cp_model.py File Reference

Go to the source code of this file.

Classes
class	ortools.sat.python.cp_model.LinearExpr
class	ortools.sat.python.cp_model._Sum
class	ortools.sat.python.cp_model._ProductCst
class	ortools.sat.python.cp_model._SumArray
class	ortools.sat.python.cp_model._WeightedSum
class	ortools.sat.python.cp_model.IntVar
class	ortools.sat.python.cp_model._NotBooleanVariable
class	ortools.sat.python.cp_model.BoundedLinearExpression
class	ortools.sat.python.cp_model.Constraint
class	ortools.sat.python.cp_model.IntervalVar
class	ortools.sat.python.cp_model.CpModel
class	ortools.sat.python.cp_model.CpSolver
class	ortools.sat.python.cp_model.CpSolverSolutionCallback
class	ortools.sat.python.cp_model.ObjectiveSolutionPrinter
class	ortools.sat.python.cp_model.VarArrayAndObjectiveSolutionPrinter
class	ortools.sat.python.cp_model.VarArraySolutionPrinter

Namespaces
namespace	ortools
namespace	ortools.sat
namespace	ortools.sat.python
namespace	ortools.sat.python.cp_model

Functions
str	ortools.sat.python.cp_model.display_bounds (Sequence[int] bounds)
str	ortools.sat.python.cp_model.short_name (cp_model_pb2.CpModelProto model, int i)
str	ortools.sat.python.cp_model.short_expr_name (cp_model_pb2.CpModelProto model, cp_model_pb2.LinearExpressionProto e)
bool	ortools.sat.python.cp_model.object_is_a_true_literal (LiteralT literal)
bool	ortools.sat.python.cp_model.object_is_a_false_literal (LiteralT literal)
Union[Iterable[LiteralT], LiteralT]	ortools.sat.python.cp_model.expand_generator_or_tuple (Union[Tuple[LiteralT,...], Iterable[LiteralT]] args)
Union[Iterable[LinearExprT], LinearExprT]	ortools.sat.python.cp_model.expand_generator_or_tuple (Union[Tuple[LinearExprT,...], Iterable[LinearExprT]] args)
	ortools.sat.python.cp_model.expand_generator_or_tuple (args)
int	ortools.sat.python.cp_model.evaluate_linear_expr (LinearExprT expression, cp_model_pb2.CpSolverResponse solution)
bool	ortools.sat.python.cp_model.evaluate_boolean_expression (LiteralT literal, cp_model_pb2.CpSolverResponse solution)
pd.Index	ortools.sat.python.cp_model._get_index (_IndexOrSeries obj)
pd.Series	ortools.sat.python.cp_model._attribute_series (*, Callable[[IntVar], IntegralT] func, _IndexOrSeries values)
pd.Series	ortools.sat.python.cp_model._convert_to_integral_series_and_validate_index (Union[IntegralT, pd.Series] value_or_series, pd.Index index)
pd.Series	ortools.sat.python.cp_model._convert_to_linear_expr_series_and_validate_index (Union[LinearExprT, pd.Series] value_or_series, pd.Index index)
pd.Series	ortools.sat.python.cp_model._convert_to_literal_series_and_validate_index (Union[LiteralT, pd.Series] value_or_series, pd.Index index)

