Python Devs: init-app Simplifies Project Setup with Flask, Django & More

While I realize Shell stays stable with timeless commands, Python battles dependencies, so efficiency comes down to stability vs flexibility. grep, awk, cat, and ls work anywhere instantly, Python may require installing and managing libraries to parse the same file. #AIScripting #AI #FutureOfWork #SRE #DevOps

IO Ninja and Python Can Jam Together. As you know, IO Ninja excels as a UI debugger for serial, network, USB, and all other forms of communication. It offers a slick, polished user interface, a beautiful and lightning-fast logging engine, a sophisticated hex packet editor with packet templates, regex-based data markup, and many other powerful features. Read more via Tibbo: https://lnkd.in/dxyzDyft

Save on your API costs. Chipotle's support bot writes Python for free. Two people sent this to our Slack at the same time last night. The bot wrote a full linked list reversal, then casually pivoted back to taking their order.

🐍 Python Roadmap Want to master Python? Here’s a simple roadmap: 🔹 Basics – Syntax, variables, conditionals, functions, data structures 🔹 Advanced – List comprehensions, generators, decorators, regex 🔹 DSA – Arrays, stacks, queues, trees, recursion, sorting 🔹 OOP – Classes, inheritance, methods 🔹 Data Science – NumPy, Pandas, Matplotlib, Scikit-learn, TensorFlow, PyTorch 🔹 Web Dev – Django, Flask, FastAPI 🔹 Automation – Scripting, web scraping, GUI automation 🔹 Testing – Unit testing, integration testing, TDD 🚀 Learn → Practice → Build projects = Python mastery. #Python #Programming #Coding #Developer #DataScience #100DaysOfCode

🐍 Python Roadmap Want to master Python? Here’s a simple roadmap: 🔹 Basics – Syntax, variables, conditionals, functions, data structures 🔹 Advanced – List comprehensions, generators, decorators, regex 🔹 DSA – Arrays, stacks, queues, trees, recursion, sorting 🔹 OOP – Classes, inheritance, methods 🔹 Data Science – NumPy, Pandas, Matplotlib, Scikit-learn, TensorFlow, PyTorch 🔹 Web Dev – Django, Flask, FastAPI 🔹 Automation – Scripting, web scraping, GUI automation 🔹 Testing – Unit testing, integration testing, TDD 🚀 Learn → Practice → Build projects = Python mastery. #Python #Programming #Coding #Developer #DataScience #100DaysOfCode

Andrej Karpathy’s 630-line Python script ran 50 experiments overnight without any human input: On the night of March 7, Andrej Karpathy pushed a 630-line Python script to GitHub and went to sleep. By The post Andrej Karpathy’s 630-line Python script ran 50 experiments overnight without any human input appeared first on The New Stack. Read more: https://lnkd.in/ge23_upv 📈 Accelerate your DevOps journey! Join our community for expert advice, career tips, and industry news.

Machine Learning Data Visualization using Pyecharts #machinelearning #datascience #datavisualization #pyecharts Pyecharts is a Python library, serving as a class library that allows you to effortlessly generate interactive and visually compelling charts using ECharts, an open-source data visualization JavaScript library developed by Baidu. With Pyecharts, users can easily create dynamic and customizable charts for data visualization in web applications or Jupyter notebooks. The Pyecharts library uses Echarts to generate charts. Pyecharts library provides the interface between Python and Echarts. The Pyecharts work usually like we use visualization library in Python or R in our Jupyter Notebook. Pyecharts have flexible configuration options, so you can easily match the desired chart you want to make. Detailed documentation and samples to help developers get started the faster project. This Pyecharts library supports the chained calls and can easily integrate them into Flask, Django Web framework, and other mainstream. https://lnkd.in/g2VzqRJm

💻 Docker Practice: Optimizing Image Size Today I practiced reducing the footprint of my Docker images by switching to a lightweight base. 💠 Base Image Swap: Switched the Dockerfile from a standard slim image to python:3.12-alpine. 💠 Efficient Packaging: Rebuilt the application (optimizedapp) to see the impact on storage. 💠 Result Analysis: Successfully shrunk the image size from 183MB down to just 72.5MB. 💠 Verification: Ran the container to ensure the Alpine-based environment still executes the Python script perfectly. #Docker #Optimization #AlpineLinux #DevOps #CloudComputing #Efficiency #Backend

Switched our core microservices from Node/Express to Django and FastAPI recently as we pivot to an "AI-First" model. Honestly, the difference for complex business logic is stark. With Python, I find I spend less time managing async state and more time actually defining the transformations. Django’s ORM handles migration headaches, and FastAPI’s Pydantic validation keeps my data models clean before hitting Supabase. It just feels tighter when dealing with LLM pipelines. Anyone else seeing better velocity on heavy backend lifting by leaning into Python frameworks now? #BackendDev #FastAPI #Django #Python

The useful part of most AI code review tools fits in about 300 lines of Python. The other 100,000 are SaaS overhead. Fetch the diff. Chunk by file. One prompt per chunk with the PR description for context. One LLM call. Structured output posted as comments. Three cents. Three dependencies. Runs as a GitHub Action. A generic tool reviews generic code. Yours should know your conventions, your edge cases, your architecture. I open-sourced a reference implementation. Fork it, strip it, own it. Stop buying LLM wrappers. https://lnkd.in/gqgqY2Sk #AIEngineering #MultiAgentSystems #SoftwareArchitecture #OpenSource