ortools.linear_solver.python.model_builder_helper

class LinearExpr(pybind11_builtins.pybind11_object):

Holds an linear expression.

A linear expression is built from constants and variables. For example, x + 2.0 * (y - z + 1.0).

Linear expressions are used in Model models in constraints and in the objective:
  • You can define linear constraints as in:
  model.add(x + 2 * y <= 5.0)
  model.add(sum(array_of_vars) == 5.0)
  • In Model, the objective is a linear expression:
  model.minimize(x + 2.0 * y + z)
  • For large arrays, using the LinearExpr class is faster that using the python sum() function. You can create constraints and the objective from lists of linear expressions or coefficients as follows:
  model.minimize(model_builder.LinearExpr.sum(expressions))
  model.add(model_builder.LinearExpr.weighted_sum(expressions, coeffs) >= 0)
LinearExpr(*args, **kwargs)
def sum(unknown):

sum(args, *kwargs) -> ortools.linear_solver.python.model_builder_helper.LinearExpr

Creates sum(expressions) [+ constant].

def weighted_sum(unknown):

weighted_sum(expressions: Sequence, coefficients: list[float], *, constant: float = 0.0) -> ortools.linear_solver.python.model_builder_helper.LinearExpr

Creates sum(expressions[i] * coefficients[i]) [+ constant].

def term(unknown):

term(args, *kwargs) Overloaded function.

  1. term(expr: ortools.linear_solver.python.model_builder_helper.LinearExpr, coeff: float) -> ortools.linear_solver.python.model_builder_helper.LinearExpr

Returns expr * coeff.

  1. term(expr: ortools.linear_solver.python.model_builder_helper.LinearExpr, coeff: float, *, constant: float) -> ortools.linear_solver.python.model_builder_helper.LinearExpr

Returns expr * coeff [+ constant].

  1. term(value: float, coeff: float, *, constant: float) -> ortools.linear_solver.python.model_builder_helper.LinearExpr

Returns value * coeff [+ constant].

def affine(unknown):

affine(args, *kwargs) Overloaded function.

  1. affine(expr: ortools.linear_solver.python.model_builder_helper.LinearExpr, coeff: float, constant: float = 0.0) -> ortools.linear_solver.python.model_builder_helper.LinearExpr

Returns expr * coeff + constant.

  1. affine(value: float, coeff: float, constant: float = 0.0) -> ortools.linear_solver.python.model_builder_helper.LinearExpr

Returns value * coeff + constant.

def constant(unknown):

constant(value: float) -> ortools.linear_solver.python.model_builder_helper.LinearExpr

Returns a constant linear expression.

class FlatExpr(LinearExpr):

Holds an linear expression.

A linear expression is built from constants and variables. For example, x + 2.0 * (y - z + 1.0).

Linear expressions are used in Model models in constraints and in the objective:
  • You can define linear constraints as in:
  model.add(x + 2 * y <= 5.0)
  model.add(sum(array_of_vars) == 5.0)
  • In Model, the objective is a linear expression:
  model.minimize(x + 2.0 * y + z)
  • For large arrays, using the LinearExpr class is faster that using the python sum() function. You can create constraints and the objective from lists of linear expressions or coefficients as follows:
  model.minimize(model_builder.LinearExpr.sum(expressions))
  model.add(model_builder.LinearExpr.weighted_sum(expressions, coeffs) >= 0)
FlatExpr()

__init__(args, *kwargs) Overloaded function.

  1. __init__(self: ortools.linear_solver.python.model_builder_helper.FlatExpr, arg0: ortools.linear_solver.python.model_builder_helper.LinearExpr) -> None

  2. __init__(self: ortools.linear_solver.python.model_builder_helper.FlatExpr, arg0: ortools.linear_solver.python.model_builder_helper.LinearExpr, arg1: ortools.linear_solver.python.model_builder_helper.LinearExpr) -> None

  3. __init__(self: ortools.linear_solver.python.model_builder_helper.FlatExpr, arg0: list[operations_research::mb::Variable], arg1: list[float], arg2: float) -> None

  4. __init__(self: ortools.linear_solver.python.model_builder_helper.FlatExpr, arg0: float) -> None

vars

(arg0: ortools.linear_solver.python.model_builder_helper.FlatExpr) -> list[operations_research::mb::Variable]

def variable_indices(unknown):

variable_indices(self: ortools.linear_solver.python.model_builder_helper.FlatExpr) -> list[int]

Inherited Members
LinearExpr
sum
weighted_sum
term
affine
constant
class SumArray(LinearExpr):

Holds a sum of linear expressions, and constants.

