sirupsen

class Trie
  attr_accessor :word, :trie

  def initialize
    @trie = {}
    @word = false
  end

  def <<(string)
    node = string.each_char.inject(self) { |node, char| node.trie[char] ||= Trie.new }

kevin-smets

Default

Powerlevel10k

csamsel

Enhanced NGINX logstash parser:

NGINX log format:

        log_format enhanced '$remote_addr - $remote_user [$time_local] "$request" $status $body_bytes_sent $request_length "$http_referer" "$http_user_agent" $request_time $upstream_response_time';
        access_log /var/log/nginx/access.log enhanced;
        error_log /var/log/nginx/error.log;

logstash pattern (/opt/logstash/pattern/nginx):

subfuzion

Common Options

-#, --progress-bar Make curl display a simple progress bar instead of the more informational standard meter.

-b, --cookie <name=data> Supply cookie with request. If no =, then specifies the cookie file to use (see -c).

-c, --cookie-jar <file name> File to save response cookies to.

JonCole

Some of the Redis best practices content has moved

This content from this markdown file has moved a new, happier home where it can serve more people. Please check it out : https://docs.microsoft.com/azure/azure-cache-for-redis/cache-best-practices.

NOTE: Client specific guidance listed below is still valid and should still be considered. I will update this document once all content has been moved.

DanielThomas

import java.time.Duration;
import java.util.List;
import java.util.concurrent.locks.ReentrantLock;
import java.util.stream.IntStream;
import java.util.stream.Stream;

/**
 * Demonstrate potential for deadlock on a {@link ReentrantLock} when there is both a synchronized and
 * non-synchronized path to that lock, which can allow a virtual thread to hold the lock, but
 * other pinned waiters to consume all the available workers. 

sivaprasadreddy

Junie Guidelines

This document provides guidelines for developing a Spring Boot project. It includes coding standards, Spring Boot best practices and testing recommendations to follow.

Prerequisites

• Java 21 or later
• Docker and Docker Compose
• Maven (or use the included Maven wrapper)

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.