#python

cuTile Python is a new programming tool from NVIDIA that lets you write GPU programs in Python more easily and efficiently. It uses a tile-based model, where you work with chunks of data called tiles, making your code portable across different NVIDIA GPUs without needing to rewrite it for each hardware generation. cuTile automatically uses advanced GPU features like tensor cores and memory accelerators, so you get high performance without complex coding. You can install it via pip, and it requires CUDA Toolkit 13.1+ and Python 3.10+. This helps you develop faster, future-proof GPU applications with less effort.

https://github.com/NVIDIA/cutile-python

#python

You can access a free, detailed global dataset called the Global Building Atlas, which includes 2D building shapes, heights, and simple 3D models (LoD1) for 2.75 billion buildings worldwide, including areas often missing in other maps like Africa and South America. This data is very accurate, with a fine 3x3 meter resolution, and can be used in GIS software or downloaded fully. It helps with urban planning, disaster risk assessment, climate adaptation, and monitoring sustainable development goals by showing where people live and how cities grow. The dataset and related code are openly available for research and practical use.

https://github.com/zhu-xlab/GlobalBuildingAtlas

#python #agent #llm #rag #tutorial

You can learn to build smart AI agents from scratch with a free, open-source tutorial called Hello-Agents by Datawhale. It covers everything from basic concepts and history to hands-on projects like creating your own AI agent framework and multi-agent systems. The course includes practical skills such as memory, context handling, communication protocols, and training large language models. By following it, you gain deep understanding and real coding experience, moving from just using AI models to designing intelligent systems yourself. This helps you develop advanced AI skills useful for jobs, research, or building innovative AI applications. The materials are online and easy to access anytime.

https://github.com/datawhalechina/hello-agents

#python #agents #gcp #gemini #genai_agents #generative_ai #llmops #mlops #observability

You can quickly create and deploy AI agents using the Agent Starter Pack, a Python package with ready-made templates and full infrastructure on Google Cloud. It handles everything except your agent’s logic, including deployment, monitoring, security, and CI/CD pipelines. You can start a project in just one minute, customize agents for tasks like document search or real-time chat, and extend them as needed. This saves you time and effort by providing production-ready tools and integration with Google Cloud services, letting you focus on building smart AI agents without worrying about backend setup or deployment details.

https://github.com/GoogleCloudPlatform/agent-starter-pack

#python #dictionary_attack #password #password_strength #weak_passwords #wordlist #wordlist_generator

**CUPP** is a free Python 3 tool that creates custom password wordlists from personal details like names, birthdays, pet names, or nicknames, using interactive questions or existing dictionaries. Run it with options like `-i` for profiling or `-l` to download huge wordlists. This helps you in legal penetration tests or investigations by generating targeted lists for efficient brute-force or dictionary attacks, cracking weak passwords faster than generic ones.

https://github.com/Mebus/cupp

#python #datascience #formula1 #motorsport

FastF1 is a Python package that lets you easily access and analyze Formula 1 data like results, schedules, timing, telemetry, and more. It uses Pandas DataFrames with custom F1 tools, Matplotlib for charts, and caching for fast scripts—install via pip install fastf1. You benefit by quickly pulling historical and live F1 stats to build insights, visualizations, or apps without hassle.

https://github.com/theOehrly/Fast-F1

#python #help_wanted #looking_for_contributors

This M3U playlist gives you a single, regularly updated file of free, legal TV channels worldwide (grouped by country and marked for HD, geo-blocking, or YouTube live) so you can add it to an IPTV player and watch many working streams without hunting links; it focuses on quality (only free, mainstream channels, one URL per channel) and lets you contribute fixes or channel changes via GitHub pull requests, which helps you get reliable channels and keeps the list current for smoother viewing.

https://github.com/Free-TV/IPTV

#python #gym #gym_environment #reinforcement_learning #reinforcement_learning_agent #reinforcement_learning_environments #rl_environment #rl_training

NeMo Gym helps you build and run reinforcement‑learning training environments for large language models, letting you develop, test, and collect verified rollouts separately from the training loop and integrate with your preferred RL framework and model endpoints (OpenAI, vLLM, etc.). It includes ready resource servers, datasets, and patterns for multi‑step, multi‑turn, and tool‑using scenarios, runs on a typical dev machine (no GPU required), and is early-stage with evolving APIs and docs. Benefit: you can generate high‑quality, verifiable training data faster and plug it into existing training pipelines to improve model behavior.

https://github.com/NVIDIA-NeMo/Gym

#python

**ty** is a super-fast Python type checker and language server built in Rust by Astral (makers of uv and Ruff). It's 10-100x faster than mypy or Pyright, with rich error messages, IDE features like auto-complete and hover help, and support for big projects or partial typing. Try it via `uvx ty check`. This helps you catch bugs early, code faster with real-time feedback, and boost productivity in editors like VS Code.

https://github.com/astral-sh/ty