SumArray()

__init__(self: ortools.linear_solver.python.model_builder_helper.SumArray, arg0: list[ortools.linear_solver.python.model_builder_helper.LinearExpr], arg1: float) -> None

Inherited Members
LinearExpr
sum
weighted_sum
term
affine
constant
class AffineExpr(LinearExpr):

Holds an linear expression.

A linear expression is built from constants and variables. For example, x + 2.0 * (y - z + 1.0).

Linear expressions are used in Model models in constraints and in the objective:
  • You can define linear constraints as in:
  model.add(x + 2 * y <= 5.0)
  model.add(sum(array_of_vars) == 5.0)
  • In Model, the objective is a linear expression:
  model.minimize(x + 2.0 * y + z)
  • For large arrays, using the LinearExpr class is faster that using the python sum() function. You can create constraints and the objective from lists of linear expressions or coefficients as follows:
  model.minimize(model_builder.LinearExpr.sum(expressions))
  model.add(model_builder.LinearExpr.weighted_sum(expressions, coeffs) >= 0)
AffineExpr()

__init__(self: ortools.linear_solver.python.model_builder_helper.AffineExpr, arg0: ortools.linear_solver.python.model_builder_helper.LinearExpr, arg1: float, arg2: float) -> None

Inherited Members
LinearExpr
sum
weighted_sum
term
affine
constant
class Variable(LinearExpr):

A variable (continuous or integral).

A Variable is an object that can take on any integer value within defined ranges. Variables appear in constraint like:

x + y >= 5

Solving a model is equivalent to finding, for each variable, a single value from the set of initial values (called the initial domain), such that the model is feasible, or optimal if you provided an objective function.

Variable()

__init__(args, *kwargs) Overloaded function.

  1. __init__(self: ortools.linear_solver.python.model_builder_helper.Variable, arg0: operations_research::mb::ModelBuilderHelper, arg1: int) -> None

  2. __init__(self: ortools.linear_solver.python.model_builder_helper.Variable, arg0: operations_research::mb::ModelBuilderHelper, arg1: float, arg2: float, arg3: bool) -> None

  3. __init__(self: ortools.linear_solver.python.model_builder_helper.Variable, arg0: operations_research::mb::ModelBuilderHelper, arg1: float, arg2: float, arg3: bool, arg4: str) -> None

  4. __init__(self: ortools.linear_solver.python.model_builder_helper.Variable, arg0: operations_research::mb::ModelBuilderHelper, arg1: int, arg2: int, arg3: bool) -> None

  5. __init__(self: ortools.linear_solver.python.model_builder_helper.Variable, arg0: operations_research::mb::ModelBuilderHelper, arg1: int, arg2: int, arg3: bool, arg4: str) -> None

helper

(arg0: ortools.linear_solver.python.model_builder_helper.Variable) -> operations_research::mb::ModelBuilderHelper

objective_coefficient

(arg0: ortools.linear_solver.python.model_builder_helper.Variable) -> float

Inherited Members
LinearExpr
sum
weighted_sum
term
affine
constant
class BoundedLinearExpression(pybind11_builtins.pybind11_object):
BoundedLinearExpression()

__init__(args, *kwargs) Overloaded function.

  1. __init__(self: ortools.linear_solver.python.model_builder_helper.BoundedLinearExpression, arg0: ortools.linear_solver.python.model_builder_helper.LinearExpr, arg1: float, arg2: float) -> None

