LiteLLLM [compromised] - Python library and proxy server that makes applications Llm-agnostic - Was a catchy phrase that I thought was going to help with model switching efficiently instead of custom code... until... it was found out that, it contains litellm_init.pth with base64 encoded instructions to send all the credentials it can find to remote server + self-replicate!! Another reason why you don't want to just blindly follow the "Agent" hype with a a flashy site, PiP install and use it in prod. . https://lnkd.in/g5NDyj8C
LiteLLLM Compromised: Credentials Exposed via Base64 Encoding
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I've been concentrating on reimplementing Helix's RAG implementation to use our code intelligence (See https://lnkd.in/eMGtMqE4). Previously we've tried and experimented with other open source libraries and implementations. But honestly the speed and simplicity of doing everything in go is a breath of fresh air. It needs more work but soon we'll be able to remove multiple containers from the Helix stack, remove a lot of Python scripts, and it will be more performant.
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🚀 Shemul v1.0.1 is live from March 20, 2026 Your favorite project-aware CLI for Python just got smoother ⚙️ Organize all your repetitive commands in one place with shemul.json and run them with a clean, simple CLI 💻✨ No more messy scripts. No more forgotten commands. 📦 Install / Update: 👉 https://lnkd.in/gXhn-iSE 🌐 Learn more: 👉 https://lnkd.in/g58VTVDv #Shemul #Python #CLI #DevTools #OpenSource #Automation #STechBD
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45 seconds to install packages with pip. 3 seconds with uv. Same project. Same dependencies. I have used pip for years and never questioned it. Recently tried uv while setting up a new project and the difference caught me off guard. It is not just faster. It completely changes how you set up and manage a Python project. One tool replacing what used to take four. The image breaks down what is actually happening under the hood and why the difference is this big. Have you come across anything that changed how you manage Python projects? #Python #DataEngineering #uv
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With sub-scripting you can take a single function code and turn it into various types of automated processes -> nano Cloudy_Day.py [input python code] -> python3 Cloudy_Day.py thats decent , but: for i in {1..50} do nohup python3 Cloudy_Day.py > cd_$i.log 2>&1 & done 🫡🤐😶🌫️
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🚀 Python 3.13+ is a game-changer: Free-threading (no-GIL mode) and experimental JIT boost multithreaded code by 2-5x! Speed gains are real for CPU-heavy tasks. Tested a simple parallel sum script—3x faster than 3.12. Python 3.15 stabilizes JIT fully. Here’s the snippet: # Run with: python3.13 -X free-threading import threading def compute(n): return sum(i*i for i in range(n)) threads = [threading.Thread(target=compute, args=(10**7,)) for _ in range(4)] for t in threads: t.start() for t in threads: t.join() print("Done!") Who’s upgraded? Share your benchmarks below! 👇 #Python #Python313 #Programming
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Managing Python environments across different tools can get messy fast. As I’ve been using uv with good results in my Python projects, I decided to align agents around a uv-first workflow for generating and running code. Using one tool for environments, dependencies, and execution made the setup much simpler and more predictable. I wrote down how I set this up step by step: https://lnkd.in/dAvyjEwr There’s also a GitHub repo linked in the post with AGENTS.md and CLAUDE.md you can use as a starting point.
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Claude Agent SDK tracing in LangSmith just got an upgrade. Now you can trace: → Subagents → Child runs inside MCP tools → Cost tracking + more Update to the latest Python SDK to try it out. Docs: https://lnkd.in/gTaNkWMa
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⚠️ Medium Risk Vulnerability Alert! The Claude SDK for Python has a memory tool path validation race condition that allows sandbox escape. This issue is related to API security and can lead to unrestricted resource consumption. It's been patched in version 0.87.0. Stay safe and keep your systems updated! #ClaudeSDK #Python #APIsecurity #OWASP #CVE2026-34452 https://lnkd.in/g26q6ZAn
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I built a Python CLI toolkit because everything felt fragmented Created by Arjun M Most Python CLI tools start simple… and then slowly turn into chaos. You begin with a couple of commands, maybe argparse, maybe click. Then you add prompts. Then state. Then formatted output. Then some sort of flow. And suddenly your “small CLI tool” looks like a badly stitched Frankenstein of ut... link https://lnkd.in/eXHSCBSX pubDate Sat, 11 Apr 2026 03:28:37 +0000
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