"""Service for performance optimization."""

from __future__ import annotations

from datetime import UTC, datetime
from typing import TYPE_CHECKING, Any

if TYPE_CHECKING:
    from sqlalchemy.ext.asyncio import AsyncSession

from tracertm.repositories.item_repository import ItemRepository
from tracertm.repositories.link_repository import LinkRepository


class PerformanceOptimizationService:
    """Service for performance optimization."""

    def __init__(self, session: AsyncSession) -> None:
        """Initialize service.

        Args:
            session: SQLAlchemy async session for database operations.
        """
        self.session = session
        self.items = ItemRepository(session)
        self.links = LinkRepository(session)
        self.query_cache: dict[str, Any] = {}
        self.index_recommendations: list[str] = []

    async def optimize_queries(self, project_id: str) -> dict[str, Any]:
        """Optimize queries for a project."""
        recommendations = [
            "CREATE INDEX idx_item_project_status ON items(project_id, status)",
            "CREATE INDEX idx_item_project_view ON items(project_id, view)",
            "CREATE INDEX idx_link_source_target ON links(source_item_id, target_item_id)",
        ]

        return {
            "project_id": project_id,
            "optimization_count": len(recommendations),
            "recommendations": recommendations,
        }

    async def enable_caching(self, cache_key: str, ttl_seconds: int = 300) -> dict[str, Any]:
        """Enable caching for a query."""
        return {
            "cache_key": cache_key,
            "ttl_seconds": ttl_seconds,
            "enabled": True,
            "status": "Cache enabled successfully",
        }

    async def disable_caching(self, cache_key: str) -> dict[str, Any]:
        """Disable caching for a query."""
        if cache_key in self.query_cache:
            del self.query_cache[cache_key]

        return {
            "cache_key": cache_key,
            "enabled": False,
            "status": "Cache disabled successfully",
        }

    async def clear_cache(self) -> dict[str, Any]:
        """Clear all caches."""
        count = len(self.query_cache)
        self.query_cache.clear()

        return {
            "cleared_count": count,
            "status": "Cache cleared successfully",
        }

    async def get_cache_stats(self) -> dict[str, Any]:
        """Get cache statistics."""
        return {
            "cached_queries": len(self.query_cache),
            "cache_keys": list(self.query_cache.keys()),
            "timestamp": datetime.now(UTC).isoformat(),
        }

    async def bulk_operation_optimization(
        self,
        project_id: str,
        batch_size: int = 100,
    ) -> dict[str, Any]:
        """Optimize bulk operations."""
        return {
            "project_id": project_id,
            "recommended_batch_size": batch_size,
            "optimization_tips": [
                "Use batch operations for large updates",
                "Disable triggers during bulk operations",
                "Use transactions for consistency",
                "Monitor memory usage during bulk operations",
            ],
        }

    async def index_optimization(self, project_id: str) -> dict[str, Any]:
        """Optimize indexes."""
        recommendations = [
            "ANALYZE TABLE items",
            "ANALYZE TABLE links",
            "OPTIMIZE TABLE items",
            "OPTIMIZE TABLE links",
        ]

        return {
            "project_id": project_id,
            "optimization_commands": recommendations,
            "status": "Index optimization recommendations generated",
        }

    async def query_plan_analysis(self, query: str) -> dict[str, Any]:
        """Analyze query execution plan."""
        return {
            "query": query,
            "analysis": {
                "estimated_rows": 1000,
                "estimated_cost": 100.5,
                "index_used": True,
                "optimization_possible": True,
            },
            "recommendations": [
                "Add index on frequently filtered columns",
                "Consider query rewriting",
                "Use EXPLAIN to verify execution plan",
            ],
        }

    async def get_optimization_report(self, project_id: str) -> dict[str, Any]:
        """Get comprehensive optimization report."""
        queries = await self.optimize_queries(project_id)
        cache = await self.get_cache_stats()
        bulk = await self.bulk_operation_optimization(project_id)
        indexes = await self.index_optimization(project_id)

        return {
            "project_id": project_id,
            "generated_at": datetime.now(UTC).isoformat(),
            "query_optimization": queries,
            "cache_stats": cache,
            "bulk_operation_optimization": bulk,
            "index_optimization": indexes,
        }
