dnllu

Exporting SQL Server database structure into SQL script files

Scripting your SQL Server database schema is one such task that can benefit significantly from automation. Using C# and SQL Server Management Objects (SMO), you can easily generate scripts for your database schema and data.

Automating database scripting ensures that your schema and data scripts are always up-to-date and reduces the risk of human error. It is particularly useful for version control, backups, and migration tasks.

By integrating it into your workflow, you can significantly enhance your database management processes.

abstractart

Free Programming Ebooks - O'Reilly Media

Categories

• Programming
• IoT
• Data
• WebOps
• Web Development
• Security
• Business

lyc8503

// ==UserScript==
// @name         Telegram Block Chat Message
// @namespace    https://github.com/lyc8503
// @version      2026-02-08
// @description  Block annoying users' messages everywhere (e.g. in Groups, Channels); Middle click someone's avatar to add to blocklist
// @author       lyc8503
// @match        https://web.telegram.org/*
// @grant        GM_registerMenuCommand
// ==/UserScript==

leafm

<?php
/**
 * Leaf PHP Mailer by [leafmailer.pw]
 * @version : 2.7
**/

$password = ""; // Password 

session_start();
error_reporting(0);

coolaj86

Chat GPT "DAN" (and other "Jailbreaks")

• https://chat.openai.com/
• Is ChatGPT "DAN" Real? Gonna find out [Part 1]
  (https://www.youtube.com/watch?v=-q8woRG9FrI)
• Part 2: I thought ChatGPT DAN was a hoax, but...
  (https://www.youtube.com/watch?v=rHZRrDu3A2U&lc=UgxfrxX8aK7gnCzkend4AaABAg)

diogobenica

var Robot = function(robot) {
	robot.rotateCannon(90);
};

Robot.prototype.onIdle = function(ev) {
    var robot = ev.robot;
  	robot.ahead(1000);
  	
  	robot.fire();
};

SaltyAom

You are the orchestrator.

You think, design and plan architectural decision only. Write only essential technical specs and reasoning. Prefer not to write code yourself unless all executors fail.

Never assume the user's intent. Ask for clarification for ambiguous situations.

Executors:
- fellow (Fable): second opinion for architectural or complex decisions. For hardest problem only.
- mechanical (Sonnet): mechanical for fast/small redundant tasks.
- thinker (Opus): reasoning-heavy, help you review/verify your thinking along side Codex gpt-5.6-sol below.

saggie

FROM ubuntu:16.04

# Install sshd
RUN apt-get update
RUN apt-get install -y openssh-server

# Modify `sshd_config`
RUN sed -ri 's/PermitEmptyPasswords no/PermitEmptyPasswords yes/' /etc/ssh/sshd_config
RUN sed -ri 's/PermitRootLogin prohibit-password/PermitRootLogin yes/' /etc/ssh/sshd_config
RUN sed -ri 's/^UsePAM yes/UsePAM no/' /etc/ssh/sshd_config

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.

fbradyirl

type: custom:button-card
show_state: true
tap_action: none
custom_fields:
  home_image:
    card:
      type: picture
      image: local/Sigenergy/home_has_solar_has_car.png
      card_mod:
        style: |