Strengthening Backend Fundamentals with DSA and Development

In my 3rd semester, I challenged myself to build something bigger than assignments and coding exercises. So I built a complete Library Management System (LMS) from scratch using only core Data Structures in Python. No frameworks. No databases. No shortcuts. Just raw DSA. At that time, we were studying Binary Search Trees and Linked Lists. Instead of just solving textbook problems, I wanted to see what happens when these structures power a real system. Here’s how I designed it: 🔹 Books → Binary Search Tree (BST) Each book was stored using its ID as the key. This allowed efficient search, insertion, and deletion in O(log n) average time. I implemented: Insertion Deletion (including inorder successor logic) Search Quantity updates Issue & return operations 🔹 Admin Accounts → Singly Linked List Admins were stored dynamically in a linked list. I implemented: Account creation with duplicate prevention Password verification Hint-based password recovery Account deletion with position tracking 🔹 Students → Ordered Linked Structure Each student record contained: ID Name Two book slots Issue dates Return deadlines Fine calculation logic The system also: ✔ Applied 15-day return deadlines ✔ Automatically calculated fines ✔ Controlled maximum book allotment ✔ Maintained dynamic memory without using built-in collections What I learned from this project: Data structure choice directly impacts performance. Edge cases take more effort than the main logic. Deletion in a BST is not as simple as it looks in textbooks. Building a system teaches more than solving isolated problems. Debugging pointer logic in linked lists strengthens fundamentals. Looking back, I would now improve it using: Hash maps for O(1) lookups A self-balancing tree (AVL/Red-Black) instead of a plain BST Better separation between logic and UI But the most important outcome wasn’t the code. It was understanding how data structures connect to real-world systems. If you’re learning DSA right now, try building something complete instead of just solving practice questions. It changes how you think. Curious — what was the first “real” system you built while learning core CS concepts? #DataStructures #Python #ComputerScience #DSA #LearningJourney #SoftwareEngineering #ProblemSolving

𝐅𝐨𝐜𝐮𝐬 𝐨𝐧 𝐬𝐨𝐥𝐯𝐢𝐧𝐠 𝐩𝐫𝐨𝐛𝐥𝐞𝐦𝐬, 𝐧𝐨𝐭 𝐣𝐮𝐬𝐭 𝐥𝐞𝐚𝐫𝐧𝐢𝐧𝐠 𝐬𝐲𝐧𝐭𝐚𝐱 Many beginners spend months watching tutorials on languages like Python or JavaScript but never build anything on their own. Programming isn’t about memorizing syntax, it’s about learning how to think and solve problems. 𝗪𝗵𝗮𝘁 𝘆𝗼𝘂 𝘀𝗵𝗼𝘂𝗹𝗱 𝗱𝗼 𝗶𝗻𝘀𝘁𝗲𝗮𝗱: Learn a little → Build a little. After learning a concept (loops, functions, arrays), immediately use it in a small project. Example: Learned loops? → Build a number guessing game. Learned APIs? → Build a simple weather app. Learned basics of web? → Create your own portfolio site. 𝗦𝘁𝗿𝘂𝗴𝗴𝗹𝗲 𝗽𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝘃𝗲𝗹𝘆. Don’t quit when you’re stuck. That “confused” phase is where real learning happens. Googling errors and reading documentation is part of the job. 𝗣𝗶𝗰𝗸 𝗼𝗻𝗲 𝗹𝗮𝗻𝗴𝘂𝗮𝗴𝗲 𝗮𝗻𝗱 𝗴𝗼 𝗱𝗲𝗲𝗽. Don’t jump between 5 languages. Start with something beginner-friendly like Python and stick with it until you’re comfortable building small projects alone. 𝘽𝙪𝙞𝙡𝙙 𝙧𝙚𝙖𝙡 𝙥𝙧𝙤𝙟𝙚𝙘𝙩𝙨 𝙚𝙖𝙧𝙡𝙮. Projects teach you: Debugging Structuring code Researching solutions Handling frustration Those skills matter more than knowing every keyword. #beginners #coding #journey #roadmap #programming #skills #python #django #fastapi #html #css

🚀 Day 10 of My DSA Journey Today I solved the “Missing Number” problem on LeetCode using Java. This problem is about finding the missing number in an array containing n distinct numbers from the range [0, n]. Example: Input: [3,0,1] Output: 2 💡 My Learning Process Today Instead of jumping directly to the optimal solution, I followed a step-by-step thinking approach. 1️⃣ First Approach (Brute Force) Initially, I used nested loops to check every number from 0 → n and see if it exists in the array. For each number i, I searched the entire array. If the number wasn't found, that was the missing number. 📊 Time Complexity: O(n²) Although it worked, it was not efficient, and the runtime reflected that. 2️⃣ Second Approach (Optimal Solution) After thinking again about the problem, I realized something interesting. If the numbers range from 0 → n, then the sum of all numbers should be: n(n+1)/2n(n+1)/2n(n+1)/2So I: 1️⃣ Calculated the expected sum using the formula 2️⃣ Calculated the actual sum of array elements 3️⃣ Subtracted them to find the missing number 📊 Time Complexity: O(n) 📦 Space Complexity: O(1) This approach improved the runtime significantly. ⚡ Result: 0 ms — Beats 100% 📚 Key Takeaway Today reinforced an important lesson: The first solution doesn’t have to be perfect. Start with a working approach, then optimize it. This mindset is helping me develop stronger algorithmic thinking every day. On to Day 11 tomorrow. 💪 #DSA #LeetCode #100DaysOfCode #Java #ProblemSolving #CodingJourney #LearningInPublic #Algorithms #Consistency

