Christmas names with constraint programming random.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from ortools.sat.python import cp_model\n",
    "from random import choice"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "persons = ['Mam', 'Dad', 'Bart', 'Belle', 'Jonathan', 'Johanna', 'Alex', 'Alice', 'Robert', 'Rhonda']\n",
    "\n",
    "forbidden = [\n",
    "    ['Mam', 'Dad'],\n",
    "    ['Bart', 'Belle',],\n",
    "    ['Jonathan', 'Johanna'],\n",
    "    ['Alex', 'Alice'],\n",
    "    ['Robert', 'Rhonda']\n",
    "]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "model = cp_model.CpModel()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "variables = {}\n",
    "\n",
    "for buyer in persons:\n",
    "    receiver_dict = {}\n",
    "    for receiver in persons:\n",
    "        receiver_dict[receiver] = model.NewIntVar(0, 1, f'{buyer} buys for {receiver}')\n",
    "    variables[buyer] = receiver_dict"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "for name, buyer in variables.items():\n",
    "    model.Add(sum(buyer.values()) == 1)\n",
    "\n",
    "for name in persons:\n",
    "    model.Add(sum([receivers[name] for buyer_name, receivers in variables.items()]) == 1)\n",
    "\n",
    "for name in persons:\n",
    "    model.Add(variables[name][name] == 0)\n",
    "\n",
    "for name_1, name_2 in forbidden:\n",
    "    model.Add(variables[name_1][name_2] == 0)\n",
    "    model.Add(variables[name_2][name_1] == 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "class AllSolutionsStore(cp_model.CpSolverSolutionCallback):\n",
    "    \"\"\"Count all solutions\"\"\"\n",
    "\n",
    "    def __init__(self, variables):\n",
    "        cp_model.CpSolverSolutionCallback.__init__(self)\n",
    "        self.__variables = variables\n",
    "        self.__solution_count = 0\n",
    "\n",
    "\n",
    "    def on_solution_callback(self):\n",
    "        self.__solution_count += 1\n",
    "\n",
    "    def solution_count(self):\n",
    "        return self.__solution_count"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "all_variables = []\n",
    "for name, x in variables.items():\n",
    "    all_variables += list(x.values())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "solver = cp_model.CpSolver()\n",
    "solutionsstore = AllSolutionsStore(all_variables)\n",
    "result = solver.SearchForAllSolutions(model, solutionsstore)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of solutions found: 440192\n"
     ]
    }
   ],
   "source": [
    "print('Number of solutions found: %i' % solutionsstore.solution_count())"
   ]
  }
 ],
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