Greed-Dice-Game.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "\n",
    "**Attention:** Import the random module to determine the dice.\n",
    "\n",
    "Greed is a dice game played with five six-sided dice. Your mission, should you choose to accept it, is to score a throw according to these rules. You will always be given an array with five six-sided dice values.\n",
    "\n",
    "![image.png](data:image/png;base64,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)\n",
    "\n",
    "A single die can only be counted once in each roll. For example, a given \"5\" can only count as part of a triplet (contributing to the 500 points) or as a single 50 points, but not both in the same roll.\n",
    "\n",
    "Example scoring\n",
    "\n",
    "![image.png](data:image/png;base64,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)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[6, 2, 4, 6, 5]\n",
      "Score: 50\n"
     ]
    }
   ],
   "source": [
    "import random\n",
    "throw = []\n",
    "for i in range(5) :\n",
    "    throw += [random.randint(1,6)]\n",
    "\n",
    "print(throw)\n",
    "\n",
    "my_dict = {\"1\" : 0, \"2\" : 0, \"3\" : 0, \"4\" : 0, \"5\" : 0, \"6\" : 0}\n",
    "point = 0\n",
    "for i in range(len(throw)) :\n",
    "  my_dict[str(throw[i])] += 1\n",
    "\n",
    "results = list(my_dict.values())\n",
    "\n",
    "if results[0] >= 3 :\n",
    "  point += 1000 + (results[0] - 3) * 100 + results[4] * 50\n",
    "elif results[4] >= 3 :\n",
    "  point += 500 + (results[4] - 3) * 50 + results[0] * 100\n",
    "elif results[0] < 3 or results[4] < 3 :\n",
    "  for x in [1, 2, 3, 5] :\n",
    "    if results[x] == 3 :\n",
    "      point += (x + 1) * 100 + results[0] * 100 + results[4] * 50\n",
    "      break\n",
    "  else :\n",
    "    point += results[0] * 100 + results[4] * 50  \n",
    "\n",
    "print(f\"Score: {point}\")"
   ]
  }
 ],
 "metadata": {
  "interpreter": {
   "hash": "42b42069cbbf0a6319a26f91c3d8a98d7fbd1c788cb6a50cdce8d66031b17e46"
  },
  "kernelspec": {
   "display_name": "Python 3.9.2rc1 64-bit (system)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.2rc1"
  },
  "orig_nbformat": 4
 },
 "nbformat": 4,
 "nbformat_minor": 2
}