python: Fix tests when SCIP and COINOR are disabled (#3261)

examples/contrib/3_jugs_mip.py

@@ -32,19 +32,11 @@ from ortools.linear_solver import pywraplp
 
 
 def main(sol='CBC'):
-
   # Create the solver.
-
   print('Solver: ', sol)
-
-  # using GLPK
-  if sol == 'GLPK':
-    solver = pywraplp.Solver('CoinsGridGLPK',
-                             pywraplp.Solver.GLPK_MIXED_INTEGER_PROGRAMMING)
-  else:
-    # Using CBC
-    solver = pywraplp.Solver('CoinsGridCBC',
-                             pywraplp.Solver.CBC_MIXED_INTEGER_PROGRAMMING)
+  solver = pywraplp.Solver.CreateSolver(sol)
+  if not solver:
+    return
 
   #
   # data

examples/contrib/assignment6_mip.py

@@ -48,14 +48,12 @@ def main(sol='CBC'):
   # Create the solver.
   print('Solver: ', sol)
 
-  # using GLPK
   if sol == 'GLPK':
-    solver = pywraplp.Solver('CoinsGridGLPK',
-                             pywraplp.Solver.GLPK_MIXED_INTEGER_PROGRAMMING)
+    solver = pywraplp.Solver.CreateSolver('GLPK')
   else:
-    # Using CBC
-    solver = pywraplp.Solver('CoinsGridCBC',
-                             pywraplp.Solver.CBC_MIXED_INTEGER_PROGRAMMING)
+    solver = pywraplp.Solver.CreateSolver('CBC')
+  if not solver:
+    return
 
   #
   # data

examples/contrib/blending.py

@@ -31,14 +31,12 @@ def main(sol='CBC'):
 
   print('Solver: ', sol)
 
-  # using GLPK
   if sol == 'GLPK':
-    solver = pywraplp.Solver('CoinsGridGLPK',
-                             pywraplp.Solver.GLPK_MIXED_INTEGER_PROGRAMMING)
+    solver = pywraplp.Solver.CreateSolver('GLPK')
   else:
-    # Using CBC
-    solver = pywraplp.Solver('CoinsGridCBC',
-                             pywraplp.Solver.CBC_MIXED_INTEGER_PROGRAMMING)
+    solver = pywraplp.Solver.CreateSolver('CBC')
+  if not solver:
+    return
 
   #
   # data

examples/contrib/coins_grid_mip.py

@@ -47,12 +47,9 @@ def main(unused_argv):
   # Create the solver.
 
   # using CBC
-  solver = pywraplp.Solver('CoinsGridCBC',
-                           pywraplp.Solver.CBC_MIXED_INTEGER_PROGRAMMING)
-
-  # Using CLP
-  # solver = pywraplp.Solver('CoinsGridCLP',
-  #                          pywraplp.Solver.CBC_MIXED_INTEGER_PROGRAMMING)
+  solver = pywraplp.Solver.CreateSolver('CBC')
+  if not solver:
+    return
 
   # data
   n = 31  # the grid size

examples/contrib/coloring_ip.py

@@ -43,17 +43,10 @@ from ortools.linear_solver import pywraplp
 def main(sol='CBC'):
 
   # Create the solver.
-
   print('Solver: ', sol)
-
-  if sol == 'GLPK':
-    # using GLPK
-    solver = pywraplp.Solver('CoinsGridGLPK',
-                             pywraplp.Solver.GLPK_MIXED_INTEGER_PROGRAMMING)
-  else:
-    # Using CBC
-    solver = pywraplp.Solver('CoinsGridCLP',
-                             pywraplp.Solver.CBC_MIXED_INTEGER_PROGRAMMING)
+  solver = pywraplp.Solver.CreateSolver(sol)
+  if not solver:
+    return
 
   #
   # data

examples/contrib/diet1_mip.py

@@ -43,15 +43,9 @@ def main(sol='CBC'):
   # Create the solver.
 
   print('Solver: ', sol)
-
-  if sol == 'GLPK':
-    # using GLPK
-    solver = pywraplp.Solver('CoinsGridGLPK',
-                             pywraplp.Solver.GLPK_MIXED_INTEGER_PROGRAMMING)
-  else:
-    # Using CBC
-    solver = pywraplp.Solver('CoinsGridCLP',
-                             pywraplp.Solver.CBC_MIXED_INTEGER_PROGRAMMING)
+  solver = pywraplp.Solver.CreateSolver(sol)
+  if not solver:
+    return
 
