Stop waiting for pip. Start using uv. ⚡ If you’re still using traditional tools to manage Python environments, you’re losing hours to loading bars. I’ve been diving into uv lately, and it’s a total game-changer for Python development. It’s a single tool (written in Rust) that replaces pip, venv, pip-tools, and pyenv. Why I’m switching: Insane Speed: It’s 10x–100x faster than pip. No hyperbole—it’s nearly instant. All-in-One: It manages your Python versions, virtual environments, and packages in one place. Reliability: It creates a uv.lock file by default, making deployments to VPS or containers 100% reproducible. Modern Features: It can run single-file scripts with inline dependencies automatically. Whether you're building FastAPI bots or complex data pipelines, your time is too valuable to spend watching packages install. Have you made the switch to uv yet, or are you sticking with the classic pip? #Python #SoftwareEngineering #Rust #DeveloperTools #OpenSource #Programming
Boost Python Development with uv: Faster, All-in-One Solution
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Day 2/30 – Building with Python Recently, I worked on a Vehicle Feedback System using Python The idea behind this project was to create a simple system where users can: 📝 Submit feedback about vehicles 📊 Store and manage responses efficiently Through this project, I learned: ✨ How to handle user input and data ✨ Basic logic building and structuring a program ✨ The importance of user-friendly systems This is just the beginning — I’m planning to improve it further by adding: OTP-based authentication for better security Database integration for scalability Possibly a simple UI for better user experience Building projects like this is helping me understand how real-world systems evolve step by step Would love your suggestions or ideas to improve this further! #Day2 #PythonProject #LearningInPublic #StudentDeveloper #BuildInPublic #TechJourney
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🚀 Day 3/100: Mastering Logic Flow & Decision Making! 🏝️ The #100DaysOfCode journey is heating up! Today was all about Control Flow and Conditional Logic in Python. I built a "Treasure Island" text adventure game to practice: ✅ Nested if/elif/else statements ✅ Complex logical operators (AND / OR) ✅ Managing user input edge cases Understanding branching logic is a massive step toward building robust automation scripts and handling real-world data scenarios. ⚔️ Check out my code here: 🔗 https://lnkd.in/gxyRjpGh Onward to Day 4! 🚀 #Python #100DaysOfCode #LogicBuilding #Programming #DevLife #GrowthMindset #CodeNewbie
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🚀 𝗗𝗮𝘆 𝟮𝟱/𝟯𝟬 – 𝟯𝟬 𝗗𝗮𝘆𝘀 𝗼𝗳 𝗣𝘆𝘁𝗵𝗼𝗻 𝗣𝗿𝗼𝗷𝗲𝗰𝘁 𝗖𝗵𝗮𝗹𝗹𝗲𝗻𝗴𝗲 Continuing my journey of building one Python project every day to improve consistency and real-world problem-solving. Today’s focus: File Handling & PDF Automation 🧠 𝗣𝗿𝗼𝗷𝗲𝗰𝘁: 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗰 𝗣𝗗𝗙 𝗣𝗮𝗴𝗲 𝗦𝗽𝗹𝗶𝘁𝘁𝗲𝗿 Built a simple Python tool that splits a multi-page PDF into individual pages and saves them automatically in the same directory. ✨ 𝗙𝗲𝗮𝘁𝘂𝗿𝗲𝘀: • Split PDF into single-page files 📄 • Automatically saves files in the original folder 📂 • Fast and lightweight ⚡ • Clean and minimal code structure 🧩 💡 𝗖𝗼𝗻𝗰𝗲𝗽𝘁𝘀 𝗨𝘀𝗲𝗱: • File handling in Python • Working with PDFs using pikepdf • OS module for path management • Looping and automation 🔗 𝗚𝗶𝘁𝗛𝘂𝗯: https://lnkd.in/dmiQStmG A small but powerful utility that solves a real-world problem efficiently. Building discipline through code — one project at a time. Follow along as I complete 30 Python projects in 30 days 🚀 #Python #BuildInPublic #DeveloperJourney #30DaysOfCode #PythonProjects #Automation #PDF #Coding #Learning
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We spent years asking Python to orchestrate, sandbox, schedule, and run concurrent tasks while pretending the GIL wasn't there laughing at us. Two shifts are quietly fixing that... 1.) Hybrid runtimes like #OpenFANG let Rust handle sandboxing and execution while Python defines the workflow. Declarative glue,,, which is what most of us were using it for anyway. 2.) #Agents now generate Python instead of chaining tool calls. The old loop, #LLM tool LLM tool LLM tool, burned tokens for sport. Now the model emits one small program, runs it once, and several reasoning steps collapse into a single cycle. The two fit together. A hardened runtime makes generated code less terrifying, and generated code makes the runtime worth having. #Python is the language of intent. #Rust is where intent actually runs. Still chaining one call at a time... fair enough. Your token bill will tell you when...
