import optuna

import numpy as np


def create_study_with_various_trials(storage: str) -> None:
    rng = np.random.RandomState(42)

    def _objective_intermediate_values(trial: optuna.Trial) -> float:
        x = trial.suggest_categorical("x", choices=["a", "b", "c"])
        rnd = rng.random()
        if rnd < 0.25:
            trial.report(trial.number, step=0)
            trial.report(trial.number + 1, step=1)
        elif rnd < 0.5:
            trial.report(trial.number, step=0)
            raise optuna.TrialPruned()
        elif rnd < 0.75:
            raise optuna.TrialPruned()
        else:
            raise ValueError("Unexpected Error.")

        return 0.0

    study = optuna.create_study(study_name="various-trials", storage=storage)
    study.optimize(_objective_intermediate_values, n_trials=40, catch=(Exception,))

create_study_with_various_trials(storage=storage)