   #
   # data

examples/contrib/game_theory_taha.py

@@ -30,15 +30,9 @@ from ortools.linear_solver import pywraplp
 def main(sol='CBC'):
 
   # Create the solver.
-
-  # using GLPK
-  if sol == 'GLPK':
-    solver = pywraplp.Solver('CoinsGridGLPK',
-                             pywraplp.Solver.GLPK_LINEAR_PROGRAMMING)
-  else:
-    # Using CLP
-    solver = pywraplp.Solver('CoinsGridCLP',
-                             pywraplp.Solver.CLP_LINEAR_PROGRAMMING)
+  solver = pywraplp.Solver.CreateSolver(sol)
+  if not solver:
+    return
 
   # data
   rows = 3

examples/contrib/knapsack_mip.py

@@ -28,17 +28,10 @@ from ortools.linear_solver import pywraplp
 def main(sol='CBC'):
 
   # Create the solver.
-
   print('Solver: ', sol)
-
-  # using GLPK
-  if sol == 'GLPK':
-    solver = pywraplp.Solver('CoinsGridGLPK',
-                             pywraplp.Solver.GLPK_MIXED_INTEGER_PROGRAMMING)
-  else:
-    # Using CBC
-    solver = pywraplp.Solver('CoinsGridCBC',
-                             pywraplp.Solver.CBC_MIXED_INTEGER_PROGRAMMING)
+  solver = pywraplp.Solver.CreateSolver(sol)
+  if not solver:
+    return
 
   #
   # data

examples/contrib/least_square.py

@@ -31,15 +31,9 @@ from ortools.linear_solver import pywraplp
 def main(sol='CBC'):
 
   # Create the solver.
-
-  # using GLPK
-  if sol == 'GLPK':
-    solver = pywraplp.Solver('CoinsGridGLPK',
-                             pywraplp.Solver.GLPK_LINEAR_PROGRAMMING)
-  else:
-    # Using CLP
-    solver = pywraplp.Solver('CoinsGridCLP',
-                             pywraplp.Solver.CLP_LINEAR_PROGRAMMING)
+  solver = pywraplp.Solver.CreateSolver(sol)
+  if not solver:
+    return
 
   # data
   # number of points

examples/contrib/magic_square.py

@@ -28,6 +28,8 @@ from ortools.constraint_solver import pywrapcp
 def main(n, limit):
   # Create the solver.
   solver = pywrapcp.Solver("n-queens")
+  if not solver:
+    return
 
   #
   # data

examples/contrib/magic_square_mip.py

@@ -52,19 +52,11 @@ from ortools.linear_solver import pywraplp
 
 
 def main(n=3, sol='CBC', use_output_matrix=0):
-
   # Create the solver.
-
   print('Solver: ', sol)
-
-  # using GLPK
-  if sol == 'GLPK':
-    solver = pywraplp.Solver('CoinsGridGLPK',
-                             pywraplp.Solver.GLPK_MIXED_INTEGER_PROGRAMMING)
-  else:
-    # Using CLP
-    solver = pywraplp.Solver('CoinsGridCLP',
-                             pywraplp.Solver.CBC_MIXED_INTEGER_PROGRAMMING)
+  solver = pywraplp.Solver.CreateSolver(sol)
+  if not solver:
+    return
 
   #
   # data

examples/contrib/production.py

@@ -28,15 +28,9 @@ from ortools.linear_solver import pywraplp
 def main(sol='CBC'):
 
   # Create the solver.
-
-  # using GLPK
-  if sol == 'GLPK':
-    solver = pywraplp.Solver('CoinsGridGLPK',
-                             pywraplp.Solver.GLPK_LINEAR_PROGRAMMING)
-  else:
-    # Using CLP
-    solver = pywraplp.Solver('CoinsGridCLP',
-                             pywraplp.Solver.CLP_LINEAR_PROGRAMMING)
+  solver = pywraplp.Solver.CreateSolver(sol)
+  if not solver:
+    return
 
   #
   # data

examples/contrib/stigler_contrib.py

@@ -122,19 +122,11 @@ from ortools.linear_solver import pywraplp
 
 
 def main(sol="CBC"):
-
   # Create the solver.
-
   print("Solver: ", sol)
-
-  # using GLPK
-  if sol == "GLPK":
-    solver = pywraplp.Solver("CoinsGridGLPK",
-                             pywraplp.Solver.GLPK_MIXED_INTEGER_PROGRAMMING)
-  else:
-    # Using CLP
-    solver = pywraplp.Solver("CoinsGridCLP",
-                             pywraplp.Solver.CBC_MIXED_INTEGER_PROGRAMMING)
+  solver = pywraplp.Solver.CreateSolver(sol)
+  if not solver:
+    return
 
