How Python simplifies cross-platform development

Ever wished your Linux terminal could do exactly what you want? Well, it can — with a little help from Python. 🐍💻 I just published a new blog where I show how to turn a simple Python script into a fully functional Linux command — one that works just like ls or grep. No heavy dependencies. No complex setup. Just pure Python + Linux power. ⚙️ If you love coding, automation, or just enjoy bending your terminal to your will — this one’s for you. 👉 Read it here: [https://lnkd.in/gPN-DbFi] #Python #Linux #Automation #Coding #Developers #Productivity #CommandLine #TechCommunity #Trading #AlgoTrading #Quant #DataScience #DevOps #Developers #CommandLine #Coding #WorkflowAutomation #OpenSource #TechInnovation

After dealing with a messy Python setup, I have decided to write this blog A quick guide on when (and how) to uninstall all Python packages safely across Windows, macOS and Linux Read it here 👉 https://lnkd.in/dy7DJQuQ How do you keep your Python setup clean - venv, Conda, pyenv, or something else? #Python #Developers #Programming #pyenv

💭 Why not the documentation? There was a time when programmers lived in documentation — it was the only way to learn a technology. Now? Just open YouTube. Tutorials everywhere. Back then, if you wanted a library or package, congratulations — you had to build it yourself, often from scratch in C or C++. Today, we have over 500,000 packages for just one language — Python. The result? Programmers are getting comfortable, even dummy-proofed. From the legendary Linus Torvalds writing the Linux kernel… …to a 12-year-old launching a SaaS company today — the landscape has completely changed. Maybe it’s progress. Maybe it’s dilution. But it definitely makes you think. *DON’T BE A DUMB PROGRAMMER DIVE DEEPER* #Programming #Developers #Technology #Python #CodingLife

💡 Python + Ubuntu = Automation Powerhouse I’ve been using Python scripts on Ubuntu to automate everyday system tasks — from log cleanup and data backups to monitoring services. Some of my go-to tools and modules: • subprocess → run shell commands • os and pathlib → manage files & directories • crontab → schedule jobs • psutil → monitor system performance It’s amazing how much efficiency you can achieve with just a few lines of Python code. Anyone else here using Python for Linux automation? Would love to exchange ideas! #Python #Ubuntu #Automation #Linux #Scripting #DevCommunity

What’s New for Python on App Service for Linux: pyproject.toml, uv, and more. Python apps on Azure App Service for Linux just got a lot easier to build and ship! We’ve modernized the build pipeline to support new deployment options —whether you’re on classic setup.py, fully on pyproject.toml with Poetry or uv, or somewhere in between. This post walks through five upgrades that reduce friction end-to-end—from local dev to GitHub Actions to the App Service build environment: pyproject.toml + uv (and poetry): modern, reproducible Python builds setup.py support .bashrc quality-of-life improvements in the App Service container shell GitHub Actions samples for common Python flows (setup.py, uv.lock, local venv, and pyproject.toml deployments) pyproject.toml + uv uv is an extremely fast Python package & project manager written in Rust—think “pip + virtualenv + pip-tools,” but much faster and with first-class project workflows.... #techcommunity #azure #microsoft https://lnkd.in/gJaAdxzg

I just created a Linux System Call Table for easy reference — a simple Markdown reference listing syscall numbers, names, descriptions, and prototypes for x86_64 Linux. I hope it’ll also be helpful for developers, system programmers, and learners who want to explore and understand how Linux system calls are structured. I’ve also included the Python script that lets you generate or update the table directly from your own system — so it stays up to date across kernel versions. 👉 Check it out and feel free to contribute: https://lnkd.in/dHan2dVM #Linux #OpenSource #Syscalls #Programming #Python #Documentation

🚀 #PythonJourney | Day 76 – Python + Linux in Action Day 76 of my Python journey, and today I went hands-on with Python inside Linux — coding directly in the terminal using Neovim. 🐍🐧 This setup is simple, fast, and perfect for staying focused on logic and clean code. Writing Python scripts directly in the terminal brings full control over the environment and reinforces the connection between Linux and automation. 🎯 Today’s Focus: Working with Python scripts in the Ubuntu terminal Key takeaways from today: ✅ Developing in Linux helps you understand what happens under the hood ✅ Neovim provides a minimal, distraction-free coding experience ✅ The combination of Python + terminal is ideal for automation and scripting ✅ Saving data in JSON or text files is a practical way to persist information 💡 Why it matters: Building tools directly from the Linux terminal trains discipline, precision, and focus — skills every backend developer needs. 🧠 Screenshot: my Ubuntu terminal running Neovim while coding today’s exercise. #Python #Linux #Neovim #Automation #DevJourney #BackendDevelopment #LearningByDoing

Compiling Python to Run Anywhere The Future of Code Portability Ever wished your Python code could run natively on any platform from servers to smartphones without needing the heavy Python runtime? That’s exactly what this new approach is tackling. Instead of relying on interpreters or containers, it compiles plain Python into optimized C++ binaries that run anywhere Linux, macOS, ARM, or even WebAssembly. What makes it special: Writes pure Python no DSLs or weird syntax. Uses AI-assisted code generation to create native backends automatically. Compiles multiple variants for different devices and picks the fastest one. Opens up huge potential for AI workloads, edge computing, and lightweight deployments. Sure, there are limits (not all Python magic works yet), but the direction is crystal clear Python’s flexibility + C++’s performance + global portability = a new era for developers. If this vision lands, we might soon ship Python apps like we ship Go binaries. #Python #AI #DevTools #Performance #OpenSource #SoftwareEngineering

Setting Up cocotb on Ubuntu 22.04+ with PEP 668: A Complete Guide In the past, older versions of cocotb could be installed directly into the system Python, but modern Linux distributions—especially Ubuntu 22.04 and 24.04—now enforce PEP 668, which blocks system-wide pip installations to protect the OS from dependency conflicts. Because of this restriction, it is recommended to install cocotb in a virtual environment to isolate Python packages, avoid OS conflicts, and ensure that cocotb, simulators, and testbench dependencies all work consistently without interfering with system Python. cocotb is a Python-based verification framework, so Python is mandatory. Since Ubuntu blocks system-wide pip installs, we need to install the cocotb package inside a virtual environment. We also require Icarus Verilog and GTKWave to perform simulation and analyze waveforms. Once all mandatory dependencies are installed, we are ready to run code with Icarus: Python3 → pip3 → Icarus → cocotb. Newer versions of cocotb have completely removed BinaryValue as the main class used to represent HDL values in Python. With the removal of this class, we now need to use Logic or LogicArray. Logic is used to pass HDL values (1, 0, x, z) in Python for single-bit variables, while LogicArray is used to pass multi-bit HDL values in Python. Now we need to create three files: one for the design code in SystemVerilog, one for the testbench code in Verilog, and finally a Makefile to specify the top files. After that, we can run the code by calling “make sim=icarus”. Learn how we do RTL verification in Python from scratch here: https://lnkd.in/djVjPEMy