Boundev.ai’s Post

🚀 Day 8/30 of My LeetCode Journey (Python + SQL) Staying consistent and leveling up every day! 💻🔥 🔹 **SQL Problem of the Day** 👉 *Find Customer Referee* Given a `Customer` table, write a query to find the names of customers who are either: • Not referred by customer with id = 2 • OR not referred by anyone 💡 *Key Concept:* Filtering with conditions (`!= 2` OR `IS NULL`). 🔹 **Python Problem of the Day** 👉 *Merge Sorted Array* Given two sorted arrays, merge them into a single sorted array in-place without returning a new array. 💡 *Key Concept:* Two-pointer approach from the end for efficient in-place merging. Every problem is helping me think more efficiently and write better code ⚡ Day 8 done ✅ #LeetCode #30DaysChallenge #Python #SQL #CodingJourney #Consistency #ProblemSolving #Learning

A 40ms API became a 4ms API. Here's the only thing that changed. We were making 3 separate DB queries to assemble a response. Each was fast in isolation. Together, they were sequential — each waited for the previous. The fix: run them concurrently. In Python (asyncio), this went from: result_a = await get_a() result_b = await get_b() result_c = await get_c() To: result_a, result_b, result_c = await asyncio.gather(get_a(), get_b(), get_c()) That's it. No caching, no infra change, no complex refactor. The mental model that helps: always ask "are these operations actually dependent on each other?" before assuming they need to run in sequence. Most API latency problems aren't hard — they're just unexamined. #BackendDevelopment #PythonAsyncio #APIOptimization #SoftwareEngineering

Day 46/60 of #60DaysOfMiniProjects Built a Smart Study & Mood Tracker using Flask! Excited to share my latest project where I combined productivity tracking with a touch of intelligent suggestions Features: • Track daily study sessions with mood & notes • Smart suggestions based on mood and activity • Productivity score calculation • Daily streak tracking • Search, edit, and manage past sessions • Clean and simple user interface Tech Stack: Python | Flask | JSON | HTML/CSS This project helped me understand how small data insights can improve consistency and focus in daily routines. Would love your feedback and suggestions to improve it further! #Python #Flask #WebDevelopment #StudentProjects #Productivity #CodingJourney #OpenToLearn

This week I spent 2 hours debugging a pipeline that broke because of a subtle mutable default argument. Last week I finished DataCamp's "Intermediate Python for Developers" - and guess what chapter was in there. Funny how that works sometimes. A few takeaways that'll stick with me: • Mutable defaults are a trap, even for people who "know Python" • Decorators aren't magic - they're just functions returning functions (but the mental model matters) • Comprehensions > loops, until they don't fit on one screen anymore Working with Python daily on dbt models, and data transformations, it's easy to get comfortable in a narrow slice of the language. Stepping back to revisit the fundamentals consistently makes my production code cleaner. What's your approach - do you block time for structured learning, or learn purely on the job? #Python #DataEngineering #LearningInPublic

QuillSort — A data sorter Created by Isaiah Tucker Most of the time, Python’s built-in sorted() and list.sort() are all you need. But if you ever try to sort a lot of data—millions to billions of values, big numeric logs, or giant SQL exports—you quickly run into a wall: RAM, speed, or both. So I built Quill-Sort (quill-sort on PyPI). / ... link https://lnkd.in/eHaFZyx4 pubDate Wed, 01 Apr 2026 03:29:53 +0000

𝗣𝘆𝘁𝗵𝗼𝗻 𝗖𝗼𝗹𝗹𝗲𝗰𝘁𝗶𝗼𝗻𝘀 – 𝗟𝗶𝘀𝘁 𝘃𝘀. 𝗦𝗲𝘁 🐍 When you're building a Python app, choosing the right data structure isn't just about syntax, it's about performance. I spent today breaking down the "Why" and "When" of Lists and Sets: 🔹 𝗨𝘀𝗲 𝗮 𝗟𝗜𝗦𝗧 𝘄𝗵𝗲𝗻: 1️⃣ You need to maintain the order of items. 2️⃣ You have duplicate data (e.g., a list of transaction amounts). 3️⃣ You need to access items by their position (Index). 🔸 𝗨𝘀𝗲 𝗮 𝗦𝗘𝗧 𝘄𝗵𝗲𝗻: 1️⃣ You need unique items only (Auto-removes duplicates). 2️⃣ Search speed is critical.Sets use Hashing for O(1) lookups. 𝗗𝗮𝘆 𝟭𝟰/𝟯𝟬 #30DaysOfCode #PythonLearning #DataStructures #Day14

When you start working with APIs in Python 🧪 one of the most common ways to see results is with Flask. Just like in a laboratory, you experiment with flasks and ampoules. Here, the Flask is your container. You pour in routes, logic, requests. You observe what comes out. Simple. Lightweight. Immediate feedback. No heavy setup. No complex structure at the beginning. Just you… testing ideas in real time. And that’s exactly why it works so well early on. Because before scaling, before architecture, before optimization… you need a place to experiment. Flask is that place. #Python #Flask #APIs #SoftwareEngineering #BackendDevelopment #DeveloperLife #ContinuousLearning #RotterdamTech

🚀 Day 3/30 of My LeetCode Journey (Python + SQL) Showing up daily and building consistency, one problem at a time! 💻🔥 🔹 **Python Problems of the Day** 👉 *1. Move Zeroes* Given an integer array, move all 0’s to the end while maintaining the relative order of non-zero elements. Do it in-place without making a copy. 💡 *Key Concept:* Two-pointer technique for efficient in-place rearrangement. 👉 *2. Remove Element* Given an array and a value, remove all occurrences of that value in-place and return the number of remaining elements. 💡 *Key Concept:* In-place filtering using pointer overwrite approach. 🔹 **SQL Problem of the Day** 👉 *Find Duplicate Emails* Given a `Person` table with an email column, write a query to report all duplicate emails. 💡 *Key Concept:* GROUP BY with HAVING COUNT > 1. Small steps daily = Big progress over time 📈 Staying consistent and enjoying the process! #LeetCode #30DaysChallenge #Python #SQL #CodingJourney #Consistency #ProblemSolving #LearnInPublic

📝 Why I deliberately write "boring" code: Fancy code is impressive. Boring code is reliable. What boring code looks like: ✅ Clear variable names (customer_count not cc) ✅ Small functions that do one thing ✅ Comments that explain WHY, not WHAT ✅ Consistent formatting ✅ Error handling for edge cases Who benefits? → Future me (6 months from now, I won't remember) → My teammates (they can actually read it) → Production (less surprises at 2 AM) Clever code makes you feel smart. Boring code makes you effective. Which do you prefer to maintain? #CodeQuality #Python #DataEngineering #CleanCode