Flux v1.0.0 — Quick Demo ⚡ See how an explainable, adaptive CLI file transfer system behaves in real time. Open Cmd Check your python --version 🛠️ Quick Install pip install flux-download 🔍 Check version python -m flux.cli --version 🖥️ Launch Flux (Dashboard) python -m flux.app ➕ Add a real download (inside Flux) Press:a Paste: Paste some link which you wanted to download Press Enter ⏯️ Pause / Resume: p ❌ Quit q ⚙️ Optional: Headless CLI download python -m flux.cli downloadhttps://lnkd.in/dagknx4e 🧹 Uninstall pip uninstall flux-download This demo shows Flux adapting, explaining decisions, and reacting to network conditions — all inside the terminal. CLI first. Open source always. #cli #opensource #python #terminal #systems #networking #buildinpublic #opensourcecommunity #commandline #devtools #softwareengineering #systemsengineering #terminaltools #linux #windows
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Just released nas-sync-script-builder — a Python GUI that generates a Bash script for safe, one-way NAS sync on Linux using rsync and lsyncd. Perfect for incremental, append-only updates without touching existing NAS files. GitHub: https://lnkd.in/dC_ZmYqU
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How Python Actually Runs? Ever wondered what happens the moment you hit "Run"? Python doesn't just read your code like a book; it goes through a fascinating two-step process to turn your logic into action. Here is the simple breakdown: • The Compilation Phase Before your code executes, Python "compiles" it. No, it doesn't turn it into a Windows .exe file. It transforms your source code into Bytecode. - Think of it as: Translating a complex recipe into a simplified checklist that only a chef understands. - The Result: Those .pyc files you often see in __pycache__ folders. • The Interpretation Phase This is where the Python Virtual Machine (PVM) takes over. It reads the Bytecode line-by-line and executes it on your computer. - Think of it as: The chef following that checklist to actually cook the meal. - The Benefit: This is why Python is "cross-platform" the same Bytecode can run on Windows, Mac, or Linux as long as the PVM is there. 💡 Why should you care? Understanding this model helps you realize why Python is so flexible. It’s an Interpreted language, meaning it’s optimized for developer speed and ease of use, even if it trades off a little bit of raw execution power. #Python #DataEngineering #DataScience
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For those who don't know Mustel... Python environment management, simplified. 🦦 We just released Mustel v0.1.3, making it easier than ever to inspect and maintain your Python workflows. If you've ever struggled with "ModuleNotFoundError" when you know the package is installed, Mustel is for you. It gives you immediate visibility into your active environment and system installation. New in v0.1.3: 🛠 Virtual Environment Manager: Create and list venvs easily. 🩺 Maintenance Tools: Specific commands like mustel doctor and mustel clean to keep your setup healthy. ⚡ Broken Venv Detection: Automatically finds and helps fix broken environments (including OneDrive sync issues). Install now: pip install mustel Learn more: 📜 Docs: https://lnkd.in/dyrxjVEi 📦 PyPI: https://lnkd.in/dn2MFe-G We still are under heavy development! #Python #SoftwareEngineering #OpenSource #CLI #DeveloperTool
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As multi-agent systems become more and more popular, I'm leaving a small tool i made for myself as opensource. SocketBridge — a tiny, stdlib-only TCP bridge for agent↔agent (and agent↔tool) chats. - Length‑prefixed JSON (no partial reads) - Loopback-by-default + optional auth token + host allowlist - Max-bytes cap and protocol versioning - Zero dependencies (pure Python) Use it as a side-band channel between agents or harnesses. Install: pip install socketbridge Repo: https://lnkd.in/eezCCWc8 #python #opensource #agents #ipc #security #devtools
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Python: The Modular Reference Guide 🐍 In software development, we often rush to complex frameworks without mastering the modular fundamentals. I recently reviewed a comprehensive reference guide that breaks down the Python ecosystem beautifully. Here are the 4 pillars of Python structure every developer should master: 1. The Environment ⚙️ Whether you are on Windows (using the official installer for control), macOS (Homebrew vs. Official), or Linux (apt/yum), setting up your path correctly is step one. 2. Control Flow & Logic 🔀 Writing clean code means mastering the flow. Loops: Know when to use while (reiterates as long as true) vs. for (iterates over a sequence). Scope: Understand that variables defined inside a function are Local, while those outside are Global. 3. Data Structure Selection 📊 Choosing the wrong structure costs memory and speed. Need constant data? Use a Tuple (1,2). Need key lookups? Use a Dictionary {'key': 'value'}. Need an ordered, mutable collection? Use a List [1,2]. 4. Exception Safety 🛡️ "Live to learn & learn to share." Part of that is writing safe code. Always close your files after use and utilize try/except blocks to prevent runtime crashes. The difference between a script that runs and a script that scales is often just adherence to these basics. Which Python feature do you find yourself using the most in your daily workflow? (I'm a huge fan of List Comprehensions for concise syntax! ) #Python #SoftwareDevelopment #CodingBestPractices #DataStructures #Programming #TechCommunity
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PdfItDown, the python library I created to convert (almost) any file format to PDF, has now an MCP server!🚀 Built on top of FastMCP and running over stdio transport, PdfItDown MCP server allows your agents to seamlessly convert one or more files to PDF in one go! 📦 Install with: 𝘶𝘷 𝘵𝘰𝘰𝘭 𝘪𝘯𝘴𝘵𝘢𝘭𝘭 𝘱𝘥𝘧𝘪𝘵𝘥𝘰𝘸𝘯-𝘮𝘤𝘱-𝘴𝘦𝘳𝘷𝘦𝘳 📚 Take a look at the docs: pdfitdown.eu ⭐ Star the repo on GitHub: https://lnkd.in/dQs6ZKj3
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Magic Wormhole for the win 🤠💪🏻🚀 Magic Wormhole: Open-source CLI alternative with no size limits, using relay servers and code phrases for pairing. Great for tech users handling arbitrary large files/directories, but requires Python installation and command-line knowledge.
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🛠️ Stop wasting time on boilerplate: Introducing 'mkf' As a developer who lives in the terminal, I believe in automating the repetitive to focus on what matters: the architecture. I built mkf, a high-efficiency CLI tool designed to bootstrap modular, production-ready FastAPI applications with a single command. What it automates: 📦 Virtual Environment (venv) setup. 🛠️ Git initialization. 🏗️ Modular Boilerplate generation for scalable backends. If you are looking for a faster way to start your Python projects. 🚀 Get it running in seconds: pipx install mkf 📂 Repository: https://lnkd.in/greWRFx5 #Python #FastAPI #DevOps #Automation #Linux #BackendEngineering
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You can expose a FastAPI app as an MCP server with almost no effort. There is now a simple way to convert an existing FastAPI service into an MCP-compatible server using a single line of code. No extra configuration, no separate server process, and no custom wrappers to maintain. This makes it much easier to plug FastAPI backends directly into agent workflows without changing how your app is built or deployed. Repository link is in the comments 👇 #FastAPI #MCP #AIAgents #DeveloperTools #BackendEngineering #Python #OpenSource
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Pyodide compiles CPython to WebAssembly, letting developers run full Python directly in the browser without servers or installations. By Jessica Wachtel
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