{"id":28357935,"url":"https://github.com/optuna/kurobako-py","last_synced_at":"2025-08-31T20:40:25.457Z","repository":{"id":42081914,"uuid":"185230720","full_name":"optuna/kurobako-py","owner":"optuna","description":"A Python library to help implement kurobako's solvers and 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license](https://img.shields.io/badge/license-MIT-blue.svg)](https://github.com/sile/kurobako-py)\n[![Actions Status](https://github.com/sile/kurobako-py/workflows/CI/badge.svg)](https://github.com/sile/kurobako-py/actions)\n\nA Python library to help implement [kurobako]'s solvers and problems.\n\n[kurobako]: https://github.com/sile/kurobako\n\n\nInstallation\n------------\n\n```console\n$ pip install kurobako\n```\n\nUsage Examples\n--------------\n\n### Define a solver based on random search\n\n```python\n# filename: random_solver.py\nimport numpy as np\n\nfrom kurobako import problem\nfrom kurobako import solver\n\n\nclass RandomSolverFactory(solver.SolverFactory):\n    def specification(self):\n        return solver.SolverSpec(name='Random Search')\n\n    def create_solver(self, seed, problem):\n        return RandomSolver(seed, problem)\n\n\nclass RandomSolver(solver.Solver):\n    def __init__(self, seed, problem):\n        self._rng = np.random.RandomState(seed)\n        self._problem = problem\n\n    def ask(self, idg):\n        params = []\n        for p in self._problem.params:\n            if p.distribution == problem.Distribution.UNIFORM:\n                params.append(self._rng.uniform(p.range.low, p.range.high))\n            else:\n                low = np.log(p.range.low)\n                high = np.log(p.range.high)\n                params.append(float(np.exp(self._rng.uniform(low, high))))\n\n        trial_id = idg.generate()\n        next_step = self._problem.last_step\n        return solver.NextTrial(trial_id, params, next_step)\n\n    def tell(self, trial):\n        pass\n\n\nif __name__ == '__main__':\n    runner = solver.SolverRunner(RandomSolverFactory())\n    runner.run()\n```\n\n### Define a problem that represents a quadratic function `x**2 + y`\n\n```python\n# filename: quadratic_problem.py\nfrom kurobako import problem\n\n\nclass QuadraticProblemFactory(problem.ProblemFactory):\n    def specification(self):\n        params = [\n            problem.Var('x', problem.ContinuousRange(-10, 10)),\n            problem.Var('y', problem.DiscreteRange(-3, 3))\n        ]\n        return problem.ProblemSpec(name='Quadratic Function',\n                                   params=params,\n                                   values=[problem.Var('x**2 + y')])\n\n    def create_problem(self, seed):\n        return QuadraticProblem()\n\n\nclass QuadraticProblem(problem.Problem):\n    def create_evaluator(self, params):\n        return QuadraticEvaluator(params)\n\n\nclass QuadraticEvaluator(problem.Evaluator):\n    def __init__(self, params):\n        self._x, self._y = params\n        self._current_step = 0\n\n    def current_step(self):\n        return self._current_step\n\n    def evaluate(self, next_step):\n        self._current_step = 1\n        return [self._x**2 + self._y]\n\n\nif __name__ == '__main__':\n    runner = problem.ProblemRunner(QuadraticProblemFactory())\n    runner.run()\n```\n\n### Run a benchmark that uses the above solver and problem\n\n```console\n$ SOLVER=$(kurobako solver command python3 random_solver.py)\n$ PROBLEM=$(kurobako problem command python3 quadratic_problem.py)\n$ kurobako studies --solvers $SOLVER --problems $PROBLEM | kurobako run \u003e result.json\n```\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Foptuna%2Fkurobako-py","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Foptuna%2Fkurobako-py","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Foptuna%2Fkurobako-py/lists"}