204 lines
7.0 KiB
Plaintext
204 lines
7.0 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "google",
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"metadata": {},
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"source": [
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"##### Copyright 2025 Google LLC."
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]
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},
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{
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"cell_type": "markdown",
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"id": "apache",
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"metadata": {},
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"source": [
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"Licensed under the Apache License, Version 2.0 (the \"License\");\n",
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"you may not use this file except in compliance with the License.\n",
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"You may obtain a copy of the License at\n",
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"\n",
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" http://www.apache.org/licenses/LICENSE-2.0\n",
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"\n",
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"Unless required by applicable law or agreed to in writing, software\n",
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"distributed under the License is distributed on an \"AS IS\" BASIS,\n",
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"WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
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"See the License for the specific language governing permissions and\n",
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"limitations under the License.\n"
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]
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},
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{
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"cell_type": "markdown",
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"id": "basename",
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"metadata": {},
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"source": [
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"# nurses_sat"
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]
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},
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{
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"cell_type": "markdown",
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"id": "link",
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"metadata": {},
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"source": [
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"<table align=\"left\">\n",
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"<td>\n",
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"<a href=\"https://colab.research.google.com/github/google/or-tools/blob/main/examples/notebook/sat/nurses_sat.ipynb\"><img src=\"https://raw.githubusercontent.com/google/or-tools/main/tools/colab_32px.png\"/>Run in Google Colab</a>\n",
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"</td>\n",
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"<td>\n",
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"<a href=\"https://github.com/google/or-tools/blob/main/ortools/sat/samples/nurses_sat.py\"><img src=\"https://raw.githubusercontent.com/google/or-tools/main/tools/github_32px.png\"/>View source on GitHub</a>\n",
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"</td>\n",
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"</table>"
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]
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},
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{
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"cell_type": "markdown",
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"id": "doc",
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"metadata": {},
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"source": [
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"First, you must install [ortools](https://pypi.org/project/ortools/) package in this colab."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "install",
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"metadata": {},
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"outputs": [],
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"source": [
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"%pip install ortools"
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]
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},
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{
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"cell_type": "markdown",
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"id": "description",
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"metadata": {},
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"source": [
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"\n",
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"Example of a simple nurse scheduling problem."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "code",
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"metadata": {},
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"outputs": [],
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"source": [
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"from ortools.sat.python import cp_model\n",
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"\n",
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"\n",
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"\n",
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"def main() -> None:\n",
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" # Data.\n",
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" num_nurses = 4\n",
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" num_shifts = 3\n",
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" num_days = 3\n",
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" all_nurses = range(num_nurses)\n",
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" all_shifts = range(num_shifts)\n",
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" all_days = range(num_days)\n",
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"\n",
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" # Creates the model.\n",
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" model = cp_model.CpModel()\n",
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"\n",
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" # Creates shift variables.\n",
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" # shifts[(n, d, s)]: nurse 'n' works shift 's' on day 'd'.\n",
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" shifts = {}\n",
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" for n in all_nurses:\n",
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" for d in all_days:\n",
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" for s in all_shifts:\n",
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" shifts[(n, d, s)] = model.new_bool_var(f\"shift_n{n}_d{d}_s{s}\")\n",
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"\n",
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" # Each shift is assigned to exactly one nurse in the schedule period.\n",
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" for d in all_days:\n",
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" for s in all_shifts:\n",
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" model.add_exactly_one(shifts[(n, d, s)] for n in all_nurses)\n",
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"\n",
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" # Each nurse works at most one shift per day.\n",
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" for n in all_nurses:\n",
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" for d in all_days:\n",
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" model.add_at_most_one(shifts[(n, d, s)] for s in all_shifts)\n",
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"\n",
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" # Try to distribute the shifts evenly, so that each nurse works\n",
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" # min_shifts_per_nurse shifts. If this is not possible, because the total\n",
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" # number of shifts is not divisible by the number of nurses, some nurses will\n",
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" # be assigned one more shift.\n",
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" min_shifts_per_nurse = (num_shifts * num_days) // num_nurses\n",
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" if num_shifts * num_days % num_nurses == 0:\n",
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" max_shifts_per_nurse = min_shifts_per_nurse\n",
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" else:\n",
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" max_shifts_per_nurse = min_shifts_per_nurse + 1\n",
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" for n in all_nurses:\n",
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" shifts_worked = []\n",
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" for d in all_days:\n",
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" for s in all_shifts:\n",
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" shifts_worked.append(shifts[(n, d, s)])\n",
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" model.add(min_shifts_per_nurse <= sum(shifts_worked))\n",
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" model.add(sum(shifts_worked) <= max_shifts_per_nurse)\n",
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"\n",
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" # Creates the solver and solve.\n",
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" solver = cp_model.CpSolver()\n",
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" solver.parameters.linearization_level = 0\n",
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" # Enumerate all solutions.\n",
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" solver.parameters.enumerate_all_solutions = True\n",
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"\n",
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" class NursesPartialSolutionPrinter(cp_model.CpSolverSolutionCallback):\n",
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" \"\"\"Print intermediate solutions.\"\"\"\n",
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"\n",
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" def __init__(self, shifts, num_nurses, num_days, num_shifts, limit):\n",
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" cp_model.CpSolverSolutionCallback.__init__(self)\n",
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" self._shifts = shifts\n",
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" self._num_nurses = num_nurses\n",
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" self._num_days = num_days\n",
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" self._num_shifts = num_shifts\n",
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" self._solution_count = 0\n",
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" self._solution_limit = limit\n",
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"\n",
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" def on_solution_callback(self):\n",
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" self._solution_count += 1\n",
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" print(f\"Solution {self._solution_count}\")\n",
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" for d in range(self._num_days):\n",
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" print(f\"Day {d}\")\n",
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" for n in range(self._num_nurses):\n",
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" is_working = False\n",
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" for s in range(self._num_shifts):\n",
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" if self.value(self._shifts[(n, d, s)]):\n",
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" is_working = True\n",
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" print(f\" Nurse {n} works shift {s}\")\n",
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" if not is_working:\n",
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" print(f\" Nurse {n} does not work\")\n",
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" if self._solution_count >= self._solution_limit:\n",
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" print(f\"Stop search after {self._solution_limit} solutions\")\n",
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" self.stop_search()\n",
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"\n",
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" def solutionCount(self):\n",
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" return self._solution_count\n",
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"\n",
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" # Display the first five solutions.\n",
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" solution_limit = 5\n",
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" solution_printer = NursesPartialSolutionPrinter(\n",
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" shifts, num_nurses, num_days, num_shifts, solution_limit\n",
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" )\n",
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"\n",
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" solver.solve(model, solution_printer)\n",
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"\n",
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" # Statistics.\n",
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" print(\"\\nStatistics\")\n",
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" print(f\" - conflicts : {solver.num_conflicts}\")\n",
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" print(f\" - branches : {solver.num_branches}\")\n",
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" print(f\" - wall time : {solver.wall_time} s\")\n",
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" print(f\" - solutions found: {solution_printer.solutionCount()}\")\n",
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"\n",
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"\n",
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"main()\n",
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"\n"
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]
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}
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],
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"metadata": {
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"language_info": {
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"name": "python"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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