Introducing proxyml: Open Source Python SDK for Privacy-Preserving Model Explainability

If you're a Python developer and you're not using tools like ruff, black, pytest, mypy, py-spy and pre-commit, then you're probably behind the curve. All these tools are free to download and use in your projects, and WILL make your code better and less buggy. My latest article on Towards Data Science goes into more depth on all the above-mentioned tools and shows how to download and use each one. A link to the article is in the first comment.

Have you ever been to dependency hell? A situation where a Python library version is causing a problem in your environment, but you don’t know which library it is and which version you should choose to fix it. Plotly staff member, Celia López Monreal, created a Plotly Dash App to debug dependency issues. More precisely, the app gets insights into library versions that might be causing issues in your Python environment. https://lnkd.in/eEKZYPmj

The Model Context Protocol, or MCP, has changed how LLMs connect with data and tools. It can expose data as resources, provide actions through tools, and define prompts that guide how the model interacts with data or users. In this guide, Manish teaches you how to build your own MCP server using the FastMCP Python framework. https://lnkd.in/gCwmUgr5

My biggest mistake early in my Python journey wasn’t bad code. It was ignoring the small tools that make systems reliable. After 4+ years building automation projects, I found a handful of libraries that quietly transformed my side projects into production-ready products. I wrote about the exact 8 libraries I rely on today. Check out the full breakdown on my Medium account.

one important part of controlling kubernetes clusters is a monitoring tool. However, taking a look at that tool sometimes and very often we cannot understand what is going on and what further steps to solve it are. Therefore, I have created a diagnostic web tool in order to make suggestions and recommendations with issues on clusters. It has a report system as well. Here is the GitHub repo where you can either run as a python script or use docker compose file. Please try to diagnose your cluster. Thanks https://lnkd.in/efEsRDXW

I built a Log inspector, a Python tool that parses system log files, filters errors, generates per-user statistics, and exports reports as CSV or HTML. What it does: Parses system logs using regular expressions (regex). Filters by error type or specific user. Generates ranked error summaries. Exports reports as CSV or HTML What I learned building it: How to refactor a monolithic script into modular, reusable functions. Separation of concerns like parsing, reporting, and logic in separate files. Writing unit tests with unittest to catch edge cases. Using Git and GitHub to manage and publish a project. This project builds on concepts from the Google IT Automation with Python Certificate but focuses on solving a real-world problem engineers face daily: understanding system logs efficiently. 🔗 GitHub: https://lnkd.in/dJ3maRBW If you work with system logs or automation tools, I’d love your feedback! #Python #Automation #ITAutomation #Regex #GitHub #GoogleCertificate #Coursera #LogAnalysis #Programming

uefi-firmware, Stack out-of-bounds write, CVE(N/A) (Medium) The vulnerability resides in the `MakeTable()` function of the native Tiano/EFI decompressor used by the `uefi-firmware` Python package. The flaw is triggered when the decompressor processes a specially crafted firmware blob. The function `MakeTable()` reads bit-length values from a compressed bitstream but does not validate that these values fall within the expected range of 0 to 16 inclusive. An attacker can supply bit-length values greater than 16, which causes an out-of-bounds write to the stack-allocated `Count` array and other decode tables....

uefi-firmware, Stack out-of-bounds write, CVE(N/A) (Medium) The vulnerability resides in the `MakeTable()` function of the native Tiano/EFI decompressor used by the `uefi-firmware` Python package. The flaw is triggered when the decompressor processes a specially crafted firmware blob. The function `MakeTable()` reads bit-length values from a compressed bitstream but does not validate that these values fall within the expected range of 0 to 16 inclusive. An attacker can supply bit-length values greater than 16, which causes an out-of-bounds write to the stack-allocated `Count` array and other decode tables....

Django REST Framework Authentication Authentication is the backbone of secure APIs, yet it’s often misunderstood. In my latest deep-dive, I break down Basic, Session, and Token Authentication in Django REST Framework with real-world examples, edge case analysis, and production-ready insights. 🔑 Key takeaways: Authentication ≠ Permissions Why BasicAuth is risky in production without HTTPS The hidden CSRF pitfalls of SessionAuthentication How TokenAuthentication works, its limitations, and why tools like Knox or JWT are better for scaling Practical code snippets for login, logout, and securing views Read the full article here: https://lnkd.in/dmiTxTp4 #Django #RESTAPI #Authentication #Python #WebDevelopment #Security

🚀 Built a Password Manager in Python 🔐 📅 Day 29 of #100DaysOfCode Continuing my journey, I developed a Password Manager that helps securely store and manage login credentials. 🔹 Key Features: • Generate strong and secure passwords • Save website credentials (email & password) • Data stored using file handling • Simple and clean user interface 💡 What This Improved: • Understanding of data persistence • Working with file handling in Python • Building utility-based real-world projects • Improving UI logic and user input handling 🔗 GitHub Repository: https://lnkd.in/dGPM65fY More improvements coming soon as I continue building and learning 🚀 #Python #100DaysOfCode #ProjectBasedLearning #GitHub