🚀 Day 85 of #100DaysOfLeetCode 🔍 Problem Solved: Ransom Note (LeetCode 383) Today’s problem was all about efficiently checking whether one string can be constructed from another — a classic hashing / frequency counting concept. ⚡ What I Learned: - Importance of frequency maps (hash tables) - Writing optimized solutions over naive approaches - How built-in methods can simplify logic but may impact performance 📊 Performance: ✅ Runtime: 0 ms (Beats 100%) ✅ Memory: Efficient usage 🔥 Takeaway: Small optimizations and choosing the right data structure can make a huge difference, even in easy problem #Day85 #LeetCode #CodingJourney #Python #DataStructures #ProblemSolving #100DaysOfCode

🔁 Python Revision – Sets Continuing my Python fundamentals revision 🐍 In this session, I focused on: ✔️ Sets (creation and properties) ✔️ Unique elements and unordered nature ✔️ Set methods (add, remove, discard, etc.) ✔️ Set operations (union, intersection, difference) Practiced using sets to handle unique data and perform efficient operations like finding common or different elements between datasets. Documented my practice in a Jupyter Notebook and shared it as a PDF to track my progress. Understanding sets is helping me work better with data and avoid duplicates 📊 Next: dictionaries and real-world data handling 🚀 #Python #Revision #Sets #Programming #DataAnalytics #LearningJourney #Coding

The moment you add a new condition to an if/else chain in your pipeline, you’ve modified existing code! That’s exactly the smell OCP is meant to catch. 🔍 Open for extension, closed for modification means adding new behavior by writing new code, not patching old one! In my latest article, I break down what OCP looks like in Python data projects: strategy patterns, abstract base classes, and the tradeoffs of when the extra structure is actually worth it. https://lnkd.in/eE9yicvC This is Part 2 of my SOLID series. What’s the most painful “just add another elif” you’ve ever had to maintain? 😅 #Python #SoftwareEngineering #SOLID #DataScience #CleanCode

Day 4 done Today was less about “big problems” and more about practical coding: File line counting from a text file Word frequency counting with text cleaning Just Python basics that actually matter in real projects: file I/O, regex splitting, whitespace cleanup, punctuation handling, and case normalization. What I liked most today: small logic details made a big difference. A tiny cleanup step can completely change output quality. Code for Day 4: https://lnkd.in/gh-KJzG5 #Python #SoftwareEngineering #DeveloperJourney #Day4 #ProblemSolving

🔁 Python Revision – Tuples Continuing my Python fundamentals revision 🐍 In this session, I focused on: ✔️ Tuples (creation and properties) ✔️ Indexing and slicing ✔️ Immutable nature of tuples ✔️ Tuple methods (count, index) Practiced using tuples for storing fixed and ordered data, and understood how immutability can help in writing safer and more efficient code. Documented my practice in a Jupyter Notebook and shared it as a PDF to track my progress. Learning when to use tuples vs lists for better data handling 📊 Next: functions and applying concepts to real-world problems 🚀 #Python #Revision #Tuples #Programming #DataAnalytics #LearningJourney #Coding

🚀 Day 37/60 — LeetCode Discipline Problem Solved: Concatenation of Array Difficulty: Easy Today’s problem was simple yet elegant — creating a new array by concatenating the given array with itself. Instead of manually looping, I used Python’s direct list operation to duplicate the array efficiently. 💡 Focus Areas: • Understanding array manipulation • Leveraging built-in language features • Writing concise and clean code • Avoiding unnecessary complexity • Strengthening fundamentals ⚡ Performance Highlight: Achieved 0 ms runtime (100% performance) Sometimes, the most powerful solutions are the simplest ones. No heavy logic… no complex structures— just clarity of thought and clean execution. #LeetCode #60DaysOfCode #100DaysOfCode #DSA #Arrays #Python #CodingJourney #ProblemSolving #Developers #TechGrowth #Consistency

⏰ Day 56 of My Python Journey – Building an Alarm Clock Today I combined my knowledge of date & time manipulation with automation and text-to-speech to create a simple alarm program in Python. 🔹 What I built: An alarm that checks the current time continuously using the datetime module. When the set alarm time matches, it triggers a voice alert using the pyttsx3 library. Added a loop to repeat the spoken message multiple times for emphasis. 🔹 Key Learnings: How to integrate multiple modules (datetime, time, pyttsx3) to solve a real-world problem. The importance of continuous loops and condition checks in automation tasks. How text-to-speech can make Python programs more interactive and user-friendly. ✨ Reflection: Crossing Day 56 feels exciting because I’m now building programs that connect directly to everyday life. From simple algorithms to now creating an alarm clock, Python is proving to be a versatile tool for both problem-solving and practical applications. #Python #Day56 #LearningJourney #Automation #TextToSpeech #CodingConsistency #ProblemSolving

Dashboard with DASH. Using a series of synthetic data, I created this dashboard using the DASH library in Python, but I must admit that it's easier to work with the Shainy library in R. Which do you prefer? The advantages of using these two libraries I just mentioned are that they are completely free and that you can also share and interact with the image in a professional meeting without having to pay a single cent. This is much more expensive with other solutions. #DataVisualization #PythonProgramming #BusinessIntelligence

🚀Day 65 | Lambda Functions & Functional Programming Today I practiced Python lambda functions and their real-time usage - What I Worked On: •Created lambda function to find square of a number •Used lambda with sum() to calculate total of list elements •Applied sorted() with lambda to sort tuples based on index •Used math.sqrt() with lambda for square root calculation •Built lambda for adding two numbers 💡Key Learning: •Lambda functions help write short and clean code •Useful for one-line operations and quick logic •Powerful when combined with functions like sorted(), map() 👉🏻Small concepts like lambda can make code more efficient and readable Consistency is turning basics into strength #Day65 #Python #LambdaFunctions #FunctionalProgramming #ProblemSolving #CodingJourney #10000Coders #PythonDeveloper #SravanKumarSir

🐍 New on wcblog.in: Python Basics — Variables, Data Types, Loops & Functions Explained If you're starting out with Python (or need a solid refresher), I just published a practical, engineer-focused guide covering everything you need to write real Python code from day one: ✅ Variables & data types (int, str, list, dict, set...) ✅ String manipulation & f-strings ✅ Loops — for, while & list comprehensions ✅ Functions, *args, **kwargs ✅ Error handling with try/except ✅ A mini pipeline project to tie it all together Python is the backbone of data engineering, ML, and automation — and it all starts with these fundamentals. 👉 Read the full guide: https://lnkd.in/g92XrVSU #Python #DataEngineering #PythonBasics #LearnPython #Programming #DataEngineer #TechBlog