Day 12 — Error Handling: Writing Code That Doesn’t Crash Errors are not failures. They are signals. Real-world programs don’t stop just because something goes wrong — they handle it gracefully. That’s exactly what error handling is about. Today you learned: • Why errors happen at runtime • How try and except blocks prevent crashes • How to catch specific errors like ZeroDivisionError • How to keep programs running even when inputs are wrong This is where your code starts behaving like production code, not practice code. Error handling is used everywhere: • User input validation • File handling • Network requests • APIs and backend systems If your code can fail safely, it can scale confidently. Mini Challenge: Write a program that asks for two numbers and safely handles division by zero using try and except. Post your solution in the comments. I’m sharing Python fundamentals — one practical concept per day. Built to help beginners write reliable, real-world Python. Next up: List and Dictionary Comprehensions — writing clean one-line logic. Learning to debug and handle errors becomes much smoother in PyCharm by JetBrains, especially with clear error messages and stack traces. Follow for the full day Python series. Like • Save • Share with someone learning Python. #Python #LearnPython #PythonBeginners #ErrorHandling #Programming #CodingJourney #Developer #Tech #JetBrains #PyCharm

🧠 Python Feature That Makes Error Handling Elegant: contextlib.suppress 💫 No noisy try/except. 💫 No empty except: pass. 💫 Just clean intent ❌ Old Way try: os.remove("temp.txt") except FileNotFoundError: pass Works… but feels messy 😬 ✅ Pythonic Way from contextlib import suppress with suppress(FileNotFoundError): os.remove("temp.txt") Readable. Explicit. Clean. 🧒 Simple Explanation Imagine wearing noise-canceling headphones 🎧 You choose which noise to ignore. Python ignores only that error — nothing else. 💡 Why This Is Powerful ✔ Cleaner error handling ✔ Avoids swallowing real bugs ✔ Very expressive code ✔ Used in production-grade code ⚠️ Important Rule Only suppress errors you truly expect (never hide bugs blindly ❌) 💻 Clean code isn’t about removing errors. 💻 It’s about handling them intentionally 🐍✨ 💻 contextlib.suppress is Python being elegant again. #Python #PythonTips #PythonTricks #AdvancedPython #CleanCode #LearnPython #Programming #DeveloperLife #DailyCoding #100DaysOfCode

Here's what nobody tells you about learning Python 🐍 Most people waste months on random tutorials. 📚 Here's the exact roadmap that actually works. ⚡ Learn in this order: 🎯 - Variables, data types, strings (Day 1-2) 📝 - If/else, loops, functions (Day 3-5) 🔄 - Lists, dicts, tuples (Day 6-8) 📊 - File handling (read/write files) (Day 9-10) 📁 - Modules like requests, pandas (Week 2-3) 🧩 Then build real projects immediately: 🛠️ File renamer, expense tracker, web scraper, automated emails 📧 The brutal truth? 💡 You don't need 6 months of theory. Learn basics in 2 weeks, then build daily. 🚀 #python #coding #programming #developer #softwareengineer #tech #learning #productivity #careergrowth #buildinpublic #devlife #techcommunity #growthmindset #datascience #webdevelopment #successmindset #innovation #careertips

𝗧𝗵𝗲 𝗣𝗼𝘄𝗲𝗿 𝗼𝗳 𝗙𝗲𝗮𝘁𝘂𝗿𝗲 𝗧𝗼𝗴𝗴𝗹𝗲𝘀 You want to launch new software features without breaking everything. You can use Feature Toggles to turn features on or off. - They let you change your system without changing code. - You can test features in production without affecting users. There are four types of Feature Toggles: - Release Toggles: for launching new features - Experiment Toggles: for testing features - Ops Toggles: for controlling features - Permissioning Toggles: for customizing user experiences Here's an example with Python and FastAPI: - Create a toggle for a new feature - Use the toggle to turn the feature on or off You can manage toggles with tools like LaunchDarkly or Unleash. Tips for using Feature Toggles: - Name your toggles clearly - Remove old toggles - Test both paths - Use management tools Feature Toggles help you: - Reduce deploy risk - Test features in production - Release features to subsets of users - React quickly to production problems Source: https://lnkd.in/featuretoggles Optional learning community: https://lnkd.in/g3KuFrnk

