"""Comprehensive error handling for the trading analysis platform."""

from typing import Optional


class TradingAnalysisError(Exception):
    """Base exception for all trading analysis errors."""

    def __init__(
        self,
        message: str,
        details: Optional[str] = None,
        suggestion: Optional[str] = None,
    ):
        """
        Initialize error with comprehensive information.

        Args:
            message: The main error message
            details: Additional technical details about the error
            suggestion: User-friendly suggestion on how to resolve the issue
        """
        self.message = message
        self.details = details
        self.suggestion = suggestion
        super().__init__(self.format_error())

    def format_error(self) -> str:
        """Format error message with all available information."""
        parts = [f"❌ {self.message}"]

        if self.details:
            parts.append(f"\nDetails: {self.details}")

        if self.suggestion:
            parts.append(f"\n💡 Suggestion: {self.suggestion}")

        return "\n".join(parts)


# Data Provider Errors
class DataProviderError(TradingAnalysisError):
    """Base class for data provider errors."""

    pass


class TickerNotFoundError(DataProviderError):
    """Raised when a ticker symbol is not found."""

    def __init__(self, ticker: str, provider: str = "data provider"):
        super().__init__(
            message=f"Ticker '{ticker}' not found",
            details=f"The ticker symbol '{ticker}' could not be found in {provider}",
            suggestion=(
                f"Please verify the ticker symbol is correct. "
                f"Examples: AAPL (stock), BTC-USD (crypto), GC=F (commodity), ^GSPC (index)"
            ),
        )


class NoDataReturnedError(DataProviderError):
    """Raised when no data is returned for a valid ticker."""

    def __init__(self, ticker: str, timeframe: str, provider: str = "data provider"):
        super().__init__(
            message=f"No data available for {ticker}",
            details=f"No OHLC data returned for ticker '{ticker}' with timeframe '{timeframe}' from {provider}",
            suggestion=(
                f"This could mean: "
                f"1) The market is closed and no recent data is available, "
                f"2) The ticker doesn't support this timeframe, "
                f"3) Try a different timeframe (e.g., '1d' instead of '{timeframe}')"
            ),
        )


class RateLimitError(DataProviderError):
    """Raised when API rate limits are exceeded."""

    def __init__(self, provider: str, wait_time: Optional[int] = None):
        wait_msg = f" Please wait {wait_time} seconds." if wait_time else ""
        super().__init__(
            message=f"Rate limit exceeded for {provider}",
            details=f"Too many requests to {provider} API.{wait_msg}",
            suggestion=(
                f"1) Wait a few minutes before trying again, "
                f"2) Consider upgrading to a premium API key, "
                f"3) Use a different data provider in Settings"
            ),
        )


class InsufficientDataError(DataProviderError):
    """Raised when there's insufficient data for analysis."""

    def __init__(self, ticker: str, required: int, actual: int):
        super().__init__(
            message=f"Insufficient data for analysis of {ticker}",
            details=f"Need at least {required} data points for analysis, but only {actual} available",
            suggestion=(
                f"1) Try a longer time period (increase date range), "
                f"2) Use a higher timeframe (e.g., '1d' instead of '1m'), "
                f"3) Check if the asset has been trading long enough"
            ),
        )


class DataValidationError(DataProviderError):
    """Raised when data validation fails."""

    def __init__(self, issue: str):
        super().__init__(
            message="Data validation failed",
            details=issue,
            suggestion="This might be a temporary data provider issue. Try again in a few moments.",
        )


# API and Configuration Errors
class APIKeyError(TradingAnalysisError):
    """Raised when API keys are missing or invalid."""

    def __init__(self, provider: str):
        super().__init__(
            message=f"Missing or invalid API key for {provider}",
            details=f"The {provider} API key is either not configured or invalid",
            suggestion=(
                f"1) Set your {provider} API key in the .env file or API Keys tab, "
                f"2) Verify the API key is valid and active, "
                f"3) Restart the application after setting the key"
            ),
        )


class ConfigurationError(TradingAnalysisError):
    """Raised when configuration is invalid."""

    def __init__(self, parameter: str, issue: str):
        super().__init__(
            message=f"Invalid configuration for {parameter}",
            details=issue,
            suggestion=f"Check the Settings tab and verify {parameter} is configured correctly",
        )


# LLM Errors
class LLMError(TradingAnalysisError):
    """Base class for LLM-related errors."""

    pass


class LLMProviderError(LLMError):
    """Raised when LLM provider encounters an error."""

    def __init__(self, provider: str, model: str, error: str):
        super().__init__(
            message=f"{provider} API error",
            details=f"Model '{model}' returned error: {error}",
            suggestion=(
                f"1) Check your {provider} API key is valid and has credits, "
                f"2) Verify you have access to the '{model}' model, "
                f"3) Try a different model in Settings, "
                f"4) Check your internet connection"
            ),
        )


class LLMTimeoutError(LLMError):
    """Raised when LLM request times out."""

    def __init__(self, agent: str, timeout: int):
        super().__init__(
            message=f"Agent '{agent}' timed out",
            details=f"LLM request exceeded timeout of {timeout} seconds",
            suggestion=(
                f"1) Try again - this might be temporary network congestion, "
                f"2) Check your internet connection, "
                f"3) Consider using a faster model in Settings"
            ),
        )


class LLMContextLimitError(LLMError):
    """Raised when context length is exceeded."""

