Fix issues with random.sample() for python>=3.11

Starting from python 3.11, random.sample() must apply to a sequence with no automatic conversion from sets or dicts. See https://docs.python.org/3/library/random.html#random.sample.
airbus · Jan 23, 2024 · 0f9551d · 0f9551d
1 parent 06ee518
commit 0f9551d
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Showing 10 changed files with 21 additions and 21 deletions.
diff --git a/discrete_optimization/generic_rcpsp_tools/neighbor_tools_rcpsp.py b/discrete_optimization/generic_rcpsp_tools/neighbor_tools_rcpsp.py
@@ -1085,7 +1085,7 @@ def find_subtasks(
             subtasks.update(task_intersect)
             len_subtask = len(subtasks)
         if len(subtasks) >= self.nb_jobs_subproblem:
-            subtasks = set(random.sample(subtasks, self.nb_jobs_subproblem))
+            subtasks = set(random.sample(list(subtasks), self.nb_jobs_subproblem))
         return subtasks, self.set_tasks.difference(subtasks)
 
 
@@ -1184,7 +1184,7 @@ def find_subtasks(
                 )
             len_subtasks = len(subtasks)
             if len_subtasks > self.nb_jobs_subproblem:
-                subtasks = random.sample(subtasks, self.nb_jobs_subproblem)
+                subtasks = set(random.sample(list(subtasks), self.nb_jobs_subproblem))
             return subtasks, self.set_tasks.difference(subtasks)
         else:
             return self.other.find_subtasks(

diff --git a/discrete_optimization/generic_rcpsp_tools/solution_repair.py b/discrete_optimization/generic_rcpsp_tools/solution_repair.py
@@ -168,7 +168,7 @@ def problem_constraints(
     subtasks = set(problems_output.keys())
     if len(subtasks) >= 0.2 * current_solution.problem.n_jobs:
         subtasks = set(
-            random.sample(subtasks, int(0.2 * current_solution.problem.n_jobs))
+            random.sample(list(subtasks), int(0.2 * current_solution.problem.n_jobs))
         )
     else:
         subtasks = subtasks.union(

diff --git a/discrete_optimization/knapsack/solvers/knapsack_decomposition.py b/discrete_optimization/knapsack/solvers/knapsack_decomposition.py
@@ -99,7 +99,7 @@ def solve(self, **kwargs: Any) -> ResultStorage:
             sol, fit = results_storage.get_best_solution_fit()
             indexes_to_remove = set(
                 random.sample(
-                    all_indexes,
+                    list(all_indexes),
                     int(proportion_to_remove * self.knapsack_model.nb_items),
                 )
             )

diff --git a/discrete_optimization/pickup_vrp/solver/lp_solver.py b/discrete_optimization/pickup_vrp/solver/lp_solver.py
@@ -1583,7 +1583,7 @@ def adding_constraint(self, rebuilt_dict: Dict[int, List[Node]]) -> None:
                 edges_to_constraint[v].update(
                     set(
                         random.sample(
-                            set(
+                            list(
                                 self.linear_solver.variable_decisions[
                                     "variables_edges"
                                 ][v]
@@ -1606,7 +1606,7 @@ def adding_constraint(self, rebuilt_dict: Dict[int, List[Node]]) -> None:
                 edges_to_constraint[v].update(
                     set(
                         random.sample(
-                            set(
+                            list(
                                 self.linear_solver.variable_decisions[
                                     "variables_edges"
                                 ][v]

diff --git a/discrete_optimization/pickup_vrp/solver/lp_solver_pymip.py b/discrete_optimization/pickup_vrp/solver/lp_solver_pymip.py
@@ -1029,7 +1029,7 @@ def adding_constraint(self, rebuilt_dict: Dict[int, List[Node]]) -> None:
                 edges_to_constraint[v].update(
                     set(
                         random.sample(
-                            set(
+                            list(
                                 self.linear_solver.variable_decisions[
                                     "variables_edges"
                                 ][v]
@@ -1049,7 +1049,7 @@ def adding_constraint(self, rebuilt_dict: Dict[int, List[Node]]) -> None:
                 edges_to_constraint[v].update(
                     set(
                         random.sample(
-                            set(
+                            list(
                                 self.linear_solver.variable_decisions[
                                     "variables_edges"
                                 ][v]

diff --git a/discrete_optimization/rcpsp/solver/cp_lns_methods_preemptive.py b/discrete_optimization/rcpsp/solver/cp_lns_methods_preemptive.py
@@ -462,7 +462,7 @@ def adding_constraint_from_results_store(
         nb_jobs = self.problem.n_jobs
         jobs_to_fix = set(
             random.sample(
-                current_solution.rcpsp_schedule.keys(),
+                list(current_solution.rcpsp_schedule),
                 int(self.fraction_to_fix * nb_jobs),
             )
         )
@@ -803,7 +803,7 @@ def adding_constraint_from_results_store(
         nb_jobs = self.problem.n_jobs
         jobs_to_fix = set(
             random.sample(
-                current_solution.rcpsp_schedule.keys(),
+                list(current_solution.rcpsp_schedule),
                 int(self.fraction_to_fix * nb_jobs),
             )
         )