Variables
	ortools.sat.python.cp_model.Domain = sorted_interval_list.Domain
	ortools.sat.python.cp_model.INT_MIN = -(2**63)
int	ortools.sat.python.cp_model.INT_MAX = 2**63 - 1
	ortools.sat.python.cp_model.INT32_MIN = -(2**31)
int	ortools.sat.python.cp_model.INT32_MAX = 2**31 - 1
	ortools.sat.python.cp_model.UNKNOWN = cp_model_pb2.UNKNOWN
	ortools.sat.python.cp_model.MODEL_INVALID = cp_model_pb2.MODEL_INVALID
	ortools.sat.python.cp_model.FEASIBLE = cp_model_pb2.FEASIBLE
	ortools.sat.python.cp_model.INFEASIBLE = cp_model_pb2.INFEASIBLE
	ortools.sat.python.cp_model.OPTIMAL = cp_model_pb2.OPTIMAL
	ortools.sat.python.cp_model.CHOOSE_FIRST = cp_model_pb2.DecisionStrategyProto.CHOOSE_FIRST
	ortools.sat.python.cp_model.CHOOSE_LOWEST_MIN = cp_model_pb2.DecisionStrategyProto.CHOOSE_LOWEST_MIN
	ortools.sat.python.cp_model.CHOOSE_HIGHEST_MAX = cp_model_pb2.DecisionStrategyProto.CHOOSE_HIGHEST_MAX
	ortools.sat.python.cp_model.CHOOSE_MIN_DOMAIN_SIZE = cp_model_pb2.DecisionStrategyProto.CHOOSE_MIN_DOMAIN_SIZE
	ortools.sat.python.cp_model.CHOOSE_MAX_DOMAIN_SIZE = cp_model_pb2.DecisionStrategyProto.CHOOSE_MAX_DOMAIN_SIZE
	ortools.sat.python.cp_model.SELECT_MIN_VALUE = cp_model_pb2.DecisionStrategyProto.SELECT_MIN_VALUE
	ortools.sat.python.cp_model.SELECT_MAX_VALUE = cp_model_pb2.DecisionStrategyProto.SELECT_MAX_VALUE
	ortools.sat.python.cp_model.SELECT_LOWER_HALF = cp_model_pb2.DecisionStrategyProto.SELECT_LOWER_HALF
	ortools.sat.python.cp_model.SELECT_UPPER_HALF = cp_model_pb2.DecisionStrategyProto.SELECT_UPPER_HALF
	ortools.sat.python.cp_model.AUTOMATIC_SEARCH = sat_parameters_pb2.SatParameters.AUTOMATIC_SEARCH
	ortools.sat.python.cp_model.FIXED_SEARCH = sat_parameters_pb2.SatParameters.FIXED_SEARCH
	ortools.sat.python.cp_model.PORTFOLIO_SEARCH = sat_parameters_pb2.SatParameters.PORTFOLIO_SEARCH
	ortools.sat.python.cp_model.LP_SEARCH = sat_parameters_pb2.SatParameters.LP_SEARCH
	ortools.sat.python.cp_model.PSEUDO_COST_SEARCH = sat_parameters_pb2.SatParameters.PSEUDO_COST_SEARCH
tuple	ortools.sat.python.cp_model.PORTFOLIO_WITH_QUICK_RESTART_SEARCH
	ortools.sat.python.cp_model.HINT_SEARCH = sat_parameters_pb2.SatParameters.HINT_SEARCH
	ortools.sat.python.cp_model.PARTIAL_FIXED_SEARCH = sat_parameters_pb2.SatParameters.PARTIAL_FIXED_SEARCH
	ortools.sat.python.cp_model.RANDOMIZED_SEARCH = sat_parameters_pb2.SatParameters.RANDOMIZED_SEARCH
	ortools.sat.python.cp_model.IntegralT = Union[int, np.int8, np.uint8, np.int32, np.uint32, np.int64, np.uint64]
tuple	ortools.sat.python.cp_model.IntegralTypes
	ortools.sat.python.cp_model.NumberT
tuple	ortools.sat.python.cp_model.NumberTypes
	ortools.sat.python.cp_model.LiteralT = Union["IntVar", "_NotBooleanVariable", IntegralT, bool]
	ortools.sat.python.cp_model.BoolVarT = Union["IntVar", "_NotBooleanVariable"]
	ortools.sat.python.cp_model.VariableT = Union["IntVar", IntegralT]
	ortools.sat.python.cp_model.LinearExprT = Union["LinearExpr", "IntVar", IntegralT]
	ortools.sat.python.cp_model.ObjLinearExprT = Union["LinearExpr", NumberT]
	ortools.sat.python.cp_model.BoundedLinearExprT = Union["BoundedLinearExpression", bool]
	ortools.sat.python.cp_model.ArcT = Tuple[IntegralT, IntegralT, LiteralT]
	ortools.sat.python.cp_model._IndexOrSeries = Union[pd.Index, pd.Series]