  2. __init__(self: ortools.linear_solver.python.model_builder_helper.BoundedLinearExpression, arg0: ortools.linear_solver.python.model_builder_helper.LinearExpr, arg1: ortools.linear_solver.python.model_builder_helper.LinearExpr, arg2: float, arg3: float) -> None

  3. __init__(self: ortools.linear_solver.python.model_builder_helper.BoundedLinearExpression, arg0: ortools.linear_solver.python.model_builder_helper.LinearExpr, arg1: int, arg2: int) -> None

  4. __init__(self: ortools.linear_solver.python.model_builder_helper.BoundedLinearExpression, arg0: ortools.linear_solver.python.model_builder_helper.LinearExpr, arg1: ortools.linear_solver.python.model_builder_helper.LinearExpr, arg2: int, arg3: int) -> None

def to_mpmodel_proto(unknown):

to_mpmodel_proto(helper: operations_research::mb::ModelBuilderHelper) -> operations_research::MPModelProto

class MPModelExportOptions(pybind11_builtins.pybind11_object):
MPModelExportOptions()

__init__(self: ortools.linear_solver.python.model_builder_helper.MPModelExportOptions) -> None

class ModelBuilderHelper(pybind11_builtins.pybind11_object):
ModelBuilderHelper()

__init__(self: ortools.linear_solver.python.model_builder_helper.ModelBuilderHelper) -> None

def read_model_from_proto_file(unknown):

read_model_from_proto_file(self: ortools.linear_solver.python.model_builder_helper.ModelBuilderHelper, filename: str) -> bool

def write_model_to_proto_file(unknown):

write_model_to_proto_file(self: ortools.linear_solver.python.model_builder_helper.ModelBuilderHelper, filename: str) -> bool

def import_from_mps_string(unknown):

import_from_mps_string(self: ortools.linear_solver.python.model_builder_helper.ModelBuilderHelper, mps_string: str) -> bool

def import_from_mps_file(unknown):

import_from_mps_file(self: ortools.linear_solver.python.model_builder_helper.ModelBuilderHelper, mps_file: str) -> bool

def import_from_lp_string(unknown):

import_from_lp_string(self: ortools.linear_solver.python.model_builder_helper.ModelBuilderHelper, lp_string: str) -> bool

def import_from_lp_file(unknown):

import_from_lp_file(self: ortools.linear_solver.python.model_builder_helper.ModelBuilderHelper, lp_file: str) -> bool

def fill_model_from_sparse_data(unknown):

fill_model_from_sparse_data(self: ortools.linear_solver.python.model_builder_helper.ModelBuilderHelper, variable_lower_bound: numpy.ndarray[numpy.float64[m, 1]], variable_upper_bound: numpy.ndarray[numpy.float64[m, 1]], objective_coefficients: numpy.ndarray[numpy.float64[m, 1]], constraint_lower_bounds: numpy.ndarray[numpy.float64[m, 1]], constraint_upper_bounds: numpy.ndarray[numpy.float64[m, 1]], constraint_matrix: scipy.sparse.csr_matrix[numpy.float64]) -> None

def add_var(unknown):

add_var(self: ortools.linear_solver.python.model_builder_helper.ModelBuilderHelper) -> int

def add_var_array(unknown):

add_var_array(self: ortools.linear_solver.python.model_builder_helper.ModelBuilderHelper, arg0: list[int], arg1: float, arg2: float, arg3: bool, arg4: str) -> numpy.ndarray[numpy.int32]

def add_var_array_with_bounds(unknown):

add_var_array_with_bounds(self: ortools.linear_solver.python.model_builder_helper.ModelBuilderHelper, arg0: numpy.ndarray[numpy.float64], arg1: numpy.ndarray[numpy.float64], arg2: numpy.ndarray[bool], arg3: str) -> numpy.ndarray[numpy.int32]

def set_var_lower_bound(unknown):

set_var_lower_bound(self: ortools.linear_solver.python.model_builder_helper.ModelBuilderHelper, var_index: int, lb: float) -> None

def set_var_upper_bound(unknown):

set_var_upper_bound(self: ortools.linear_solver.python.model_builder_helper.ModelBuilderHelper, var_index: int, ub: float) -> None