   #
   # data

examples/contrib/volsay.py

@@ -33,8 +33,9 @@ def main(unused_argv):
   #                         pywraplp.Solver.GLPK_LINEAR_PROGRAMMING)
 
   # Using CLP
-  solver = pywraplp.Solver('CoinsGridCLP',
-                           pywraplp.Solver.CLP_LINEAR_PROGRAMMING)
+  solver = pywraplp.Solver.CreateSolver('CLP')
+  if not solver:
+    return
 
   # data
 

examples/contrib/volsay2.py

@@ -34,8 +34,9 @@ def main(unused_argv):
   #                          pywraplp.Solver.GLPK_LINEAR_PROGRAMMING)
 
   # Using CLP
-  solver = pywraplp.Solver('CoinsGridCLP',
-                           pywraplp.Solver.CLP_LINEAR_PROGRAMMING)
+  solver = pywraplp.Solver.CreateSolver('CLP')
+  if not solver:
+    return
 
   # data
   num_products = 2

examples/contrib/volsay3.py

@@ -34,8 +34,9 @@ def main(unused_argv):
   #                          pywraplp.Solver.GLPK_LINEAR_PROGRAMMING)
 
   # Using CLP
-  solver = pywraplp.Solver('CoinsGridCLP',
-                           pywraplp.Solver.CLP_LINEAR_PROGRAMMING)
+  solver = pywraplp.Solver.CreateSolver('CLP')
+  if not solver:
+    return
 
   # data
   num_products = 2

examples/python/appointments.py

@@ -116,8 +116,9 @@ def AggregateItemCollectionsOptimally(item_collections, max_num_collections,
       - and its associated "num_selections" is the number of times it was
         selected.
   """
-    solver = pywraplp.Solver('Select',
-                             pywraplp.Solver.SCIP_MIXED_INTEGER_PROGRAMMING)
+    solver = pywraplp.Solver.CreateSolver('SCIP')
+    if not solver:
+      return []
     n = len(ideal_item_ratios)
     num_distinct_collections = len(item_collections)
     max_num_items_per_collection = 0
@@ -238,10 +239,12 @@ def solve_appointments(_):
     print()
     print('%d installations planned' % installed)
     for a in demand:
-        name = a[1]
-        per_type = installed_per_type[name]
-        print(('   %d (%.2f%%) installations of type %s planned' %
-               (per_type, per_type * 100.0 / installed, name)))
+      name = a[1]
+      per_type = installed_per_type[name]
+      if installed != 0:
+        print(f'   {per_type} ({per_type * 100.0 / installed}%) installations of type {name} planned')
+      else:
+        print(f'   {per_type} installations of type {name} planned')
     # [END print_solution]
 
 

examples/python/steel_mill_slab_sat.py

@@ -705,8 +705,9 @@ def steel_mill_slab_with_mip_column_generation(problem):
 
     # create model and decision variables.
     start_time = time.time()
-    solver = pywraplp.Solver('Steel',
-                             pywraplp.Solver.SCIP_MIXED_INTEGER_PROGRAMMING)
+    solver = pywraplp.Solver.CreateSolver('SCIP')
+    if not solver:
+      return
     selected = [
         solver.IntVar(0.0, 1.0, 'selected_%i' % i) for i in all_valid_slabs
     ]

examples/tests/dual_loading.py

@@ -5,7 +5,7 @@ from ortools.linear_solver import pywraplp
 
 def main():
   cp = pywrapcp.Solver("test")
-  lp = pywraplp.Solver("test", pywraplp.Solver.CLP_LINEAR_PROGRAMMING)
+  lp = pywraplp.Solver.CreateSolver('GLOP')
 
 
 if __name__ == "__main__":

examples/tests/pywraplp_test.py

@@ -46,8 +46,9 @@ class PyWrapLp(unittest.TestCase):
     def test_proto(self):
         input_proto = linear_solver_pb2.MPModelProto()
         text_format.Merge(TEXT_MODEL, input_proto)
-        solver = pywraplp.Solver('solveFromProto',
-                                 pywraplp.Solver.CBC_MIXED_INTEGER_PROGRAMMING)
+        solver = pywraplp.Solver.CreateSolver('CBC')
+        if not solver:
+          return
         # For now, create the model from the proto by parsing the proto
         errors = solver.LoadModelFromProto(input_proto)
         self.assertFalse(errors)
@@ -61,8 +62,7 @@ class PyWrapLp(unittest.TestCase):
         self.assertEqual(solution.best_objective_bound, 3.0)
 
