krypted

class Logging(object):

    __name__ = 'logger.info(1)'
    plist = '/System/Library/Preferences/Logging/Subsystems/'

    def __init__(__name__, plist, *args, **kwargs):
        super(getLogger/, self).__init__()

        logger.info('Input parameters:\n'
                    'accessibility: "{com.apple.Accessibility.plist}"\n'

nikage

# Run python3 waf build command
_Exported on 17/08/2025 at 23:38:29 EEST from Cursor (1.4.3)_

---

**User**

python3 waf build -v

run and see what's wrong 

fawazahmed0

# Please Note, I am sharing this, hoping this will be used for good public use, such as data analysis, penetration testing etc
# These links are already available all over the internet
# Also Note, Trying to login into someone else's account without their permission is unethical and illegal


# Collection 1
magnet:?xt=urn:btih:B39C603C7E18DB8262067C5926E7D5EA5D20E12E&dn=Collection%201&tr=udp%3a%2f%2ftracker.coppersurfer.tk%3a6969%2fannounce&tr=udp%3a%2f%2ftracker.leechers-paradise.org%3a6969%2fannounce&tr=http%3a%2f%2ft.nyaatracker.com%3a80%2fannounce&tr=http%3a%2f%2fopentracker.xyz%3a80%2fannounce

# Collection 2-5 & Antipublic
magnet:?xt=urn:btih:D136B1ADDE531F38311FBF43FB96FC26DF1A34CD&dn=Collection%20%232-%235%20%26%20Antipublic&tr=udp%3a%2f%2ftracker.coppersurfer.tk%3a6969%2fannounce&tr=udp%3a%2f%2ftracker.leechers-paradise.org%3a6969%2fannounce&tr=http%3a%2f%2ft.nyaatracker.com%3a80%2fannounce&tr=http%3a%2f%2fopentracker.xyz%3a80%2fannounce

cassidydotdk

WebGL Showcase — Source

Source for the six WebGL demos at https://markcassidyconsulting.com/showcases/webgl/, plus the Boing Ball that runs as the hero on the showcase landing page.

Each file is a single Astro component containing HTML, scoped CSS, and the TypeScript that drives the canvas. Drop a file into an Astro project (src/components/) and reference it from a page; or copy the contents of the <script> block into a vanilla setup that already has three installed and stitch the markup + CSS by hand.

Files

File	Technique

d-kja

Running NIKKE on Linux

Linux guide for GODDESS OF VICTORY: NIKKE into launcher-specific paths.

Paths

Path	Description	Guide
Bottles	Recommended launcher setup	Guide
Faugus	Launcher setup	Guide

milnak

Foobar2000 DSD and SACD support

I've successfully followed these steps to get DSD (.dsf filetype) and SACD (.iso filetype) playing at high bit rate using foobar2000 on my S.M.S.L M500 DAC.

This has been adapted from "SECTION II" of this page, thanks to "sirblew" for the tip!

Introduction

DSD stands for Direct Stream Digital and it is a high-definition lossless audio format with a twist. PCM signal solutions (like FLAC, TTA or APE) measure a set of bits multiple times per second to capture the audio data, hence the 16/24-bit parameter. On the other hand, DSD uses only one bit but samples it 2.8 million times a second to capture the audio signal.

naim149

GH-600 Public Study Guide

Markdown-only workbook for Exam GH-600: Developing in Agentic AI Systems.

Last updated: May 24, 2026.

This version is organized around the official GH-600 domains. Each domain explains the concepts, shows the GitHub implementation artifacts, and includes examples you should be able to read in YAML, Markdown, CLI output, PR timelines, and audit logs.

Public sharing note: this guide is not an exam dump and does not contain real exam questions or answer choices. It is a structured study workbook built from official Microsoft and GitHub documentation, with practical examples written for learning and review.

risingrising

install.md — Weekly LinkedIn analytics agent installer

You are an installer. Read this file end-to-end, then guide the user through setting up a weekly LinkedIn analytics agent. Be conversational and efficient — this should take 2-3 messages back and forth.

The user has just told you something like "install this for me" or "follow install.md and set up the LinkedIn analytics workflow". Treat that as the trigger. Don't make them re-read what's below — you do the reading, you do the work.

---

What you're installing

karpathy

LLM Wiki

A pattern for building personal knowledge bases using LLMs.

This is an idea file, it is designed to be copy pasted to your own LLM Agent (e.g. OpenAI Codex, Claude Code, OpenCode / Pi, or etc.). Its goal is to communicate the high level idea, but your agent will build out the specifics in collaboration with you.

The core idea

Most people's experience with LLMs and documents looks like RAG: you upload a collection of files, the LLM retrieves relevant chunks at query time, and generates an answer. This works, but the LLM is rediscovering knowledge from scratch on every question. There's no accumulation. Ask a subtle question that requires synthesizing five documents, and the LLM has to find and piece together the relevant fragments every time. Nothing is built up. NotebookLM, ChatGPT file uploads, and most RAG systems work this way.