StratagemGIS Solutions’ Post

My puppy friend is getting smart...generatively smart! (that's not a word, but so what) Puppy is a CLI tool that generates isolated #python #environments via pixi and uv, in complete isolation from your system - everything lives in one folder. Here's the commands it learned so far: pup --help Usage: pup.py [OPTIONS] COMMAND [ARGS]... Commands:  fetch  Fetch (install) packages with uv.  kernel Interactively create new ipython kernel linked to 🐶's...  list   List packages.  new    Create a new virtual environment in <WHERE> folder.  which  Show 🐶's current home. And now...  play   Launch jupyter notebook with added code cells. Puppy will generate, execute, and open your Jupyter notebooks, and even populate them with external scripts. Are you thinking what I'm thinking? Link to 🐶 in the comments!

𝐒𝐭𝐫𝐮𝐠𝐠𝐥𝐢𝐧𝐠 𝐭𝐨 𝐈𝐧𝐬𝐭𝐚𝐥𝐥 𝐉𝐮𝐩𝐲𝐭𝐞𝐫 𝐍𝐨𝐭𝐞𝐛𝐨𝐨𝐤 𝐯𝐢𝐚 𝐂𝐨𝐦𝐦𝐚𝐧𝐝 𝐏𝐫𝐨𝐦𝐩𝐭? 𝐇𝐞𝐫𝐞’𝐬 𝐇𝐞𝐥𝐩! Installing Jupyter Notebook can sometimes feel tricky, especially if you’re new to command-line tools or Python environments. If you’ve been stuck with errors or don’t know where to start, this video is for you! I’ll walk you through the step-by-step process to get Jupyter up and running on your system seamlessly. Whether it’s installing via pip, managing dependencies, or resolving common issues, this guide will make it simple. Say goodbye to installation headache 🤕 let’s get your Jupyter journey started! The installation guide is can also be found via the link below https://bit.ly/3CHTwBP

#Buildinginpublic #Day12 #100Daysofcode #Python Finally broke through utilizing github and example notebooks on how to use Zipline Reloaded library. I had been stuck trying to make it work for a few days. Meanwhile, I kept going, reviewing where I was going wrong and lacking in skills to get zipline working. Zipline Reloaded and VectorBT are powerful backtesting libraries. I had to review a lot of basics to understand example notebooks. The video shows results for a mean reversion strategy for 25 stocks based on standard deviations of their monthly returns from annual average. Thanks to PyQuant News 🐍 to make it easy to understand.

Having a hard time installing Jupyter Notebook via the command prompt? You're not alone! Let's tackle it step by step and make coding smoother. 🚀💻

#!/bin/bash # Install required dependencies sudo apt-get update sudo apt-get install -y git python3 python3-pip # Clone the repository git clone https://lnkd.in/gZNacKng # Enter the repository directory cd LTE-Cell-Scanner # Install Python dependencies pip3 install -r requirements.txt # Run the script python3 lte_cell_scanner.py

Let’s face it: `pip` gets the job done, but it’s not winning any speed awards. 🏆 That’s where uv comes in. Written in Rust, uv is an incredibly fast Python package installer and resolver designed as a drop-in replacement for `pip` and `pip-tools`. Whether you’re installing new packages or resolving complex dependency chains, uv does it faster and more efficiently. In this week’s video, I’ll walk you through: 🔹 How uv works under the hood (hint: Rust gives it superpowers) 🔹 Why it’s faster than `pip` 🔹 How to seamlessly switch to uv without breaking your existing workflow Stop wasting time on slow installs. Watch the full breakdown here: https://lnkd.in/e6FsKC5Z #PythonDevelopment #UvPackageInstaller #FastDependencyResolution #PythonTools #ArjanCodes

💡 Here’s a game-changer: uv generates lock files that are fast, reliable, and consistent across environments. No more dependency surprises on deployment! Just run `uv lock` to lock down your requirements and ensure smooth installs every time. 🚀 This is just one of the powerful features I cover in my latest video about uv, the lightning-fast Python package installer built in Rust. Want to see how uv can transform your workflow? 🎥 Watch the full video now: https://lnkd.in/e6FsKC5Z #PythonTips #UvInstaller #DependencyManagement #FastPython #ArjanCodes

For the past couple of years, I’ve been developing backends primarily in Python—roughly 80% of the time—leaving a trail of virtual environments (venvs) scattered across my PC. Yesterday, I decided to tackle this chaos and developed a CLI tool (of course, in Go) to manage all my venvs efficiently. Introducing venv-manager: A simple and lightweight tool that organizes all your virtual environments into a single folder (.venvs in your home directory). With venv-manager, you can easily list, delete, and perform other operations on your venvs. - No dependencies—just pure Go. - One-command installation (no need to clone or set anything up manually). If this sounds like something you’d find useful, check out the repo and give it a ⭐ on GitHub to stay updated! https://lnkd.in/deCvxW5s

IMOS has created a series of Python Jupyter Notebooks to help users access, visualise, and work with IMOS data. These interactive tools allow users to combine text, code, and visualisations in a single document, as well as extract data specific to user requirements. A total of 10 Notebooks are available, each with GitHub and interactive versions. Explore all Notebooks here 🔗 bit.ly/47ZlIMe #NCRISImpact

Check out this demo for a basic financial management app I built using python and the kivy framework. I wanted a concrete and free way to manage money over the summer, so thought, “why not build a free application?” Let me know what you think! Source code is located on my GitHub account.