add model cloning to model_builder python + sample

ortools/linear_solver/samples/BUILD.bazel

@@ -44,6 +44,8 @@ code_sample_py(name = "assignment_mb")
 
 code_sample_py(name = "bin_packing_mb")
 
+code_sample_py(name = "copy_model_mb")
+
 code_sample_py(name = "simple_lp_program_mb")
 
 code_sample_py(name = "simple_mip_program_mb")

ortools/linear_solver/samples/copy_model_mb.py

@@ -0,0 +1,92 @@
+#!/usr/bin/env python3
+# Copyright 2010-2022 Google LLC
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+# [START program]
+"""Integer programming examples that show how to use the APIs."""
+# [START import]
+import math
+
+from ortools.linear_solver.python import model_builder
+# [END import]
+
+
+def main():
+    # [START model]
+    # Create the model.
+    model = model_builder.ModelBuilder()
+    # [END model]
+
+    # [START variables]
+    # x and y are integer non-negative variables.
+    x = model.new_int_var(0.0, math.inf, "x")
+    y = model.new_int_var(0.0, math.inf, "y")
+    # [END variables]
+
+    # [START constraints]
+    # x + 7 * y <= 17.5.
+    c1 = model.add(x + 7 * y <= 17.5)
+
+    # x <= 3.5.
+    c2 = model.add(x <= 3.5)
+    # [END constraints]
+
+    # [START objective]
+    # Maximize x + 10 * y.
+    model.maximize(x + 10 * y)
+    # [END objective]
+
+    # Deep copy.
+    print("Cloning the model.")
+    model_copy = model.clone()
+    x_copy = model_copy.var_from_index(x.index)
+    y_copy = model_copy.var_from_index(y.index)
+    z_copy = model_copy.new_bool_var("z")
+    c2_copy = model_copy.linear_constraint_from_index(c2.index)
+
+    # Add new constraint.
+    model_copy.add(x_copy >= 1)
+    print("Number of constraints in original model =", model.num_constraints)
+    print("Number of constraints in cloned model =", model_copy.num_constraints)
+
+    # Modify a constraint.
+    c2_copy.add_term(z_copy, 2.0)
+
+    print(model_copy.export_to_lp_string())
+
+    # [START solve]
+    # Create the solver with the SCIP backend, and solve the model.
+    solver = model_builder.ModelSolver("scip")
+    status = solver.solve(model_copy)
+    # [END solve]
+
+    # [START print_solution]
+    if status == model_builder.SolveStatus.OPTIMAL:
+        print("Solution:")
+        print("Objective value =", solver.objective_value)
+        print("x =", solver.value(x_copy))
+        print("y =", solver.value(y_copy))
+        print("z =", solver.value(z_copy))        
+    else:
+        print("The problem does not have an optimal solution.")
+    # [END print_solution]
+
+    # [START advanced]
+    print("\nAdvanced usage:")
+    print("Problem solved in %f seconds" % solver.wall_time)
+    # [END advanced]
+
+
+if __name__ == "__main__":
+    main()
+# [END program]