as-is 2)The value of k is adjusted using modulo to handle cases where k is larger than the list size 3)The list is split into two parts: – Elements from index k to the end – Elements from the start to index k 4)Both parts are joined to form the rotated list Example 1: Original list: [1, 2, 3, 4, 5] k = 2 Output: [3, 4, 5, 1, 2] Example 2: Original list: [1, 2, 3, 4, 5] k = 4 Output: [5, 1, 2, 3, 4] Key learnings from Day 5: – List slicing in Python – Handling edge cases safely – Using modulo for optimized logic – Writing clean and reusable functions #Day5 #100DaysOfCode #PythonLists #ListManipulation #AlgorithmPractice #CodingDaily #PythonDeveloper #LearnByCoding

🚀 Want more “Pythonic” code in 5 minutes? These little tricks are not magic. They are tiny shortcuts that make your code cleaner, faster to read and easier to maintain If you write Python daily, keep this cheat sheet nearby ⏱️ 1: List comprehensions — build lists fast, clean, and Pythonic [...] 2: zip() — pair lists by index, no manual loops zip(names, ages) 🔗 3: Unpacking — swap and split values in one step a, b = b, a 🔁 4: *args and **kwargs — flexible functions that accept any inputs def f(*args, 5: **kwargs) 🧩 enumerate() — loop with index without extra counters enumerate(items) 🧠 #Python #Programming #CodingTips #Developer #CleanCode #LearnPython #DevCommunity

📘 Day 18 of my #90DaysPythonChallenge Focus: Python Foundations for Prompt Engineering Today, I worked on writing clean, modular Python code specifically for Prompt Engineering workflows. 🔹 Built reusable functions for prompt generation 🔹 Used *args and **kwargs for flexible inputs 🔹 Implemented basic decorators for logging and validation 🔹 Structured code into modules for scalability This practice helped me understand how real-world prompt pipelines are designed and maintained in production systems. 📂 Practice code available on GitHub: https://lnkd.in/dnNfeh_f #Python #90DaysPythonChallenge #PromptEngineering #LearningInPublic #CodingJourney

Stop writing for loops for simple transformations. 🛑 If you are still initializing empty lists and appending results one by one, it’s time to upgrade your Python toolkit. The combination of map() and lambda is the ultimate "clean code" hack. It allows you to apply logic to an entire iterable in a single, readable line. What’s inside the new video: ✔️ The Syntax: Breaking down the map(function, iterable) structure. ✔️ Anonymous Power: Why lambda is the perfect partner for one-time logic. ✔️ Real-world Examples: Transforming data without the boilerplate code. Check out the full breakdown here: https://lnkd.in/gmGapwUB Subscribe to Codeayan youtube channel for more such upcoming content.🫡 #PythonProgramming #CodingTips #DataScience #SoftwareEngineering #PythonTips #Codeayan #datascience #pythonfunctions

Day 23 Learning | Python Inheritance & OOP Concepts 🚀 Today, I explored the concept of Inheritance in Python, one of the core pillars of Object-Oriented Programming. I focused on how inheritance promotes code reusability, modular design, and better software structure. I studied and practiced different types of inheritance, including: Single Inheritance Multiple Inheritance Multilevel Inheritance Hierarchical Inheritance Through hands-on examples, I understood how child classes can access and extend the functionality of parent classes, and how inheritance helps build scalable and maintainable systems. To apply these concepts practically, I implemented example programs demonstrating real-world class relationships and method reuse across multiple inheritance structures. This learning strengthened my understanding of OOP design principles, code organization, and writing reusable components in Python. 🔗 GitHub Repository: https://lnkd.in/gWJJ_Dkq Consistent learning and implementation are key steps toward becoming a better developer. Looking forward to exploring more advanced OOP concepts. #Python #PythonLearning #OOP #Inheritance #HandsOnLearning #CodingPractice #ProgrammingJourney #LearningByDoing #Consistency

📘 Day 15 of my #90DaysPythonChallenge Topic: Recursion Today, I explored recursion in Python and learned how functions can call themselves to solve problems step by step. 🔹 Practiced recursive functions 🔹 Worked on factorial, sum of numbers, and Fibonacci 🔹 Understood the importance of base cases Recursion helped me think differently about problem-solving and breaking problems into smaller parts. 📂 Practice code available on GitHub: https://lnkd.in/dnNfeh_f #Python #90DaysPythonChallenge #LearningInPublic #CodingJourney #Recursion

🎥 Week 4 | Phase 0 Foundation (Python) | Mini Project video is up. Three weeks of code. All in separate folders. Disconnected. This week I stitched it all together into one reusable package. Built llm-test-utils - a single Python package bundling everything from the past 3 weeks: → Prompt formatter (Week 1) → Test case organizer (Week 2) → llm response validator (Week 3) → All wrapped in a proper package structure Modules. __init__.py. Virtual environments. The stuff that turns scripts into actual software. If you're following along, try building it yourself first. Video's there if you get stuck or want a different perspective. Link in comments. #GenAITesting #LearnInPublic #LLMTesting #Python #AITesting #QAEngineer #QAEngineer #SoftwareTesting #52WeekChallenge