diff --git a/discrete_optimization/rcpsp/solver/rcpsp_cp_lns_solver.py b/discrete_optimization/rcpsp/solver/rcpsp_cp_lns_solver.py
@@ -73,7 +73,7 @@ def adding_constraint_from_results_store(
         nb_jobs = self.problem.n_jobs
         jobs_to_fix = set(
             random.sample(
-                current_solution.rcpsp_schedule.keys(),
+                list(current_solution.rcpsp_schedule),
                 int(self.fraction_to_fix * nb_jobs),
             )
         )
@@ -168,7 +168,7 @@ def adding_constraint_from_results_store(
         nb_jobs = self.problem.n_jobs
         jobs_to_fix = set(
             random.sample(
-                current_solution.rcpsp_schedule.keys(),
+                list(current_solution.rcpsp_schedule),
                 int(self.fraction_to_fix * nb_jobs),
             )
         )
@@ -283,7 +283,7 @@ def adding_constraint_from_results_store(
         nb_jobs = self.problem.n_jobs
         jobs_to_fix = set(
             random.sample(
-                current_solution.rcpsp_schedule.keys(),
+                list(current_solution.rcpsp_schedule),
                 int(self.fraction_to_fix * nb_jobs),
             )
         )

diff --git a/discrete_optimization/rcpsp/solver/rcpsp_lp_lns_solver.py b/discrete_optimization/rcpsp/solver/rcpsp_lp_lns_solver.py
@@ -170,7 +170,7 @@ def adding_constraint_from_results_store(
         # Fix start time for a subset of task.
         jobs_to_fix = set(
             random.sample(
-                current_solution.rcpsp_schedule.keys(),
+                list(current_solution.rcpsp_schedule),
                 int(self.fraction_fix_start_time * nb_jobs),
             )
         )
@@ -246,7 +246,7 @@ def adding_constraint_from_results_store(
         nb_jobs = self.problem.n_jobs
         jobs_to_fix = set(
             random.sample(
-                current_solution.rcpsp_schedule.keys(),
+                list(current_solution.rcpsp_schedule),
                 int(self.fraction_to_fix * nb_jobs),
             )
         )
@@ -333,7 +333,7 @@ def adding_constraint_from_results_store(
         nb_jobs = self.problem.n_jobs
         jobs_to_fix = set(
             random.sample(
-                current_solution.rcpsp_schedule.keys(),
+                list(current_solution.rcpsp_schedule),
                 int(self.fraction_to_fix * nb_jobs),
             )
         )
@@ -418,7 +418,7 @@ def adding_constraint_from_results_store(
         nb_jobs = self.problem.n_jobs
         jobs_to_fix = set(
             random.sample(
-                current_solution.rcpsp_schedule.keys(),
+                list(current_solution.rcpsp_schedule),
                 int(self.fraction_to_fix * nb_jobs),
             )
         )

diff --git a/discrete_optimization/rcpsp_multiskill/solvers/ms_rcpsp_cp_lns_solver.py b/discrete_optimization/rcpsp_multiskill/solvers/ms_rcpsp_cp_lns_solver.py
@@ -80,7 +80,7 @@ def adding_constraint_from_results_store(
         nb_jobs = self.problem.n_jobs
         jobs_to_fix = set(
             random.sample(
-                current_solution.schedule.keys(), int(self.fraction_to_fix * nb_jobs)
+                list(current_solution.schedule), int(self.fraction_to_fix * nb_jobs)
             )
         )
         for lj in last_jobs:
@@ -90,7 +90,7 @@ def adding_constraint_from_results_store(
         self.employees_position = self.problem.employees_list
         task_to_fix = set(
             random.sample(
-                current_solution.schedule.keys(),
+                list(current_solution.schedule),
                 int(self.fraction_task_to_fix_employee * nb_jobs),
             )
         )

diff --git a/discrete_optimization/rcpsp_multiskill/solvers/ms_rcpsp_lp_lns_solver.py b/discrete_optimization/rcpsp_multiskill/solvers/ms_rcpsp_lp_lns_solver.py
@@ -111,7 +111,7 @@ def adding_constraint_from_results_store(
         # Fix start time for a subset of task.
         jobs_to_fix = set(
             random.sample(
-                current_solution.rcpsp_schedule.keys(),
+                list(current_solution.rcpsp_schedule),
                 int(self.fraction_fix_start_time * nb_jobs),
             )
         )
@@ -179,7 +179,7 @@ def adding_constraint_from_results_store(
         nb_jobs = self.problem.nb_tasks
         jobs_to_fix = set(
             random.sample(
-                current_solution.schedule.keys(), int(self.fraction_to_fix * nb_jobs)
+                list(current_solution.schedule), int(self.fraction_to_fix * nb_jobs)
             )
         )
         for lj in last_jobs: