# Source code for minizinc.helpers

```
import sys
from dataclasses import asdict, is_dataclass
from datetime import timedelta
from typing import Any, Dict, Optional, Sequence, Union
import minizinc
if sys.version_info >= (3, 8):
from typing import Protocol
class DataClass(Protocol):
# Checking for this attribute is currently the most reliable way to
# ascertain that something is a dataclass
__dataclass_fields__: Dict
else:
DataClass = Any
[docs]def check_result(
model: minizinc.Model,
result: minizinc.Result,
solver: minizinc.Solver,
solution_nrs: Optional[Sequence[int]] = None,
) -> bool:
"""Checks a result object for a model using the given solver.
Check the correctness of the solving process using a (different) solver
configuration. The solver configuration is now used to confirm is
assignment of the variables is correct. By default only the last solution
will be checked. A sequence of solution numbers can be provided to check
multiple solutions.
Args:
model (Model): To model for which the solution was provided
result (Result): The solution to be checked
solver (Solver): The solver configuration used to check the
solutions.
solution_nrs: The index set of solutions to be checked. (default:
``-1``)
Returns:
bool: True if the given result object is correctly verified.
"""
if solution_nrs is None:
solution_nrs = [-1]
solutions = (
result.solution if isinstance(result.solution, list) else [result.solution]
)
for i in solution_nrs:
sol = solutions[i]
if not check_solution(model, sol, result.status, solver):
return False
return True
[docs]def check_solution(
model: minizinc.Model,
solution: Union[DataClass, Dict[str, Any]],
status: minizinc.Status,
solver: minizinc.Solver,
) -> bool:
"""Checks a solution for a model using the given solver.
Check the correctness of the solving process using a (different) solver
configuration. A new model instance is created and will be assigned all
available values from the given solution. The Instance.solve() method is
then used to ensure that the same solution with the same expected status is
reached. Note that this method will not check the optimality of a solution.
Args:
model (Model): To model for which the solution was provided
solution (Union[DataClass, Dict[str, Any]]): The solution to be checked
status (Status): The expected (compatible) MiniZinc status
solver (Solver): The solver configuration used to check the
solution.
Returns:
bool: True if the given solution are correctly verified.
"""
instance = minizinc.Instance(solver, model)
if is_dataclass(solution):
solution = asdict(solution)
for k, v in solution.items():
if k not in ("objective", "__output_item"):
instance[k] = v
try:
check = instance.solve(timeout=timedelta(seconds=5))
if status == check.status:
return True
elif check.status in [
minizinc.Status.SATISFIED,
minizinc.Status.OPTIMAL_SOLUTION,
] and status in [
minizinc.Status.SATISFIED,
minizinc.Status.OPTIMAL_SOLUTION,
minizinc.Status.ALL_SOLUTIONS,
]:
return True
else:
return False
except minizinc.MiniZincError:
if status == minizinc.Status.ERROR:
return True
return False
```