"""
Insider Data Service for aggregating and analyzing insider trading data.
"""

import logging
from dataclasses import dataclass
from enum import Enum
from typing import Any

from tradingagents.domains.marketdata.finnhub_client import FinnhubClient

logger = logging.getLogger(__name__)


class DataQuality(Enum):
    """Data quality levels for insider data."""

    HIGH = "high"
    MEDIUM = "medium"
    LOW = "low"


@dataclass
class InsiderTransaction:
    """Insider transaction data."""

    date: str  # YYYY-MM-DD format
    insider_name: str
    title: str
    transaction_type: str  # "Purchase", "Sale", "Exercise", etc.
    shares: int
    price_per_share: float
    total_value: float
    shares_owned_after: int
    filing_date: str


@dataclass
class InsiderSentimentContext:
    """Insider sentiment context for trading analysis."""

    symbol: str
    period: dict[str, str]  # {"start": "YYYY-MM-DD", "end": "YYYY-MM-DD"}
    transactions: list[InsiderTransaction]
    sentiment_score: float  # -1.0 to 1.0 (-1: very bearish, 1: very bullish)
    net_buying_value: float  # Net buying (positive) or selling (negative) in USD
    insider_count: int  # Number of unique insiders in period
    transaction_count: int
    analysis_summary: str
    metadata: dict[str, Any]


@dataclass
class InsiderTransactionContext:
    """Insider transaction context for detailed transaction analysis."""

    symbol: str
    period: dict[str, str]  # {"start": "YYYY-MM-DD", "end": "YYYY-MM-DD"}
    transactions: list[InsiderTransaction]
    total_transaction_value: float
    net_insider_activity: float  # Net buying/selling activity
    top_insiders: list[dict[str, Any]]  # Top insiders by transaction value
    transaction_summary: dict[str, Any]  # Summary stats by transaction type
    analysis_summary: str
    metadata: dict[str, Any]


class InsiderDataService:
    """Service for insider trading data aggregation and analysis."""

    def __init__(
        self,
        client: FinnhubClient,
        repository: InsiderDataRepository,
    ):
        """
        Initialize insider data service.

        Args:
            client: Client for insider data (e.g., FinnhubClient)
            repository: Repository for cached insider data
            online_mode: Whether to use live data
            **kwargs: Additional configuration
        """
        self.client = client
        self.repository = repository

    def get_insider_sentiment_context(
        self,
        symbol: str,
        start_date: str,
        end_date: str,
    ) -> InsiderSentimentContext:
        """
        Get insider sentiment context for a company.

        Args:
            symbol: Stock ticker symbol
            start_date: Start date in YYYY-MM-DD format
            end_date: End date in YYYY-MM-DD format
            **kwargs: Additional parameters

        Returns:
            InsiderSentimentContext: Insider sentiment analysis
        """
        # TODO: Implement insider sentiment analysis
        transactions = []
        sentiment_score = 0.0
        net_buying_value = 0.0
        analysis_summary = f"Insider sentiment analysis for {symbol}"

        metadata = {
            "data_quality": DataQuality.HIGH if transactions else DataQuality.LOW,
            "service": "insider_data",
            "data_source": "placeholder",
            "analysis_method": "insider_sentiment",
        }

        return InsiderSentimentContext(
            symbol=symbol,
            period={"start": start_date, "end": end_date},
            transactions=transactions,
            sentiment_score=sentiment_score,
            net_buying_value=net_buying_value,
            insider_count=0,
            transaction_count=len(transactions),
            analysis_summary=analysis_summary,
            metadata=metadata,
        )

    def get_insider_transaction_context(
        self,
        symbol: str,
        start_date: str,
        end_date: str,
    ) -> InsiderTransactionContext:
        """
        Get insider transaction context for detailed analysis.

        Args:
            symbol: Stock ticker symbol
            start_date: Start date in YYYY-MM-DD format
            end_date: End date in YYYY-MM-DD format
            **kwargs: Additional parameters

        Returns:
            InsiderTransactionContext: Detailed insider transaction analysis
        """
        # TODO: Implement insider transaction analysis
        transactions = []
        total_transaction_value = 0.0
        net_insider_activity = 0.0
        top_insiders = []
        transaction_summary = {}
        analysis_summary = f"Insider transaction analysis for {symbol}"

        metadata = {
            "data_quality": DataQuality.HIGH if transactions else DataQuality.LOW,
            "service": "insider_data",
            "data_source": "placeholder",
            "analysis_method": "insider_transactions",
        }

        return InsiderTransactionContext(
            symbol=symbol,
            period={"start": start_date, "end": end_date},
            transactions=transactions,
            total_transaction_value=total_transaction_value,
            net_insider_activity=net_insider_activity,
            top_insiders=top_insiders,
            transaction_summary=transaction_summary,
            analysis_summary=analysis_summary,
            metadata=metadata,
        )

    def update_insider_sentiment(
        self,
        symbol: str,
        start_date: str,
        end_date: str,
    ):
        pass  # TODO: fetch insider sentiment with finnhub client, save with repo

    def update_insider_transactions(
        self,
        symbol: str,
        start_date: str,
        end_date: str,
    ):
        pass  # TODO: fetch insider transactions with finnhub client, save with repo