    def __init__(self, agent: str, tokens: int, limit: int):
        super().__init__(
            message=f"Context length exceeded for agent '{agent}'",
            details=f"Input requires {tokens} tokens but model limit is {limit}",
            suggestion=(
                f"1) Try analyzing a shorter time period, "
                f"2) Use a higher timeframe (fewer data points), "
                f"3) Use a model with larger context window"
            ),
        )


# Analysis Errors
class AnalysisError(TradingAnalysisError):
    """Base class for analysis errors."""

    pass


class IndicatorCalculationError(AnalysisError):
    """Raised when indicator calculation fails."""

    def __init__(self, indicator: str, reason: str):
        super().__init__(
            message=f"Failed to calculate {indicator}",
            details=reason,
            suggestion=(
                f"1) Ensure there's enough data for {indicator} calculation, "
                f"2) Try adjusting indicator parameters in Settings, "
                f"3) Check if the data quality is sufficient"
            ),
        )


class PatternRecognitionError(AnalysisError):
    """Raised when pattern recognition fails."""

    def __init__(self, reason: str):
        super().__init__(
            message="Pattern recognition failed",
            details=reason,
            suggestion="This might be due to unusual market data or chart generation issues. Try again.",
        )


class ChartGenerationError(AnalysisError):
    """Raised when chart generation fails."""

    def __init__(self, reason: str):
        super().__init__(
            message="Failed to generate chart",
            details=reason,
            suggestion=(
                "1) Ensure matplotlib and mplfinance are installed correctly, "
                "2) Check that the data directory is writable, "
                "3) Verify sufficient disk space is available"
            ),
        )


# Workflow Errors
class WorkflowError(TradingAnalysisError):
    """Base class for workflow execution errors."""

    pass


class AgentExecutionError(WorkflowError):
    """Raised when an agent fails to execute."""

    def __init__(self, agent: str, step: str, error: str):
        super().__init__(
            message=f"Agent '{agent}' failed",
            details=f"Error during {step}: {error}",
            suggestion=(
                f"1) Check the logs for more details, "
                f"2) Verify API keys are configured correctly, "
                f"3) Try running the analysis again"
            ),
        )


class WorkflowTimeoutError(WorkflowError):
    """Raised when workflow execution times out."""

    def __init__(self, workflow: str, timeout: int):
        super().__init__(
            message=f"Workflow '{workflow}' timed out",
            details=f"Analysis exceeded maximum time of {timeout} seconds",
            suggestion=(
                f"1) Try using Technical Analysis instead of Comprehensive for faster results, "
                f"2) Check your internet connection, "
                f"3) The analysis was taking too long - try again"
            ),
        )


# Helper Functions
def format_exception_for_user(e: Exception) -> str:
    """
    Format any exception into a user-friendly error message.

    Args:
        e: The exception to format

    Returns:
        Formatted error message with helpful information
    """
    if isinstance(e, TradingAnalysisError):
        return e.format_error()

    # Handle common Python exceptions
    error_type = type(e).__name__
    error_msg = str(e)

    # Map common exceptions to user-friendly messages
    if isinstance(e, KeyError):
        return (
            f"❌ Missing required data field: {error_msg}\n"
            f"💡 Suggestion: This might be due to incomplete data from the provider. Try again."
        )
    elif isinstance(e, ValueError):
        return (
            f"❌ Invalid value: {error_msg}\n"
            f"💡 Suggestion: Check your input parameters and try again."
        )
    elif isinstance(e, ConnectionError):
        return (
            f"❌ Connection error: {error_msg}\n"
            f"💡 Suggestion: Check your internet connection and try again."
        )
    elif isinstance(e, TimeoutError):
        return (
            f"❌ Request timed out: {error_msg}\n"
            f"💡 Suggestion: The service is taking too long to respond. Please try again."
        )
    else:
        return (
            f"❌ Unexpected error ({error_type}): {error_msg}\n"
            f"💡 Suggestion: Please try again. If the problem persists, check the logs for details."
        )


def wrap_provider_error(
    provider: str, ticker: str, operation: str, error: Exception
) -> TradingAnalysisError:
    """
    Wrap provider exceptions into appropriate TradingAnalysisError subclasses.

    Args:
        provider: Name of the data provider
        ticker: Ticker symbol being accessed
        operation: Operation being performed (e.g., "fetch_ohlc", "fetch_fundamentals")
        error: The original exception

    Returns:
        Appropriate TradingAnalysisError subclass
    """
    error_msg = str(error).lower()

    # Check for specific error patterns
    if "no data" in error_msg or "empty" in error_msg:
        return NoDataReturnedError(ticker, "unknown", provider)
    elif "rate limit" in error_msg or "too many requests" in error_msg:
        return RateLimitError(provider)
    elif (
        "not found" in error_msg
        or "invalid ticker" in error_msg
        or "invalid symbol" in error_msg
    ):
        return TickerNotFoundError(ticker, provider)
    elif (
        "api key" in error_msg
        or "unauthorized" in error_msg
        or "forbidden" in error_msg
    ):
        return APIKeyError(provider)
    else:
        return DataProviderError(
            message=f"{provider} error during {operation}",
            details=str(error),
            suggestion=(
                f"1) Verify the ticker '{ticker}' is correct, "
                f"2) Check your internet connection, "
                f"3) Try using a different data provider in Settings"
            ),
        )