src/cache.py

"""Metadata cache for indicators and cube mappings."""

import asyncio
import os
from datetime import datetime, timedelta
from typing import Any

from .api_client import CubeJsClient, get_client
from .cube_resolver import CubeResolver, get_resolver
from .models import IndicatorMetadata, IndicatorListItem


class IndicatorCache:
    """Cache for indicator metadata and cube resolution.
    
    This cache stores indicator metadata loaded at startup and periodically
    refreshes to pick up new indicators. It also initializes the CubeResolver
    for mapping indicator IDs to data cubes.
    """

    def __init__(
        self,
        refresh_interval_seconds: int | None = None,
    ):
        """Initialize the cache.
        
        Args:
            refresh_interval_seconds: How often to refresh the cache.
                Defaults to CACHE_REFRESH_SECONDS env var or 3600 (1 hour).
        """
        self.refresh_interval = timedelta(
            seconds=refresh_interval_seconds
            or int(os.getenv("CACHE_REFRESH_SECONDS", "3600"))
        )
        
        # Indicator metadata by ID
        self._indicators: dict[int, IndicatorMetadata] = {}
        
        # Reference to the cube resolver
        self._resolver: CubeResolver = get_resolver()
        
        # Last refresh timestamp
        self._last_refresh: datetime | None = None
        
        # Lock for thread-safe refresh
        self._refresh_lock = asyncio.Lock()
        
        # Flag to indicate if initial load is complete
        self._initialized = False

    @property
    def is_initialized(self) -> bool:
        """Check if the cache has been initialized."""
        return self._initialized

    @property
    def needs_refresh(self) -> bool:
        """Check if the cache needs to be refreshed."""
        if not self._initialized or self._last_refresh is None:
            return True
        return datetime.now() - self._last_refresh > self.refresh_interval

    @property
    def indicators(self) -> dict[int, IndicatorMetadata]:
        """Get all cached indicators."""
        return self._indicators.copy()

    @property
    def resolver(self) -> CubeResolver:
        """Get the cube resolver instance."""
        return self._resolver

    async def initialize(self, client: CubeJsClient | None = None) -> None:
        """Initialize the cache with data from the API.
        
        This should be called at application startup.
        
        Args:
            client: Optional CubeJsClient instance. If not provided,
                uses the singleton instance.
        """
        if client is None:
            client = get_client()
        
        await self.refresh(client)

    async def refresh(self, client: CubeJsClient | None = None) -> None:
        """Refresh the cache from the API.
        
        Args:
            client: Optional CubeJsClient instance.
        """
        async with self._refresh_lock:
            if client is None:
                client = get_client()
            
            # Load indicator metadata
            await self._load_indicators(client)
            
            # Load and parse /meta for cube resolution
            await self._load_cube_metadata(client)
            
            self._last_refresh = datetime.now()
            self._initialized = True

    async def _load_indicators(self, client: CubeJsClient) -> None:
        """Load all indicator metadata from the API."""
        # Note: Some dimensions listed in /meta may not exist in actual data
        # Only include dimensions that have been validated to work
        dimensions = [
            "indicateur_metadata.id",
            "indicateur_metadata.libelle",
            "indicateur_metadata.unite",
            "indicateur_metadata.description",
            "indicateur_metadata.methode_calcul",
            "indicateur_metadata.annees_disponibles",
            "indicateur_metadata.mailles_disponibles",
            "indicateur_metadata.maille_mini_disponible",
            "indicateur_metadata.couverture_geographique",
            "indicateur_metadata.completion_region",
            "indicateur_metadata.completion_departement",
            "indicateur_metadata.completion_epci",
            "indicateur_metadata.completion_commune",
            "indicateur_metadata.thematique_fnv",
            # Note: secteur_fnv, enjeux_fnv, levier_fnv cause errors despite being in schema
        ]
        
        data = await client.load_indicators_metadata(
            dimensions=dimensions,
            limit=1000,  # Should be enough for all indicators
        )
        
        self._indicators.clear()
        for row in data:
            try:
                indicator = IndicatorMetadata.from_api_response(row)
                self._indicators[indicator.id] = indicator
            except Exception as e:
                # Log but don't fail on individual indicator parsing errors
                print(f"Warning: Failed to parse indicator: {e}")

    async def _load_cube_metadata(self, client: CubeJsClient) -> None:
        """Load cube metadata from /meta and initialize the resolver."""
        meta = await client.get_meta()
        self._resolver.load_from_meta(meta)

    def get_indicator(self, indicator_id: int) -> IndicatorMetadata | None:
        """Get indicator metadata by ID.
        