In last post I talked about a problem I faced. Setting up a RAG pipeline was way harder than it should be. So here's the idea I came up with. 💡 What if there was a Python library that: → Takes any PDF or TXT file as input → Automatically chunks the document → Embeds it using FREE HuggingFace models → Stores it in a vector index → Lets you query it in plain English All of this. In 5 lines of code. No OpenAI key. No complex setup. No 200-page documentation. Just: ```python from ragkitpy import RAGPipeline rag = RAGPipeline() rag.load_document("my_file.pdf") results = rag.query("What is this document about?") ``` That's it. That's the whole idea. I'm calling it → ragkitpy 🚀 A lightweight, beginner-friendly RAG toolkit powered entirely by HuggingFace open-source models. No subscriptions. No API bills. Just pure Python. The best part? I'm building this as a complete beginner to open source. No senior guiding me. No company project backing it. Just curiosity, Google, and a lot of pytest runs. 😄 Next post → I'll break down how existing tools work and exactly where ragkitpy fits in. --- Follow along if you're curious about RAG, open source, or just love seeing someone figure things out in public. 🙌 #GenAI #RAG #OpenSource #Python #HuggingFace #BuildingInPublic #ragkitpy #AIEngineer #100DaysOfCode

I built a habit tracker because I needed one. Yes… discipline was losing the battle 😅 So instead of fixing my habits… …I built an app to fix them. 🔥 Introducing: Smart Habit Tracker (built using Python & Streamlit) Here’s what it does: 1. Sign up & create unlimited habits 2. If you type “study” → it asks for hours (no excuses allowed) 3. Other habits? Just tick and move on 4. Tracks streaks automatically 5. Shows progress in clean dashboards 6. Generates a monthly printable tracker (for the aesthetic planners 👀) Basically: No more “I’ll start tomorrow.” Now it’s: “The app is watching.” 😎 Tech used: Python, Streamlit, SQLite, Plotly, ReportLab Live Demo: https://lnkd.in/gKyRpGG6 Now I’m curious 👇 What habit do YOU struggle with the most? #Python #Streamlit #BuildInPublic #Productivity #LearningByBuilding #SideProject

#DAY 2 of challange Rule #1: Always Be Different. While others were building Python projects that create things in the air… I decided to control something real. I built a system where I can move my laptop cursor just by pointing. As you can see in the first clip — I trained my own model. In the second clip — you can see the cursor moving live. And it doesn’t just move… it performs real actions 1.Pinch gesture → Control volume 2.Grab & drop → Move software or browser windows 3.Custom gestures → Custom actions 4.Pointing → Accurate cursor movement All of this is built completely in Python This is not just a project. It’s about thinking differently. And the best part? I’m making it open-source so anyone can build, improve, and innovate on top of it. 🔗 GitHub: https://lnkd.in/gZUwMQEX The goal isn’t to follow trends. The goal is to create them. #Python #AI #MachineLearning #ComputerVision #OpenSource #Innovation #BuildInPublic

🚀 Day 9 | Python Functions – Writing Reusable and Structured Code Every programmer eventually realizes that writing the same logic again and again is inefficient. That’s where functions become powerful—they help us organize, reuse, and structure code effectively. In today’s notebook / carousel, I explored: ✔ Purpose and definition of functions ✔ Parts of a function and execution phases (Input → Process → Output) ✔ Different approaches to defining functions ✔ Arguments vs Parameters (formal and actual) ✔ Types of arguments: Positional arguments Default arguments Keyword arguments Variable-length arguments (*args) Keyword variable-length arguments (**kwargs) What stood out to me while learning this is how functions are not just about syntax—they’re about thinking in modular, reusable blocks, which is a core mindset in software engineering, data science, and machine learning workflows. Day_09_Python_Functions 📌 Part of my learning-in-public journey, building Python step by step with strong fundamentals. 🙏 Grateful to my mentor, Nallagoni Omkar Sir, for guiding me through these concepts clearly. 👉 Next up: Global and Local variables, lambda functions, and special functions (map, filter, reduce) #Python #DataScience #CorePython #Functions #LearningInPublic #ProgrammingFundamentals #StudentOfDataScience #MachineLearning #NeverStopLearning