Interactive Weather App with Open-Meteo API

Day 134 of My Data Science Journey: Today I studied Streamlit Web App Development & Deployment Here’s what I learned: 🔹 How to deploy Streamlit apps on free servers 🔹 Making apps accessible to the public 🌍 🔹 Preparing projects for real-world use 🔹 Understanding deployment challenges and how to solve them Now it’s not just about building apps, but also sharing them with the world 🔥 💡 Key Learning: If you don’t deploy your project, it stays limited to you. #Day134 #Streamlit #WebDevelopment #DataScience #Python #Learning #BuildInPublic

What really makes an app successful on the Play Store? 🤔 I recently completed an in-depth Data Analysis project using the Google Play Store dataset. I explored: • App ratings vs installs • Category-wise performance • Free vs paid app trends 💡 Key Insight: High installs don’t always mean high ratings — user experience matters more. 🛠 Tools Used: Python | Pandas | Matplotlib | Seaborn 🔗 GitHub: https://lnkd.in/dGvJaB7a #DataAnalytics #Python #EDA #DataScience #Visualization #Pandas #Seaborn #LearningJourney

🚀 Excited to share my latest project – Country Capital Finder Web App! 🌍 I built a simple and interactive web application using Python and Streamlit that allows users to quickly find the capital city of any country. 🔍 Key Features: • Search for any country and instantly get its capital city • Displays the country flag along with the result • Clean and user-friendly interface • Built using a lightweight and efficient Streamlit framework 🛠 Tech Stack: • Python • Streamlit • CountryInfo API • PyCountry This project helped me strengthen my understanding of Python application development, APIs, and deploying web apps using Streamlit. You can try the live app here: 🔗 https://lnkd.in/gjnEeNF5 I’m continuously exploring and building projects in AI, Data Science, and Python development. #Python #Streamlit #WebApp #Git #AIProjects #DataScience #MachineLearning #Developer #LearningJourney

Ten Shiny apps. One Electron shell. One very confused laptop. Quick dispatch from the Holy (native) Grail quest: last week we teased Shiny for Python running inside an Electron app on Windows. This week the temple doors creaked open a little wider, and we got the same Shiny app running in five different runtime modes at once, ten apps in total across R and Python, all wrapped in Electron and exported using one R package. The lineup: - R and Python Shiny, side by side - Native flavors: system, bundled, and auto-download - Containerized via Docker - Shinylive for more ephemeral work The dream is the boring one: you write a Shiny app, your non-technical users double-click an icon, and nobody has to learn what a port is. Different runtime modes for different deployment stories, same Shiny app underneath. No public-facing code yet. Parts of this have lived as scattered experiments on my GitHub for years: the current shinyelectron package only does shinylive export, and there was an earlier demo embedding a Docker container inside an Electron app. The new pieces, native auto-download, system, and bundled, are what finally tie it all together. More soon. Screenshot below shows all apps running at once.... #rstats #python #rshiny #pyshiny #electron #shinyelectron #datascience

🚀 Built a QR Code Generator using Flask! 🧪 I recently created a simple yet useful QR Code Generator Web App where users can instantly generate QR codes from text or URLs. 💡 This project helped me understand: • Backend development with Flask 🧪 • Connecting frontend with Python • Handling user input & generating dynamic output ⚙️ 🔗 GitHub: https://lnkd.in/dN8JBRTn Always learning, always building. 💻 Would love your feedback! 🙌 #Python #Flask #WebDevelopment #Projects #Coding #Learning

Remember the Invisibility Cloak? 🫥 Last week's post hit 15,000+ impressions, around 10,000 people reached. I said the next step was a desktop app and an APK. Here is the update. https://lnkd.in/dYen2wvS Desktop app? Done. One file, download, open, run. No Python, no terminal, no setup. Just the cloak doing its thing. Web app? Also done.  Try it here: https://lnkd.in/dWhZDFaB Open it, allow camera, that is it. APK is still in progress but it is coming. The core is still the same Python, OpenCV, NumPy. Code kept clean and documented for future use and applications because this concept goes way beyond a fun demo. Going from a script that only runs on one machine to something anyone can just open and try, that is the part that feels good. We are getting there. #Python #OpenCV #ComputerVision #NumPy #InvisibilityCloak #Tech #Coding #PythonProjects #OpenSource

🚀 From Basic Flask Apps to Real-World Features While learning Flask, I explored two important concepts that make applications more practical: 🍪 Cookies – Help store user data in the browser and improve user experience 📂 File Upload – Allows users to upload images, documents, and more 💡 What I learned: Cookies are useful for tracking users but should be handled carefully File uploads bring real functionality to web apps (like profile pictures, docs, etc.) This step really made me feel like I’m moving from just learning → building real applications 💻✨ Next goal: 🔐 Implementing secure authentication #Flask #Python #WebDevelopment #Backend #LearningJourney #Coding

From UI → working product 👇 Here’s a quick demo of the expense tracker I built using Python 💰 In this version (v1), you can: • Add income & expenses • Track balance instantly • View transaction history • View analytics & insights Built this to better understand my own spending habits — and it turned into a full working app. Currently improving it and planning to deploy it soon 🚀 Watch till the end to see insights 👀 Would love your feedback 🙌 #Python #Streamlit #WebDevelopment #BuildInPublic #SoftwareDevelopment #StudentDeveloper #Projects #LearningInPublic

API for ML system. Hello data points, We create an ML app, but how do users interact with that app? How do the backend, frontend, and other engines talk with the ML app? If you notice, we need a middleman to transfer data from one end to another. That is called an API (Application Programming Interface). I created an API with the FastAPI Python framework. It is an awesome library. It gives us: - auto validation - fields - computed fields - Pydantic models - and a lot more functionality One good part of FastAPI is that it automatically creates a docs page for the user. So I created an API for one of my projects. Because now the journey is to create ML systems, not just ML notebooks or models. Stay connected with data... --- Date: 17-03-2026 | 8:05 IST #rudra #resources #ml #ai #data

How to Create a Weather App: A Step-by-Step Guide for Web and Python At TechTide Solutions, we’ve learned that “weather app” is one of those deceptively simple product labels. On the surface, it’s a search box and a temperature. Under the hood, it’s a real-time data product that depends on external APIs, latency-sensitive UI updates, careful error handling, and respo...