def set_var_integrality(unknown):

set_var_integrality(self: ortools.linear_solver.python.model_builder_helper.ModelBuilderHelper, var_index: int, is_integer: bool) -> None

def set_var_objective_coefficient(unknown):

set_var_objective_coefficient(self: ortools.linear_solver.python.model_builder_helper.ModelBuilderHelper, var_index: int, coeff: float) -> None

def set_objective_coefficients(unknown):

set_objective_coefficients(self: ortools.linear_solver.python.model_builder_helper.ModelBuilderHelper, arg0: list[int], arg1: list[float]) -> None

def set_var_name(unknown):

set_var_name(self: ortools.linear_solver.python.model_builder_helper.ModelBuilderHelper, var_index: int, name: str) -> None

def var_lower_bound(unknown):

var_lower_bound(self: ortools.linear_solver.python.model_builder_helper.ModelBuilderHelper, var_index: int) -> float

def var_upper_bound(unknown):

var_upper_bound(self: ortools.linear_solver.python.model_builder_helper.ModelBuilderHelper, var_index: int) -> float

def var_is_integral(unknown):

var_is_integral(self: ortools.linear_solver.python.model_builder_helper.ModelBuilderHelper, var_index: int) -> bool

def var_objective_coefficient(unknown):

var_objective_coefficient(self: ortools.linear_solver.python.model_builder_helper.ModelBuilderHelper, var_index: int) -> float

def var_name(unknown):

var_name(self: ortools.linear_solver.python.model_builder_helper.ModelBuilderHelper, var_index: int) -> str

def add_linear_constraint(unknown):

add_linear_constraint(self: ortools.linear_solver.python.model_builder_helper.ModelBuilderHelper) -> int

def set_constraint_lower_bound(unknown):

set_constraint_lower_bound(self: ortools.linear_solver.python.model_builder_helper.ModelBuilderHelper, ct_index: int, lb: float) -> None

def set_constraint_upper_bound(unknown):

set_constraint_upper_bound(self: ortools.linear_solver.python.model_builder_helper.ModelBuilderHelper, ct_index: int, ub: float) -> None

def add_term_to_constraint(unknown):

add_term_to_constraint(self: ortools.linear_solver.python.model_builder_helper.ModelBuilderHelper, ct_index: int, var_index: int, coeff: float) -> None

def add_terms_to_constraint(unknown):

add_terms_to_constraint(self: ortools.linear_solver.python.model_builder_helper.ModelBuilderHelper, arg0: int, arg1: list[ortools.linear_solver.python.model_builder_helper.Variable], arg2: list[float]) -> None

def safe_add_term_to_constraint(unknown):

safe_add_term_to_constraint(self: ortools.linear_solver.python.model_builder_helper.ModelBuilderHelper, ct_index: int, var_index: int, coeff: float) -> None

def set_constraint_name(unknown):

set_constraint_name(self: ortools.linear_solver.python.model_builder_helper.ModelBuilderHelper, ct_index: int, name: str) -> None

def set_constraint_coefficient(unknown):

set_constraint_coefficient(self: ortools.linear_solver.python.model_builder_helper.ModelBuilderHelper, ct_index: int, var_index: int, coeff: float) -> None

def constraint_lower_bound(unknown):

constraint_lower_bound(self: ortools.linear_solver.python.model_builder_helper.ModelBuilderHelper, ct_index: int) -> float

def constraint_upper_bound(unknown):

constraint_upper_bound(self: ortools.linear_solver.python.model_builder_helper.ModelBuilderHelper, ct_index: int) -> float

def constraint_name(unknown):

constraint_name(self: ortools.linear_solver.python.model_builder_helper.ModelBuilderHelper, ct_index: int) -> str

def constraint_var_indices(unknown):

constraint_var_indices(self: ortools.linear_solver.python.model_builder_helper.ModelBuilderHelper, ct_index: int) -> list[int]

def constraint_coefficients(unknown):

constraint_coefficients(self: ortools.linear_solver.python.model_builder_helper.ModelBuilderHelper, ct_index: int) -> list[float]

