{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "google",
   "metadata": {},
   "source": [
    "##### Copyright 2025 Google LLC."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "apache",
   "metadata": {},
   "source": [
    "Licensed under the Apache License, Version 2.0 (the \"License\");\n",
    "you may not use this file except in compliance with the License.\n",
    "You may obtain a copy of the License at\n",
    "\n",
    "    http://www.apache.org/licenses/LICENSE-2.0\n",
    "\n",
    "Unless required by applicable law or agreed to in writing, software\n",
    "distributed under the License is distributed on an \"AS IS\" BASIS,\n",
    "WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
    "See the License for the specific language governing permissions and\n",
    "limitations under the License.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "basename",
   "metadata": {},
   "source": [
    "# clone_model_sample_sat"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "link",
   "metadata": {},
   "source": [
    "<table align=\"left\">\n",
    "<td>\n",
    "<a href=\"https://colab.research.google.com/github/google/or-tools/blob/main/examples/notebook/sat/clone_model_sample_sat.ipynb\"><img src=\"https://raw.githubusercontent.com/google/or-tools/main/tools/colab_32px.png\"/>Run in Google Colab</a>\n",
    "</td>\n",
    "<td>\n",
    "<a href=\"https://github.com/google/or-tools/blob/main/ortools/sat/samples/clone_model_sample_sat.py\"><img src=\"https://raw.githubusercontent.com/google/or-tools/main/tools/github_32px.png\"/>View source on GitHub</a>\n",
    "</td>\n",
    "</table>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "doc",
   "metadata": {},
   "source": [
    "First, you must install [ortools](https://pypi.org/project/ortools/) package in this colab."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "install",
   "metadata": {},
   "outputs": [],
   "source": [
    "%pip install ortools"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "description",
   "metadata": {},
   "source": [
    "\n",
    "Showcases deep copying of a model.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "code",
   "metadata": {},
   "outputs": [],
   "source": [
    "import copy\n",
    "\n",
    "from ortools.sat.python import cp_model\n",
    "\n",
    "\n",
    "def clone_model_sample_sat():\n",
    "    \"\"\"Showcases cloning a model.\"\"\"\n",
    "    # Creates the model.\n",
    "    model = cp_model.CpModel()\n",
    "\n",
    "    # Creates the variables.\n",
    "    num_vals = 3\n",
    "    x = model.new_int_var(0, num_vals - 1, \"x\")\n",
    "    y = model.new_int_var(0, num_vals - 1, \"y\")\n",
    "    z = model.new_int_var(0, num_vals - 1, \"z\")\n",
    "\n",
    "    # Creates the constraints.\n",
    "    model.add(x != y)\n",
    "\n",
    "    model.maximize(x + 2 * y + 3 * z)\n",
    "\n",
    "    # Creates a solver and solves.\n",
    "    solver = cp_model.CpSolver()\n",
    "    status = solver.solve(model)\n",
    "\n",
    "    if status == cp_model.OPTIMAL:\n",
    "        print(\"Optimal value of the original model: {}\".format(solver.objective_value))\n",
    "\n",
    "    # Creates a dictionary holding the model and the variables you want to use.\n",
    "    to_clone = {\n",
    "        \"model\": model,\n",
    "        \"x\": x,\n",
    "        \"y\": y,\n",
    "        \"z\": z,\n",
    "    }\n",
    "\n",
    "    # Deep copy the dictionary.\n",
    "    clone = copy.deepcopy(to_clone)\n",
    "\n",
    "    # Retrieve the cloned model and variables.\n",
    "    cloned_model: cp_model.CpModel = clone[\"model\"]\n",
    "    cloned_x = clone[\"x\"]\n",
    "    cloned_y = clone[\"y\"]\n",
    "    cloned_model.add(cloned_x + cloned_y <= 1)\n",
    "\n",
    "    status = solver.solve(cloned_model)\n",
    "\n",
    "    if status == cp_model.OPTIMAL:\n",
    "        print(\"Optimal value of the modified model: {}\".format(solver.objective_value))\n",
    "\n",
    "\n",
    "clone_model_sample_sat()\n",
    "\n"
   ]
  }
 ],
 "metadata": {
  "language_info": {
   "name": "python"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}