        Args:
            indicator_id: The indicator ID.
            
        Returns:
            The indicator metadata, or None if not found.
        """
        return self._indicators.get(indicator_id)

    def get_cube_name(self, indicator_id: int, maille: str) -> str | None:
        """Get the data cube name for an indicator at a specific maille.
        
        Args:
            indicator_id: The indicator ID.
            maille: The geographic level.
            
        Returns:
            The cube name, or None if not found.
        """
        return self._resolver.find_cube_for_indicator(indicator_id, maille)

    def list_indicators(
        self,
        thematique: str | None = None,
        maille: str | None = None,
    ) -> list[IndicatorListItem]:
        """List indicators with optional filtering.
        
        Args:
            thematique: Filter by thematique_fnv (case-insensitive partial match).
            maille: Filter by available geographic level.
            
        Returns:
            List of matching indicators.
        """
        results = []
        
        for indicator in self._indicators.values():
            # Apply thematique filter
            if thematique:
                if not indicator.thematique_fnv:
                    continue
                if thematique.lower() not in indicator.thematique_fnv.lower():
                    continue
            
            # Apply maille filter
            if maille:
                if not indicator.has_geographic_level(maille):
                    continue
            
            results.append(
                IndicatorListItem(
                    id=indicator.id,
                    libelle=indicator.libelle,
                    unite=indicator.unite,
                    mailles_disponibles=indicator.mailles_disponibles,
                    thematique_fnv=indicator.thematique_fnv,
                )
            )
        
        # Sort by ID for consistent ordering
        results.sort(key=lambda x: x.id)
        return results

    def search_indicators(self, query: str) -> list[IndicatorListItem]:
        """Search indicators by keyword.
        
        Searches in libelle and description fields (case-insensitive).
        
        Args:
            query: Search query string.
            
        Returns:
            List of matching indicators.
        """
        if not query or not query.strip():
            return self.list_indicators()
        
        query_lower = query.lower().strip()
        query_words = query_lower.split()
        results = []
        
        for indicator in self._indicators.values():
            # Search in libelle and description
            searchable = " ".join(
                filter(None, [indicator.libelle, indicator.description])
            ).lower()
            
            # Check if all query words are present
            if all(word in searchable for word in query_words):
                results.append(
                    IndicatorListItem(
                        id=indicator.id,
                        libelle=indicator.libelle,
                        unite=indicator.unite,
                        mailles_disponibles=indicator.mailles_disponibles,
                        thematique_fnv=indicator.thematique_fnv,
                    )
                )
        
        # Sort by relevance (exact match in libelle first, then by ID)
        def sort_key(item: IndicatorListItem) -> tuple[int, int]:
            exact_match = 0 if query_lower in item.libelle.lower() else 1
            return (exact_match, item.id)
        
        results.sort(key=sort_key)
        return results


# Singleton cache instance
_cache_instance: IndicatorCache | None = None


def get_cache() -> IndicatorCache:
    """Get or create the singleton IndicatorCache instance.
    
    Returns:
        The shared IndicatorCache instance.
    """
    global _cache_instance
    if _cache_instance is None:
        _cache_instance = IndicatorCache()
    return _cache_instance


async def initialize_cache(client: CubeJsClient | None = None) -> IndicatorCache:
    """Initialize the singleton cache.
    
    This should be called at application startup.
    
    Args:
        client: Optional CubeJsClient instance.
        
    Returns:
        The initialized cache.
    """
    cache = get_cache()
    if not cache.is_initialized:
        await cache.initialize(client)
    return cache


async def refresh_cache_if_needed(client: CubeJsClient | None = None) -> None:
    """Refresh the cache if it's stale.
    
    Args:
        client: Optional CubeJsClient instance.
    """
    cache = get_cache()
    if cache.needs_refresh:
        await cache.refresh(client)