def add_enforced_linear_constraint(unknown):

add_enforced_linear_constraint(self: ortools.linear_solver.python.model_builder_helper.ModelBuilderHelper) -> int

def is_enforced_linear_constraint(unknown):

is_enforced_linear_constraint(self: ortools.linear_solver.python.model_builder_helper.ModelBuilderHelper, arg0: int) -> bool

def set_enforced_constraint_lower_bound(unknown):

set_enforced_constraint_lower_bound(self: ortools.linear_solver.python.model_builder_helper.ModelBuilderHelper, ct_index: int, lb: float) -> None

def set_enforced_constraint_upper_bound(unknown):

set_enforced_constraint_upper_bound(self: ortools.linear_solver.python.model_builder_helper.ModelBuilderHelper, ct_index: int, ub: float) -> None

def add_term_to_enforced_constraint(unknown):

add_term_to_enforced_constraint(self: ortools.linear_solver.python.model_builder_helper.ModelBuilderHelper, ct_index: int, var_index: int, coeff: float) -> None

def add_terms_to_enforced_constraint(unknown):

add_terms_to_enforced_constraint(self: ortools.linear_solver.python.model_builder_helper.ModelBuilderHelper, arg0: int, arg1: list[ortools.linear_solver.python.model_builder_helper.Variable], arg2: list[float]) -> None

def safe_add_term_to_enforced_constraint(unknown):

safe_add_term_to_enforced_constraint(self: ortools.linear_solver.python.model_builder_helper.ModelBuilderHelper, ct_index: int, var_index: int, coeff: float) -> None

def set_enforced_constraint_name(unknown):

set_enforced_constraint_name(self: ortools.linear_solver.python.model_builder_helper.ModelBuilderHelper, ct_index: int, name: str) -> None

def set_enforced_constraint_coefficient(unknown):

set_enforced_constraint_coefficient(self: ortools.linear_solver.python.model_builder_helper.ModelBuilderHelper, ct_index: int, var_index: int, coeff: float) -> None

def enforced_constraint_lower_bound(unknown):

enforced_constraint_lower_bound(self: ortools.linear_solver.python.model_builder_helper.ModelBuilderHelper, ct_index: int) -> float

def enforced_constraint_upper_bound(unknown):

enforced_constraint_upper_bound(self: ortools.linear_solver.python.model_builder_helper.ModelBuilderHelper, ct_index: int) -> float

def enforced_constraint_name(unknown):

enforced_constraint_name(self: ortools.linear_solver.python.model_builder_helper.ModelBuilderHelper, ct_index: int) -> str

def enforced_constraint_var_indices(unknown):

enforced_constraint_var_indices(self: ortools.linear_solver.python.model_builder_helper.ModelBuilderHelper, ct_index: int) -> list[int]

def enforced_constraint_coefficients(unknown):

enforced_constraint_coefficients(self: ortools.linear_solver.python.model_builder_helper.ModelBuilderHelper, ct_index: int) -> list[float]

def set_enforced_constraint_indicator_variable_index(unknown):

set_enforced_constraint_indicator_variable_index(self: ortools.linear_solver.python.model_builder_helper.ModelBuilderHelper, ct_index: int, var_index: int) -> None

def set_enforced_constraint_indicator_value(unknown):

set_enforced_constraint_indicator_value(self: ortools.linear_solver.python.model_builder_helper.ModelBuilderHelper, ct_index: int, positive: bool) -> None

def enforced_constraint_indicator_variable_index(unknown):

enforced_constraint_indicator_variable_index(self: ortools.linear_solver.python.model_builder_helper.ModelBuilderHelper, ct_index: int) -> int

def enforced_constraint_indicator_value(unknown):

enforced_constraint_indicator_value(self: ortools.linear_solver.python.model_builder_helper.ModelBuilderHelper, ct_index: int) -> bool

def num_variables(unknown):

num_variables(self: ortools.linear_solver.python.model_builder_helper.ModelBuilderHelper) -> int

def num_constraints(unknown):