     def test_external_api(self):
-        solver = pywraplp.Solver('TestExternalAPI',
-                                 pywraplp.Solver.GLOP_LINEAR_PROGRAMMING)
+        solver = pywraplp.Solver.CreateSolver('GLOP')
         infinity = solver.Infinity()
         infinity2 = solver.infinity()
         self.assertEqual(infinity, infinity2)

ortools/linear_solver/samples/assignment_groups_mip.py

@@ -70,6 +70,8 @@ def main():
     # [START solver]
     # Create the mip solver with the SCIP backend.
     solver = pywraplp.Solver.CreateSolver('SCIP')
+    if not solver:
+        return
     # [END solver]
 
     # Variables

ortools/linear_solver/samples/assignment_mip.py

@@ -36,7 +36,8 @@ def main():
     # [START solver]
     # Create the mip solver with the SCIP backend.
     solver = pywraplp.Solver.CreateSolver('SCIP')
-
+    if not solver:
+        return
     # [END solver]
 
     # Variables

ortools/linear_solver/samples/assignment_task_sizes_mip.py

@@ -45,7 +45,8 @@ def main():
     # [START solver]
     # Create the mip solver with the SCIP backend.
     solver = pywraplp.Solver.CreateSolver('SCIP')
-
+    if not solver:
+        return
     # [END solver]
 
     # Variables

ortools/linear_solver/samples/assignment_teams_mip.py

@@ -42,6 +42,8 @@ def main():
     # [START solver]
     # Create the mip solver with the SCIP backend.
     solver = pywraplp.Solver.CreateSolver('SCIP')
+    if not solver:
+        return
     # [END solver]
 
     # Variables

ortools/linear_solver/samples/basic_example.py

@@ -23,6 +23,8 @@ def main():
     # [START solver]
     # Create the linear solver with the GLOP backend.
     solver = pywraplp.Solver.CreateSolver('GLOP')
+    if not solver:
+        return
     # [END solver]
 
     # [START variables]

ortools/linear_solver/samples/bin_packing_mip.py

@@ -42,7 +42,8 @@ def main():
     # [START solver]
     # Create the mip solver with the SCIP backend.
     solver = pywraplp.Solver.CreateSolver('SCIP')
-
+    if not solver:
+        return
     # [END solver]
 
     # [START program_part2]

ortools/linear_solver/samples/integer_programming_example.py

@@ -23,7 +23,8 @@ def IntegerProgrammingExample():
     # [START solver]
     # Create the mip solver with the SCIP backend.
     solver = pywraplp.Solver.CreateSolver('SCIP')
-
+    if not solver:
+        return
     # [END solver]
 
     # [START variables]

ortools/linear_solver/samples/linear_programming_example.py

@@ -23,6 +23,8 @@ def LinearProgrammingExample():
     # Instantiate a Glop solver, naming it LinearExample.
     # [START solver]
     solver = pywraplp.Solver.CreateSolver('GLOP')
+    if not solver:
+        return
     # [END solver]
 
     # Create the two variables and let them take on any non-negative value.

ortools/linear_solver/samples/mip_var_array.py

@@ -46,6 +46,8 @@ def main():
     # [START solver]
     # Create the mip solver with the SCIP backend.
     solver = pywraplp.Solver.CreateSolver('SCIP')
+    if not solver:
+        return
     # [END solver]
 
     # [START program_part2]

ortools/linear_solver/samples/simple_lp_program.py

@@ -22,6 +22,8 @@ def main():
     # [START solver]
     # Create the linear solver with the GLOP backend.
     solver = pywraplp.Solver.CreateSolver('GLOP')
+    if not solver:
+        return
     # [END solver]
 
     # [START variables]

ortools/linear_solver/samples/simple_mip_program.py

@@ -22,6 +22,8 @@ def main():
     # [START solver]
     # Create the mip solver with the SCIP backend.
     solver = pywraplp.Solver.CreateSolver('SCIP')
+    if not solver:
+        return
     # [END solver]
 
     # [START variables]

ortools/linear_solver/samples/stigler_diet.py

@@ -224,8 +224,9 @@ def main():
 
     # [START solver]
     # Instantiate a Glop solver and naming it.
-    solver = pywraplp.Solver('StiglerDietExample',
-                             pywraplp.Solver.GLOP_LINEAR_PROGRAMMING)
+    solver = pywraplp.Solver.CreateSolver('GLOP')
+    if not solver:
+        return
     # [END solver]
 
     # [START variables]