examples: regenerate notebooks

Author: Mizux

examples/notebook/algorithms/knapsack.ipynb

@@ -86,6 +86,7 @@
     "from ortools.algorithms.python import knapsack_solver\n",
     "\n",
     "\n",
+    "\n",
     "def main():\n",
     "    # Create the solver.\n",
     "    solver = knapsack_solver.KnapsackSolver(\n",

examples/notebook/algorithms/simple_knapsack_program.ipynb

@@ -86,6 +86,7 @@
     "from ortools.algorithms.python import knapsack_solver\n",
     "\n",
     "\n",
+    "\n",
     "def main():\n",
     "    # Create the solver.\n",
     "    solver = knapsack_solver.KnapsackSolver(\n",

examples/notebook/constraint_solver/cp_is_fun_cp.ipynb

@@ -91,6 +91,7 @@
     "from ortools.constraint_solver import pywrapcp\n",
     "\n",
     "\n",
+    "\n",
     "def main():\n",
     "    # Constraint programming engine\n",
     "    solver = pywrapcp.Solver(\"CP is fun!\")\n",

examples/notebook/constraint_solver/nqueens_cp.ipynb

@@ -87,6 +87,7 @@
     "from ortools.constraint_solver import pywrapcp\n",
     "\n",
     "\n",
+    "\n",
     "def main(board_size):\n",
     "    # Creates the solver.\n",
     "    solver = pywrapcp.Solver(\"n-queens\")\n",

examples/notebook/constraint_solver/simple_cp_program.ipynb

@@ -86,6 +86,7 @@
     "from ortools.constraint_solver import pywrapcp\n",
     "\n",
     "\n",
+    "\n",
     "def main():\n",
     "    \"\"\"Entry point of the program.\"\"\"\n",
     "    # Instantiate the solver.\n",

examples/notebook/contrib/permutation_flow_shop.ipynb

@@ -95,7 +95,6 @@
     "import numpy as np\n",
     "\n",
     "from ortools.sat.colab import flags\n",
-    "from google.protobuf import text_format\n",
     "from ortools.sat.python import cp_model\n",
     "\n",
     "_PARAMS = flags.define_string(\n",
@@ -217,7 +216,7 @@
     "\n",
     "    solver = cp_model.CpSolver()\n",
     "    if params:\n",
-    "        text_format.Parse(params, solver.parameters)\n",
+    "        solver.parameters.parse_text_format(params)\n",
     "    solver.parameters.log_search_progress = log\n",
     "    solver.parameters.max_time_in_seconds = time_limit\n",
     "\n",

examples/notebook/contrib/scheduling_with_transitions_sat.ipynb

@@ -90,7 +90,6 @@
     "import collections\n",
     "\n",
     "from ortools.sat.python import cp_model\n",
-    "from google.protobuf import text_format\n",
     "\n",
     "#----------------------------------------------------------------------------\n",
     "# Command line arguments.\n",
@@ -376,7 +375,7 @@
     "  solver = cp_model.CpSolver()\n",
     "  solver.parameters.max_time_in_seconds = 60 * 60 * 2\n",
     "  if parameters:\n",
-    "    text_format.Merge(parameters, solver.parameters)\n",
+    "    solver.parameters.merge_text_format(parameters)\n",
     "  solution_printer = SolutionPrinter(makespan)\n",
     "  status = solver.Solve(model, solution_printer)\n",
     "\n",

examples/notebook/examples/appointments.ipynb

@@ -244,7 +244,7 @@
     "\n",
     "\n",
     "def get_optimal_schedule(\n",
-    "    demand: list[tuple[float, str, int]]\n",
+    "    demand: list[tuple[float, str, int]],\n",
     ") -> list[tuple[int, list[tuple[int, str]]]]:\n",
     "    \"\"\"Computes the optimal schedule for the installation input.\n",
     "\n",

examples/notebook/examples/arc_flow_cutting_stock_sat.ipynb

@@ -89,7 +89,6 @@
     "from ortools.sat.colab import flags\n",
     "import numpy as np\n",
     "\n",
-    "from google.protobuf import text_format\n",
     "from ortools.linear_solver.python import model_builder as mb\n",
     "from ortools.sat.python import cp_model\n",
     "\n",
@@ -387,7 +386,7 @@
     "    # Solve model.\n",
     "    solver = cp_model.CpSolver()\n",
     "    if params:\n",
-    "        text_format.Parse(params, solver.parameters)\n",
+    "        solver.parameters.parse_text_format(params)\n",
     "    solver.parameters.log_search_progress = True\n",
     "    solver.Solve(model)\n",
     "\n",

examples/notebook/examples/balance_group_sat.ipynb

@@ -78,7 +78,8 @@
     "Each item has a color and a value. We want the sum of values of each group to\n",
     "be as close to the average as possible.\n",
     "Furthermore, if one color is an a group, at least k items with this color must\n",
-    "be in that group.\n"
+    "be in that group.\n",
+    "\n"
    ]
   },
   {