"""Proteasome organelle for quality inspection and degradation."""
from __future__ import annotations
from dataclasses import dataclass, field
from typing import Any, Callable, Optional

from .types import UbiquitinTag, UbiquitinPool, DegradationResult
from .components import ProvenanceContext, Deubiquitinase, ChaperoneRepair


@dataclass
class Proteasome:
    """
    Inspects ubiquitin tags and enforces quality thresholds.

    Biological parallel: The 26S proteasome that degrades
    ubiquitin-tagged proteins.
    """

    # Thresholds (adjusted by degron)
    degradation_threshold: float = 0.3
    block_threshold: float = 0.1

    # Capacity (ATP-dependent in biology)
    max_throughput: int = 100
    current_load: int = 0

    # Components
    chaperones: list[ChaperoneRepair] = field(default_factory=list)
    deubiquitinases: list[Deubiquitinase] = field(default_factory=list)

    # Handlers
    fallback_strategy: Optional[Callable[[Any, UbiquitinTag], Any]] = None
    review_queue: list = field(default_factory=list)

    # Metrics
    inspected: int = 0
    repairs_attempted: int = 0
    repairs_succeeded: int = 0

    def inspect(
        self,
        data: Any,
        tag: UbiquitinTag,
        context: ProvenanceContext,
        pool: UbiquitinPool,
    ) -> tuple[Optional[Any], UbiquitinTag, DegradationResult]:
        """
        Inspect data and tag, potentially degrading or blocking.

        Returns: (data, updated_tag, result)
        """
        self.inspected += 1

        # Capacity check - if overloaded, pass through
        if self.current_load >= self.max_throughput:
            return data, tag, DegradationResult.PASSED

        self.current_load += 1

        # Calculate degron-adjusted thresholds
        effective_degrade = tag.effective_threshold(self.degradation_threshold)
        effective_block = tag.effective_threshold(self.block_threshold)

        # Step 1: DUB rescue attempt
        for dub in self.deubiquitinases:
            if dub.active(context) and dub.rescue_condition(tag, context):
                tag = tag.restore_confidence(dub.rescue_amount)
                if tag.confidence >= effective_degrade:
                    return data, tag, DegradationResult.RESCUED

        # Step 2: Chaperone repair (before degradation)
        if tag.confidence < effective_degrade:
            for chaperone in self.chaperones:
                if chaperone.can_repair(data, tag):
                    self.repairs_attempted += 1
                    repaired_data, success = chaperone.repair(data, tag)
                    if success:
                        self.repairs_succeeded += 1
                        tag = tag.restore_confidence(chaperone.confidence_boost)
                        return repaired_data, tag, DegradationResult.REPAIRED

        # Step 3: Threshold enforcement
        if tag.confidence < effective_block:
            pool.recycle(tag)
            return None, tag, DegradationResult.BLOCKED

        if tag.confidence < effective_degrade:
            pool.recycle(tag)
            if self.fallback_strategy:
                degraded = self.fallback_strategy(data, tag)
                return degraded, tag, DegradationResult.DEGRADED
            else:
                self.review_queue.append((data, tag, context))
                return None, tag, DegradationResult.QUEUED_REVIEW

        # Passed inspection
        return data, tag, DegradationResult.PASSED

    def reset_cycle(self) -> None:
        """Reset throughput for new cycle."""
        self.current_load = 0

    def stats(self) -> dict:
        """Return inspection statistics."""
        return {
            "inspected": self.inspected,
            "repairs_attempted": self.repairs_attempted,
            "repairs_succeeded": self.repairs_succeeded,
            "repair_rate": (
                self.repairs_succeeded / self.repairs_attempted
                if self.repairs_attempted > 0 else 0.0
            ),
            "pending_review": len(self.review_queue),
            "current_load": self.current_load,
        }
