langgoap.CSPMetadata

class CSPMetadata(status, solver_time_ms=0.0, resource_usage=(), objective_values=<factory>, schedule=(), makespan=None, plans_evaluated=0, scale_factor=1000, explanation=None)

Results from the CSP optimizer.

Parameters:

• status (CSPStatus)

• solver_time_ms (float)

• resource_usage (tuple[ResourceUsage, ...])

• objective_values (MappingProxyType)

• schedule (tuple[ScheduleEntry, ...])

• makespan (timedelta | None)

• plans_evaluated (int)

• scale_factor (int)

• explanation (Any)

status

Solve outcome.

Type:

langgoap.planner.csp.CSPStatus

solver_time_ms

Wall-clock time spent in the solver.

Type:

float

resource_usage

Per-key resource breakdown.

Type:

tuple[langgoap.planner.csp.ResourceUsage, …]

objective_values

Objective function values for the selected plan.

Type:

types.MappingProxyType

schedule

Per-action temporal schedule.

Type:

tuple[langgoap.planner.csp.ScheduleEntry, …]

makespan

Total schedule duration (max end time), or None if no scheduling was performed.

Type:

datetime.timedelta | None

plans_evaluated

Number of candidate plans evaluated.

Type:

int

scale_factor

Integer scaling factor used for CP-SAT (float → int).

Type:

int

explanation

Explanation of why the plan is infeasible, or None when the plan is feasible or when no explanation has been computed.

Type:

Any

__init__(status, solver_time_ms=0.0, resource_usage=(), objective_values=<factory>, schedule=(), makespan=None, plans_evaluated=0, scale_factor=1000, explanation=None)

Parameters:

• status (CSPStatus)

• solver_time_ms (float)

• resource_usage (tuple[ResourceUsage, ...])

• objective_values (MappingProxyType)

• schedule (tuple[ScheduleEntry, ...])

• makespan (timedelta | None)

• plans_evaluated (int)

• scale_factor (int)

• explanation (Any)

Return type:

None

Methods

__init__(status[, solver_time_ms, ...])

Attributes

status
solver_time_ms
resource_usage
objective_values
schedule
makespan
plans_evaluated
scale_factor
explanation