Search Parameters

All three solvers in PyQBPP — EasySolver, ExhaustiveSolver, and ABS3Solver — accept search parameters through search(). Parameters are passed as a standard Python dict. Values can be strings, integers, or floats — they are automatically converted to strings before being passed to the C++ backend.

Passing Parameters

Pass a dict directly to search():

sol = solver.search({"time_limit": 10, "target_energy": 0})

Values can be mixed — strings, integers, and floats:

sol = solver.search({"time_limit": 2.5, "target_energy": "0"})

When you need to build parameters programmatically, create a dict and add entries:

params = {}
params["time_limit"] = 10
params["target_energy"] = 0
sol = solver.search(params)

No special Params object is needed — a standard Python dict is all that is required. Internally, PyQBPP converts each value to a string and passes the key-value pairs to the C++ solver.

Common Parameters

The following parameters are shared by all three solvers:

Parameter	Type	Description
"target_energy"	int	Stop when a solution with energy ≤ this value is found.
"enable_default_callback"	int (0/1)	Print newly obtained best solutions to stderr. Default: 0.
"topk_sols"	int	Keep up to N top-k solutions during the search.
"best_energy_sols"	int (0/1)	Keep all solutions with the best energy. 0 = unlimited count.

EasySolver Parameters

Parameter	Type	Description	Default
"time_limit"	float	Time limit in seconds. 0 for no limit.	10.0
"target_energy"	int	Target energy.	(none)
"enable_default_callback"	int (0/1)	Print progress.	0
"topk_sols"	int	Top-k solutions to keep.	(disabled)
"best_energy_sols"	int	Best-energy solutions to keep.	(disabled)

Example:

solver = qbpp.EasySolver(f)
sol = solver.search({"time_limit": 5, "target_energy": 0})

ExhaustiveSolver Parameters

The ExhaustiveSolver does not have a "time_limit" parameter because it performs a complete search.

Parameter	Type	Description	Default
"target_energy"	int	Target energy (for early termination).	(none)
"verbose"	int (0/1)	Display search progress percentage.	0
"enable_default_callback"	int (0/1)	Print progress.	0
"topk_sols"	int	Top-k solutions to keep.	(disabled)
"best_energy_sols"	int (0/1)	Keep all optimal solutions.	(disabled)
"all_sols"	int (0/1)	Keep all feasible solutions.	(disabled)

Example:

solver = qbpp.ExhaustiveSolver(f)
sol = solver.search({"target_energy": 0})

Multiple solutions can be collected by combining parameters:

sol = solver.search({"best_energy_sols": 0, "target_energy": 0})
for s in sol.sols():
    print(s.energy)

ABS3Solver Parameters

Parameter	Type	Description	Default
"time_limit"	float	Time limit in seconds.	10.0
"target_energy"	int	Target energy.	(none)
"enable_default_callback"	int (0/1)	Print progress.	0
"topk_sols"	int	Top-k solutions to keep.	(disabled)
"best_energy_sols"	int (0/1)	Keep all optimal solutions.	(disabled)
"cpu_enable"	int (0/1)	Enable/disable CPU solver.	1
"cpu_thread_count"	int	Number of CPU threads.	(auto)
"block_count"	int	Number of GPU blocks.	(auto)
"thread_count"	int	Number of GPU threads per block.	(auto)

Example:

solver = qbpp.ABS3Solver(f)
sol = solver.search({"time_limit": 10, "target_energy": 0})

Error Handling

Unknown parameter keys will cause a runtime error.