from __future__ import annotations

from collections.abc import Sequence
from typing import Any
from typing import TYPE_CHECKING

from optuna._warnings import optuna_warn


if TYPE_CHECKING:
    from optuna.trial import FrozenTrial


_CONSTRAINTS_KEY = "constraints"


def _is_constrained_optimization(trials: Sequence[FrozenTrial]) -> bool:
    """Return whether the given trials are created in constrained optimization."""

    return any(len(trial.constraints) > 0 for trial in trials)


def _get_feasible_trials(trials: Sequence[FrozenTrial]) -> list[FrozenTrial]:
    """Return feasible trials from given trials.

    Returns:
        A list of feasible trials.
    """

    feasible_trials = []
    for trial in trials:
        constraints = trial.constraints.values()
        if all(x <= 0.0 for x in constraints):
            feasible_trials.append(trial)
    return feasible_trials


def _get_constraints_from_system_attrs(system_attrs: dict[str, Any]) -> dict[str, float]:
    constraints_dict: dict[str, float] = {}

    # Load constraints from old format (list)
    con = system_attrs.get(_CONSTRAINTS_KEY)
    if con is not None:
        for i, c in enumerate(con):
            constraints_dict[str(i)] = c

    # Load constraints from new format (individual keys)
    prefix = f"{_CONSTRAINTS_KEY}:"
    for key, value in system_attrs.items():
        if key.startswith(prefix):
            constraint_key = key[len(prefix) :]
            if constraint_key in constraints_dict:
                optuna_warn("Overwrite an old format constraint.")
            constraints_dict[constraint_key] = value
    return constraints_dict