naufraghi

#!/usr/bin/env python
# -*- coding: utf-8 -*-
# Copyright (C) 2010 Matteo Bertini <matteo@naufraghi.net>
# Licensed as http://creativecommons.org/licenses/BSD/
#
# This is a naive implementation of the k-means unsupervised clustering
# algorithm (http://en.wikipedia.org/wiki/K-means_clustering).

from __future__ import division
import sys

lauralaurilauro

var a1 = [0,0,0]
var a2 = [0,0,0]
var a3 = [0,0,0]
var tablero = [a1,a2,a3]

function introPieza (jugador, x,y){
	si tablero[x][y] == 0
		tablero[x][y]== jugador     // si la casilla es 0, esta libre, el jugador n puede poner la 	casilla
		devuelve verdadero			// cuando es valida la accion, cambia de jugador. si devuelve falso sigue jugando el mismo

46bit

import sys, cv2

# Refactored https://realpython.com/blog/python/face-recognition-with-python/

def cascade_detect(cascade, image):
  gray_image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
  return cascade.detectMultiScale(
    gray_image,
    scaleFactor = 1.15,
    minNeighbors = 5,

fheisler

import random


class TicTacToe:
    def __init__(self, playerX, playerO):
        self.board = [' ']*9
        self.playerX, self.playerO = playerX, playerO
        self.playerX_turn = random.choice([True, False])

    def play_game(self):

PurpleBooth

Project Title

One Paragraph of project description goes here

Getting Started

These instructions will get you a copy of the project up and running on your local machine for development and testing purposes. See deployment for notes on how to deploy the project on a live system.

Prerequisites

jdjuan

Community Impact: Juan Herrera

In Person Engagements: 1213

1. NgColombia (International Conference)

Latin America first Angular conference held in Medellín and gathering +230 attendees and 8 different speakers, including 3 GDEs:

• Website
• Photos

leoaiassistant

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gandroz

version: 0.2

phases:
  install:
    runtime-versions:
      python: 3.8
  pre_build:
    commands:
      - apt-get install -y python3-venv
      - python3.6 -m venv test_venv

jorgeucano

# Meeting Intelligence Pipeline

> A Claude skill that converts any meeting transcript into a single production-ready Gherkin `.feature` file — directly consumable by Claude Code.

## What it does

Most product teams leave meetings with messy notes, vague action items, and specs that never get written. This skill closes that gap.

You give it a transcript. It gives you a `.feature` file with: