Weblearns’ Post

LeetCode #21 – Merge Two Sorted Lists | Python Implementation I implemented an iterative two-pointer merge approach for combining two sorted linked lists. A dummy node serves as the anchor, and a tail pointer builds the merged list by always selecting the smaller current node from either list. After one list is exhausted, the tail directly attaches the remainder of the non-empty list since it's already sorted. This avoids unnecessary node-by-node traversal and keeps the solution clean. This pattern is core to merge sort implementations, database query result merging, and distributed log aggregation systems where sorted streams must be combined efficiently. Key Takeaway: Using a dummy node eliminates edge case handling for the first node insertion, simplifying the logic significantly. The direct attachment of remaining nodes after one list is exhausted is an optimization that leverages the sorted property, avoiding redundant comparisons. Time: O(n + m) where n, m are list lengths | Space: O(1) #LeetCode #DataStructures #Python #LinkedList #TwoPointers #CodingInterview #ProblemSolving #SoftwareEngineering

Built a YouTube Video Statistics Checker 📊 using Python and the YouTube Data API, which extracts video details like views, likes, and comments directly from a video URL. This project helped me gain hands-on experience with API integration, regex-based URL parsing, and building command-line applications in Python. GitHub: https://lnkd.in/gKetegTd #Python #APIs #YouTubeDataAPI #MiniProject #LearningByDoing

Python Tip — Tuples: Small Feature, Big Signal Most developers see tuples as “lists you can’t modify.” That’s surface-level thinking. Tuples are about immutability and intent. When you use a tuple, you’re telling other developers: “This data should not change.” They’re: - Faster than lists - Hashable (usable as dictionary keys) - Safer for fixed data - Perfect for returning multiple values Use lists for collections that evolve. Use tuples for data that represents a fixed structure. In Python, the right data structure isn’t just technical, it communicates design. FOLOW FOR MORE PYTHON TIPS & INSIGHTS #Python #DataStructures #CleanCode #SoftwareEngineering #ProgrammingTips

I recently attempted to create some YouTube videos that explain basic Python scripts. This straightforward code uses the emails' structural profile to extract emails from a natural text file. Here is the YT link: https://lnkd.in/gtjBqve3 GitHub repository link: https://lnkd.in/gCVR3iRe

Rembus Introduces Async-first RPC and Pub/Sub with Synchronous Python API 📌 Rembus introduces a lightweight, async-first messaging system for Python that seamlessly blends RPC and Pub/Sub with a simple synchronous API-perfect for edge and embedded applications. Built with CBOR for speed and DuckDB for persistent, ACID-compliant storage, it enables real-time DataFrame sharing and hierarchical topic routing, all without heavy infrastructure. 🔗 Read more: https://lnkd.in/dF9JHama #Rembus #Python #Rpc #Pubsub #Asyncfirst

You can automate Google Drive entirely in Python. No external automation tools ! I used : Just 2 Python files to: • track new files in Google Drive • sync and categorize them automatically And 2 more Python files to: • generate embeddings • run Q&A on top of the file content The only cost involved is the LLM API used for embeddings and Q&A. Everything else runs purely in Python. All fully automated. No manual triggers. This video shows the syncing & tracking layer. PS: More Python automations coming 🐍 - - - - #AIEngineer #AIAutomation #PythonAutomation #AgenticAI #RAG

Today I went deeper into Python file handling and it turned out to be more interesting than I expected. What seems simple at first (open(), read(), write()) actually hides subtle behavior: • "w" and "w+" clear the file the moment it’s opened • "r+" allows modification without automatically deleting content • The file pointer silently moves after read/write operations making seek(0) essential • truncate() prevents unexpected leftover data when rewriting shorter content It’s easy to use these functions. It’s harder and more valuable to understand how they behave internally. Worked through practical problems to move from just using file handling to actually understanding it. #Python #learningpython #filehandling

Python Tip: List Methods - Work Smarter, Not Harder Still manually adding, removing, or searching elements in a list? Python’s built-in list methods do it cleanly and efficiently. - .append() to add - .extend() to merge - .insert() to place at a position - .remove() & .pop() to delete - .sort() & .reverse() to organize - .count() & .index() to query Smarter Python isn’t about writing more loops. It’s about using the tools Python already gives you. FOLLOW FOR MORE PYTHON TIPS & INSIGHTS #Python #DataStructures #CleanCode #ProgrammingTips #SoftwareEngineering

🐍 Python Tip of the Day: Remove duplicates from a list WITHOUT losing the order! Most developers jump to set() to remove duplicates — but there's a catch: ❌ list(set(items)) → fast, but shuffles your order ✅ list(dict.fromkeys(items)) → removes duplicates AND keeps original order Here's how it works: Dictionaries can't have duplicate keys. So when you pass your list into dict.fromkeys(), it silently drops any repeated values — keeping only the first occurrence. Since Python 3.7+, dictionaries also maintain insertion order, which means you get back a clean, deduplicated list in the exact order you started with. 🎯 Simple. Elegant. No extra imports needed. ♻️ Repost if this helps someone on your feed! #Python #CodingTips #SoftwareDevelopment #ProgrammingTricks #CleanCode

🌐 Day 11: Starting My FastAPI Journey ⚡ After revisiting Python fundamentals over the past several days, today I officially started exploring FastAPI, a modern and high-performance framework for building APIs with Python. Today’s focus was on understanding the foundations of FastAPI: ✅ What FastAPI is and why it’s widely used for backend development ✅ Installing FastAPI and setting up the development environment ✅ Running the first FastAPI application using Uvicorn ✅ Understanding the structure of a basic API endpoint ✅ Exploring FastAPI’s automatic documentation (Swagger UI) One thing that stands out immediately is how clean and developer-friendly FastAPI is. Python type hints automatically generate interactive API documentation, which is incredibly powerful. 💡 Key takeaway: A strong Python foundation makes learning backend frameworks significantly smoother. Looking forward to building more endpoints and exploring request handling, parameters, and data validation next. #FastAPI #Python #BackendDevelopment #APIDevelopment #DevJourney #LearningInPublic #SoftwareDevelopment #Coding