num_constraints(self: ortools.linear_solver.python.model_builder_helper.ModelBuilderHelper) -> int

def set_name(unknown):

set_name(self: ortools.linear_solver.python.model_builder_helper.ModelBuilderHelper, name: str) -> None

def clear_objective(unknown):

clear_objective(self: ortools.linear_solver.python.model_builder_helper.ModelBuilderHelper) -> None

def maximize(unknown):

maximize(self: ortools.linear_solver.python.model_builder_helper.ModelBuilderHelper) -> bool

def set_maximize(unknown):

set_maximize(self: ortools.linear_solver.python.model_builder_helper.ModelBuilderHelper, maximize: bool) -> None

def set_objective_offset(unknown):

set_objective_offset(self: ortools.linear_solver.python.model_builder_helper.ModelBuilderHelper, offset: float) -> None

def objective_offset(unknown):

objective_offset(self: ortools.linear_solver.python.model_builder_helper.ModelBuilderHelper) -> float

def clear_hints(unknown):

clear_hints(self: ortools.linear_solver.python.model_builder_helper.ModelBuilderHelper) -> None

def add_hint(unknown):

add_hint(self: ortools.linear_solver.python.model_builder_helper.ModelBuilderHelper, var_index: int, var_value: float) -> None

class SolveStatus(pybind11_builtins.pybind11_object):

Members:

OPTIMAL

FEASIBLE

INFEASIBLE

UNBOUNDED

ABNORMAL

NOT_SOLVED

MODEL_IS_VALID

CANCELLED_BY_USER

UNKNOWN_STATUS

MODEL_INVALID

INVALID_SOLVER_PARAMETERS

SOLVER_TYPE_UNAVAILABLE

INCOMPATIBLE_OPTIONS

SolveStatus()

__init__(self: ortools.linear_solver.python.model_builder_helper.SolveStatus, value: int) -> None

name

name(self: object) -> str

OPTIMAL = <SolveStatus.OPTIMAL: 0>
FEASIBLE = <SolveStatus.FEASIBLE: 1>
INFEASIBLE = <SolveStatus.INFEASIBLE: 2>
UNBOUNDED = <SolveStatus.UNBOUNDED: 3>
ABNORMAL = <SolveStatus.ABNORMAL: 4>
NOT_SOLVED = <SolveStatus.NOT_SOLVED: 5>
MODEL_IS_VALID = <SolveStatus.MODEL_IS_VALID: 6>
CANCELLED_BY_USER = <SolveStatus.CANCELLED_BY_USER: 7>
UNKNOWN_STATUS = <SolveStatus.UNKNOWN_STATUS: 8>
MODEL_INVALID = <SolveStatus.MODEL_INVALID: 9>
INVALID_SOLVER_PARAMETERS = <SolveStatus.INVALID_SOLVER_PARAMETERS: 10>
SOLVER_TYPE_UNAVAILABLE = <SolveStatus.SOLVER_TYPE_UNAVAILABLE: 11>
INCOMPATIBLE_OPTIONS = <SolveStatus.INCOMPATIBLE_OPTIONS: 12>
OPTIMAL = <SolveStatus.OPTIMAL: 0>
FEASIBLE = <SolveStatus.FEASIBLE: 1>
INFEASIBLE = <SolveStatus.INFEASIBLE: 2>
UNBOUNDED = <SolveStatus.UNBOUNDED: 3>
ABNORMAL = <SolveStatus.ABNORMAL: 4>
NOT_SOLVED = <SolveStatus.NOT_SOLVED: 5>
MODEL_IS_VALID = <SolveStatus.MODEL_IS_VALID: 6>
CANCELLED_BY_USER = <SolveStatus.CANCELLED_BY_USER: 7>
UNKNOWN_STATUS = <SolveStatus.UNKNOWN_STATUS: 8>
MODEL_INVALID = <SolveStatus.MODEL_INVALID: 9>
INVALID_SOLVER_PARAMETERS = <SolveStatus.INVALID_SOLVER_PARAMETERS: 10>
SOLVER_TYPE_UNAVAILABLE = <SolveStatus.SOLVER_TYPE_UNAVAILABLE: 11>
INCOMPATIBLE_OPTIONS = <SolveStatus.INCOMPATIBLE_OPTIONS: 12>
class ModelSolverHelper(pybind11_builtins.pybind11_object):
ModelSolverHelper()