🧑💻 Day 98 of My Python Learning 💡 “Small scripts build real skills. Keep learning and keep building.” 1️⃣ Refreshing the Page Sometimes a webpage needs to be refreshed to reload the latest content. We can do this using: driver.refresh(). This reloads the current webpage, just like pressing the refresh button in a browser. 2️⃣ Finding an Element by XPath XPath is a way to locate elements in the HTML structure of a webpage. Example: driver.find_element(By.XPATH, "//input[@id='twotabsearchtextbox']") XPath is useful when: -Elements don’t have simple IDs -We need to locate elements based on their position in the page structure 3️⃣ Getting Data from a Webpage After locating elements, we can extract information from them. Example: products = driver.find_elements(By.XPATH, "//h2//span") for p in products: print(p.text) This collects product titles from the page and prints them. Reference to today's Code: GitHub 1. https://lnkd.in/drXkEftF 2. https://lnkd.in/dJuzeZxg #tutedude #learning #coding #python #consistency #linkedin #skillup #linkedin #career #goal #passion #Interest #Github V S NAVEEN KUMAR AMBATI

I wanted to brush up my coding skills and upon reviewing the code I wrote with my friend I started to think deeper on how to improve readability. If everybody writes code that is simply built into the language without thinking about it, people can get lost and projects can be delayed. However, if the programmer can get enough information from the code that they are reading, they should have an easier time navigating and modifying the code. For example, with python the standard for-loop has for...in... Unless you are very used to reading python list comprehension, for-loop could serve better. Python is renowned for being short and readable, but the idea of readability might be subject to the audience. If you can see that majority of people reading the code may not be familiar with pythonic way, then it could make sense to just use classic for-loop: we could write in 2 diff manners, but if we are always spamming list comprehension when I am working with many non-python devs, it might help to use plain for-loop. Perhaps longer, but simpler. #CS #ComputerScience #SoftwareEngineer #SoftwareDeveloper #SDE #SWE #python #python3 #for-loop #readability 

🚀 Introduction to OOPS in Python – Class & Object Practice As part of strengthening my Python fundamentals, I started practicing Object-Oriented Programming (OOPS) concepts. To understand classes and objects clearly, I implemented three simple real-world examples: 🧑🎓 Student Class 4 Properties: name, age, course, marks 2 Methods: display information & check pass/fail Created object and accessed methods 💻 Laptop Class 4 Properties: brand, RAM, storage, price 2 Methods: display specs & check price category 🏍️ Bike Class 4 Properties: brand, model, mileage, price 2 Methods: display details & check affordability 📚 Concepts Practiced: ✔ Class & Object creation ✔ __init__ constructor ✔ Instance variables ✔ Method definition ✔ Accessing methods using objects ✔ Basic conditional logic inside classes This practice helped me understand how real-world entities can be modeled using OOPS principles. Strong fundamentals in OOPS are essential for: Backend Development System Design Writing scalable code Learning step by step. Improving every day 💪 📄 Code attached in the PDF. 🙏 Thanks to 10000 Coders and venubabu vajja for continuously motivates me to learn and grow. #Python #OOPS #ObjectOrientedProgramming #BackendDeveloper #CodingJourney #DSA #Learning

5 Coding Tips for Beginners (62 words) Coding writes instructions for computers using Python (AI/data), JavaScript (web), or C++. Start here: Pick Python—beginner-friendly. Use freeCodeCamp/Codecademy. Build mini-projects (calculators). Practice daily 30 mins. Leverage AI code explainers. Careers: Web dev, data science ($62k–$100k+). VS Code + Git tools. From our startup thread: Code your ad agency site for $0 after learning.

🚀 I'm working on a project. First and difficult step is to monitor webpage. The idea is to automatically check whether a website or API is working correctly instead of manually testing it. Mejor things to check: - Verifies if a page is reachable or not. Means status codes. - Measures response time to detect slow pages. - Validates API responses to make sure the expected data structure is returned. - Checks HTML structure to detect missing elements - Detects broken images on pages - Logging the results so issues can be tracked over time - means tracking all the urls, status code or severity. This helped me understand how monitoring tools detect problems before users notice them. It also connects directly to the goal of my project like- automatically detecting bugs and prioritizing them based on severity. Note: everything is in python libs, ' bs4 ' or ' request ' Next step could be - Expanding it to classify errors and devs could work on them and resolve it. #Python #BackendDevelopment #WebMonitoring #LearningInPublic

Difference Between Writing Code That Works vs Code That’s Smart Most beginners write extra logic to solve simple problems. Example: counting word frequency in text. A typical beginner approach: → loop through words → check if exists → increment count → else create entry It works ✔️ But it’s verbose and slower to write. Pythonic approach: Counter(text.split()) One line. Same result. Cleaner logic. Lesson: Great developers don’t just solve problems — they know built-in tools that solve them faster and better. Efficiency isn’t only runtime. It’s also how efficiently you think. Write code that thinks before it runs. What’s one Python shortcut you wish you learned earlier? #Python #CodingTips #Programming #SoftwareEngineering #Developers #LearnToCode

🚀 Day 25 / 100 – #100DaysOfCode Today’s focus: Prefix Sum ✅ Problem solved:longestsubarraywithequalpositiveandnegativenumbers ✅ Approach used: Prefix ✅ Time Complexity: o(n) ✅ Key learning: First convert the array with condition if (arr[i] %2 == 0) arr[i] = 1 else arr[i] = -1; Initialize the maxlength with 0 and traverse the array and put map.put(0,-1) and use the length = i - map.get(sum) and use the maxlength = Math.max(length,maxlength) to get the maximum length.Print the maximum length. Consistency > Motivation. Building strong DSA + MERN fundamentals step by step. #DSA #Java #CodingJourney #LearnInPublic #MERN #PlacementPrep