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🚀 Built a Python Quiz Game Engine: Here’s What I Learned I recently developed a fully functional Quiz Game Engine in Python designed with scalability, clean architecture, and real world usability in mind. 🔍 Key Highlights: Multiple question types (Q&A, MCQ, True/False) Time-based answering system using multi-threading JSON Schema validation for structured data integrity Automated scoring + CSV-based result tracking Modular and type-safe code design This project pushed me to think beyond “just making it work” focusing instead on: ✔ Clean architecture ✔ Input validation ✔ Real-world usability ✔ Performance under constraints (timers) 💡 One interesting challenge: implementing a thread-safe timer system without external libraries. If you're learning Python, don’t just build scripts build systems. 🔗 Check it out: https://lnkd.in/deba_WM7 #Python #SoftwareEngineering #OpenSource #Projects #LearningByDoing #Programming
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I've been building a small computer vision project: An alertness-oriented monitor that runs YOLOv5 on a live webcam feed. I labeled data, trained a custom model, wrapped inference in a Dockerized API (FastAPI with Python), and built a React frontend for it that streams the camera and overlays detections in real time with different colours for states like awake vs drowsy. It's a fun end-to-end slice: data -> training -> API -> browser. Code's on my GitHub if you're curious. https://lnkd.in/eMrw3vyn
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I’ve been spending my recent free time in building an Event-Driven Backtesting Engine from scratch for Options. Backtesting complex option strategies requires processing massive amounts of market data, calculating Greeks, and tracking portfolio metrics simultaneously. To handle this without latency bottlenecks, I decided to architect the entire core engine in C++. for now I have mostly tried to make it very flexible like modular commission and slippage and ability to write custom strategies instead of editing the core engine itself I completely decoupled most of the core things so The entire C++ backend is compiled as a standalone library. I am also trying to Integrate a python bridge using pybind11 exposing this compiled library directly to Python. The goal for this is to make the engine to do all the computation in the background, allowing anyone to write, test, and plug in custom strategies dynamically using simple Python scripts without ever needing to modify the core engine files. Getting the C++ event loop to work good with Python scripting is proving to be a little complicated right now! I'll be pushing a final README and some sample strategies once I get the bindings fully stabilized. You guys can check out the code here : https://lnkd.in/gRSgd4gs #quantfinance #cpp #python #algorithmictrading #options #pybind11 #derivatives
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Today’s Python lesson felt like the moment code stopped being just instructions and started feeling reusable, flexible, and kind of smart. 🐍 Day 14 of my #30DaysOfPython journey was all about higher order functions, and this one made Python feel a lot more powerful. In Python, functions are first-class citizens, which means they can: 1. take other functions as parameters 2. return functions as results 3. be modified 4. be assigned to variables Today I also explored: 1. Functions as parameters 2. Functions as return values 3. Closures — where an inner function can use the outer function’s scope 4. Decorators — a clean way to add extra behavior without changing the original function 5. Built-in higher order functions like: i. map() → transforms items ii. filter() → keeps only matching items iii. reduce() → combines items into one value What stood out to me today was how Python lets functions do more than one job. They are not just blocks of code anymore — they can actually shape how other code behaves. One more day, one more topic, one more step toward thinking in cleaner, more reusable logic. Which one feels the most interesting to you right now: map(), filter(), reduce(), or decorators? Github Link - https://lnkd.in/gc-mj8Qi #Python #LearnPython #CodingJourney #30DaysOfPython #Programming #DeveloperJourney
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gdown v6 is out. Biggest changes this time: - Folder downloads work with more than 50 files (this was annoying for everyone for a long time) - download() raises DownloadError on failure (instead of returning None) - New progress callback - All deprecated v5 APIs finally removed - Python 3.10+ 33 pull requests, 109 commits since v5.2.1. https://lnkd.in/gRAegKhj
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🧠 I built my own programming language — and here it is running on CLI. This is GreyMatter — a custom interpreted language I built from scratch using Python and SLY. What you're seeing in this terminal: → The GreyMatter interpreter starting up (v0.01) → A variable being assigned: a = 50 → An IF/ELSE conditional executing in real time → Output: a is even ✅ The entire interpreter was built by me — from the Lexer and Parser to the AST and Runtime Engine. Why did I build this? Because the best way to understand how Python, JavaScript, or any language works... is to build one yourself. Every keyword you type, every error you get, every output on your screen — there's an entire pipeline behind it. Building GreyMatter made me truly understand that pipeline. 🔗 GitHub: github.com/Abineshabee Drop a 🧠 in the comments if you'd like to see more about how it works! #Python #Programming #OpenSource #BuildInPublic #ComputerScience #InterpreterDesign #GreyMatter #StudentProject #Ben10
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