"""
TradeSense AI — In-Memory Market Data Cache
TTL-enforced caching with rich audit metadata. API credentials are NEVER stored.
"""

import time
from datetime import date, datetime, timezone
from typing import Dict, Optional, Tuple, Any
import pandas as pd

from backend.config.settings import settings
from backend.app.schemas.contracts import DatasetMetadata


class CacheEntryMetadata:
    """
    Audit metadata stored alongside each cached dataset.
    SECURITY: Must never contain API keys, auth headers, or secrets.
    """
    __slots__ = (
        "ticker", "start_date", "end_date", "cutoff_session",
        "dataset_version", "quality_status", "provider",
        "lineage_hash", "created_at", "expires_at",
    )

    def __init__(
        self,
        ticker: str,
        start_date: date,
        end_date: date,
        cutoff_session: date,
        dataset_version: str,
        quality_status: str,
        provider: str,
        lineage_hash: str,
        ttl_seconds: int,
    ):
        self.ticker = ticker
        self.start_date = start_date
        self.end_date = end_date
        self.cutoff_session = cutoff_session
        self.dataset_version = dataset_version
        self.quality_status = quality_status
        self.provider = provider
        self.lineage_hash = lineage_hash
        self.created_at: datetime = datetime.now(timezone.utc)
        self.expires_at: float = time.time() + ttl_seconds

    def is_expired(self) -> bool:
        return time.time() > self.expires_at

    def safe_dict(self) -> Dict[str, Any]:
        """Returns a safe, credential-free audit snapshot of this entry."""
        return {
            "ticker": self.ticker,
            "start_date": str(self.start_date),
            "end_date": str(self.end_date),
            "cutoff_session": str(self.cutoff_session),
            "dataset_version": self.dataset_version,
            "quality_status": self.quality_status,
            "provider": self.provider,
            "lineage_hash": self.lineage_hash,
            "created_at": self.created_at.isoformat(),
            "expires_at": datetime.fromtimestamp(self.expires_at, tz=timezone.utc).isoformat(),
        }


class CacheEntry:
    """Stores a frozen DataFrame + DatasetMetadata pair with TTL enforcement."""

    def __init__(
        self,
        df: pd.DataFrame,
        metadata: DatasetMetadata,
        ttl_seconds: int,
    ):
        self.df = df.copy()
        self.metadata = metadata
        self.cache_meta = CacheEntryMetadata(
            ticker=metadata.ticker,
            start_date=metadata.start_session,
            end_date=metadata.cutoff_session,
            cutoff_session=metadata.cutoff_session,
            dataset_version=metadata.dataset_version,
            quality_status=(
                metadata.quality_report.quality_status.value
                if metadata.quality_report else "UNKNOWN"
            ),
            provider=metadata.source_primary,
            lineage_hash=metadata.sha256_hash,
            ttl_seconds=ttl_seconds,
        )

    def is_expired(self) -> bool:
        return self.cache_meta.is_expired()


class MarketDataCache:
    """
    Thread-safe in-memory cache for canonical OHLCV datasets.
    Enforces:
    - TTL expiry
    - Cutoff T validation on retrieval (cached data cannot bypass temporal isolation)
    - No credential storage
    """

    def __init__(self):
        self._cache: Dict[str, CacheEntry] = {}

    # ─────────────────────────────────────────────────────────────────────
    # Internal helpers
    # ─────────────────────────────────────────────────────────────────────

    @staticmethod
    def _build_key(ticker: str, start_date: Any, end_date: Any, cutoff_session: Any) -> str:
        return f"{ticker.upper()}|{start_date}|{end_date}|{cutoff_session}"

    # ─────────────────────────────────────────────────────────────────────
    # Public API
    # ─────────────────────────────────────────────────────────────────────

    def get(
        self,
        ticker: str,
        start_date: Any,
        end_date: Any,
        cutoff_session: Any,
    ) -> Optional[Tuple[pd.DataFrame, DatasetMetadata]]:
        """
        Returns a cached (DataFrame, DatasetMetadata) pair if:
        - The cache is enabled
        - An unexpired entry exists for this key
        - The cached dataset's cutoff_session matches the requested cutoff (temporal safety)
        """
        if not settings.market_data.cache_enabled:
            return None

        key = self._build_key(ticker, start_date, end_date, cutoff_session)
        entry = self._cache.get(key)
        if entry is None:
            return None

        if entry.is_expired():
            del self._cache[key]
            return None

        # CRITICAL: Validate that the cached cutoff matches the requested cutoff.
        # This prevents stale cache entries from violating temporal isolation.
        if str(entry.cache_meta.cutoff_session) != str(cutoff_session):
            return None

        return entry.df.copy(), entry.metadata

    def set(
        self,
        ticker: str,
        start_date: Any,
        end_date: Any,
        cutoff_session: Any,
        df: pd.DataFrame,
        metadata: DatasetMetadata,
        is_historical: bool = True,
    ) -> None:
        """Stores a canonical dataset under the given key with appropriate TTL."""
        if not settings.market_data.cache_enabled:
            return

        key = self._build_key(ticker, start_date, end_date, cutoff_session)
        ttl = (
            settings.market_data.historical_cache_ttl_seconds
            if is_historical
            else settings.market_data.latest_data_cache_ttl_seconds
        )
        self._cache[key] = CacheEntry(df, metadata, ttl)

    def get_entry_metadata(
        self,
        ticker: str,
        start_date: Any,
        end_date: Any,
        cutoff_session: Any,
    ) -> Optional[Dict[str, Any]]:
        """Returns safe, credential-free metadata for a cached entry."""
        key = self._build_key(ticker, start_date, end_date, cutoff_session)
        entry = self._cache.get(key)
        if entry is None or entry.is_expired():
            return None
        return entry.cache_meta.safe_dict()

    def invalidate(self, ticker: str) -> int:
        """Evicts all entries for a ticker. Returns count evicted."""
        keys_to_drop = [k for k in self._cache if k.startswith(f"{ticker.upper()}|")]
        for k in keys_to_drop:
            del self._cache[k]
        return len(keys_to_drop)

    def clear(self) -> None:
        self._cache.clear()

    def stats(self) -> Dict[str, Any]:
        """Returns aggregate cache statistics (no credentials)."""
        live = sum(1 for e in self._cache.values() if not e.is_expired())
        return {
            "total_entries": len(self._cache),
            "live_entries": live,
            "expired_entries": len(self._cache) - live,
        }


# Global Singleton Market Data Cache
data_cache = MarketDataCache()