__init__(self: ortools.linear_solver.python.model_builder_helper.ModelSolverHelper, arg0: str) -> None

def solver_is_supported(unknown):

solver_is_supported(self: ortools.linear_solver.python.model_builder_helper.ModelSolverHelper) -> bool

def solve_serialized_request(unknown):

solve_serialized_request(self: ortools.linear_solver.python.model_builder_helper.ModelSolverHelper, arg0: str) -> bytes

def interrupt_solve(unknown):

interrupt_solve(self: ortools.linear_solver.python.model_builder_helper.ModelSolverHelper) -> bool

Returns true if the interrupt signal was correctly sent, that is, if the underlying solver supports it.

def set_log_callback(unknown):

set_log_callback(self: ortools.linear_solver.python.model_builder_helper.ModelSolverHelper, arg0: std::function, std::allocator > const&)>) -> None

def clear_log_callback(unknown):

clear_log_callback(self: ortools.linear_solver.python.model_builder_helper.ModelSolverHelper) -> None

def set_time_limit_in_seconds(unknown):

set_time_limit_in_seconds(self: ortools.linear_solver.python.model_builder_helper.ModelSolverHelper, limit: float) -> None

def set_solver_specific_parameters(unknown):

set_solver_specific_parameters(self: ortools.linear_solver.python.model_builder_helper.ModelSolverHelper, solver_specific_parameters: str) -> None

def enable_output(unknown):

enable_output(self: ortools.linear_solver.python.model_builder_helper.ModelSolverHelper, output: bool) -> None

def has_solution(unknown):

has_solution(self: ortools.linear_solver.python.model_builder_helper.ModelSolverHelper) -> bool

def has_response(unknown):

has_response(self: ortools.linear_solver.python.model_builder_helper.ModelSolverHelper) -> bool

def response(unknown):

response(self: ortools.linear_solver.python.model_builder_helper.ModelSolverHelper) -> operations_research::MPSolutionResponse

def status_string(unknown):

status_string(self: ortools.linear_solver.python.model_builder_helper.ModelSolverHelper) -> str

def wall_time(unknown):

wall_time(self: ortools.linear_solver.python.model_builder_helper.ModelSolverHelper) -> float

def user_time(unknown):

user_time(self: ortools.linear_solver.python.model_builder_helper.ModelSolverHelper) -> float

def objective_value(unknown):

objective_value(self: ortools.linear_solver.python.model_builder_helper.ModelSolverHelper) -> float

def best_objective_bound(unknown):

best_objective_bound(self: ortools.linear_solver.python.model_builder_helper.ModelSolverHelper) -> float

def variable_value(unknown):

variable_value(self: ortools.linear_solver.python.model_builder_helper.ModelSolverHelper, var_index: int) -> float

def reduced_cost(unknown):

reduced_cost(self: ortools.linear_solver.python.model_builder_helper.ModelSolverHelper, var_index: int) -> float

def dual_value(unknown):

dual_value(self: ortools.linear_solver.python.model_builder_helper.ModelSolverHelper, ct_index: int) -> float

def activity(unknown):

activity(self: ortools.linear_solver.python.model_builder_helper.ModelSolverHelper, ct_index: int) -> float

def variable_values(unknown):

variable_values(self: ortools.linear_solver.python.model_builder_helper.ModelSolverHelper) -> numpy.ndarray[numpy.float64[m, 1]]

def reduced_costs(unknown):

reduced_costs(self: ortools.linear_solver.python.model_builder_helper.ModelSolverHelper) -> numpy.ndarray[numpy.float64[m, 1]]

def dual_values(unknown):

dual_values(self: ortools.linear_solver.python.model_builder_helper.ModelSolverHelper) -> numpy.ndarray[numpy.float64[m, 1]]