"""
News and Social Media API endpoints for ticker-based sentiment analysis
"""

from datetime import datetime
from typing import Optional, Dict, Any, List
import logging

from fastapi import APIRouter, HTTPException, Query
from pydantic import BaseModel, Field

from app.services.news_social_service import news_social_service

logger = logging.getLogger(__name__)

router = APIRouter()


class NewsArticleSchema(BaseModel):
    """News article schema for API response"""
    title: str
    summary: Optional[str] = None
    content: Optional[str] = None
    url: str
    source: str
    published_at: Optional[str] = None
    author: Optional[str] = None
    relevance_score: Optional[float] = None
    image_url: Optional[str] = None
    tags: List[str] = []


class SocialPostSchema(BaseModel):
    """Social media post schema for API response"""
    title: str
    content: str
    url: str
    platform: str
    author: str
    published_at: Optional[str] = None
    score: Optional[int] = None
    comments_count: Optional[int] = None
    upvotes: Optional[int] = None
    downvotes: Optional[int] = None
    subreddit: Optional[str] = None


class NewsSourcesSchema(BaseModel):
    """News sources breakdown"""
    yahoo_finance: int = 0
    newsapi: int = 0


class SocialPlatformsSchema(BaseModel):
    """Social media platforms breakdown"""
    reddit: int = 0


class NewsSocialSummarySchema(BaseModel):
    """Summary of news and social data"""
    total_items: int
    time_range_days: int
    oldest_item: Optional[str] = None
    newest_item: Optional[str] = None


class NewsSocialResponse(BaseModel):
    """Complete response for ticker news and social data"""
    ticker: str
    retrieved_at: str
    news: Dict[str, Any] = Field(description="News articles and sources breakdown")
    social_media: Dict[str, Any] = Field(description="Social media posts and platforms breakdown")
    summary: NewsSocialSummarySchema


@router.get("/{ticker}", response_model=NewsSocialResponse)
async def get_ticker_news_and_social(
    ticker: str,
    days_back: int = Query(7, ge=1, le=30, description="Number of days to look back for articles (1-30)"),
    max_articles: int = Query(20, ge=1, le=100, description="Maximum number of news articles to return (1-100)"),
    max_social_posts: int = Query(15, ge=0, le=50, description="Maximum number of social media posts to return (0-50)"),
    include_social: bool = Query(True, description="Whether to include social media data")
):
    """
    Get comprehensive news and social media data for a ticker
    
    - **ticker**: Stock ticker symbol (e.g., AAPL, TSLA, QQQ)
    - **days_back**: Number of days to look back for articles (default: 7, max: 30)
    - **max_articles**: Maximum number of news articles to return (default: 20, min: 1, max: 100)
    - **max_social_posts**: Maximum number of social media posts to return (default: 15, max: 50)
    - **include_social**: Whether to include social media data (default: true)
    
    ## Data Sources
    - **News**: Yahoo Finance, NewsAPI
    - **Social Media**: Reddit (multiple investing subreddits)
    
    ## Features
    - ✅ Parallel data fetching from multiple sources
    - ✅ Automatic deduplication and relevance ranking
    - ✅ Rate limiting and error handling
    - ✅ Comprehensive metadata and source attribution
    
    ## Use Cases
    - Sentiment analysis and market research
    - News aggregation for trading decisions  
    - Social media monitoring for retail sentiment
    - Research and fundamental analysis support
    """
    
    try:
        # Validate ticker format
        ticker_upper = ticker.upper().strip()
        if not ticker_upper or len(ticker_upper) > 10:
            raise HTTPException(
                status_code=400, 
                detail=f"Invalid ticker format: {ticker}. Must be 1-10 characters."
            )
        
        logger.info(f"Fetching news and social data for {ticker_upper}")
        
        # Get data from service
        result = await news_social_service.get_ticker_news_and_social(
            ticker=ticker_upper,
            days_back=days_back,
            max_articles=max_articles,
            max_social_posts=max_social_posts,
            include_social=include_social
        )
        
        logger.info(f"Successfully retrieved {result['news']['total_articles']} articles and {result['social_media']['total_posts']} social posts for {ticker_upper}")
        
        return result
        
    except ValueError as e:
        logger.error(f"Invalid input for {ticker}: {e}")
        raise HTTPException(status_code=400, detail=str(e))
        
    except Exception as e:
        logger.error(f"Error fetching news and social data for {ticker}: {e}")
        raise HTTPException(
            status_code=500,
            detail=f"Failed to retrieve news and social data for {ticker}. Please try again later."
        )


@router.get("/{ticker}/news-only", response_model=Dict[str, Any])
async def get_ticker_news_only(
    ticker: str,
    days_back: int = Query(7, ge=1, le=30, description="Number of days to look back for articles (1-30)"),
    max_articles: int = Query(30, ge=1, le=100, description="Maximum number of news articles to return (1-100)")
):
    """
    Get only news articles for a ticker (faster endpoint without social media data)
    
    - **ticker**: Stock ticker symbol (e.g., AAPL, TSLA, QQQ)
    - **days_back**: Number of days to look back for articles (default: 7, max: 30) 
    - **max_articles**: Maximum number of news articles to return (default: 30, min: 1, max: 100)
    
    ## Performance
    - ⚡ Faster response time (no social media API calls)
    - ⚡ Optimized for high-frequency news monitoring
    - ⚡ Ideal for news-only sentiment analysis
    """
    
    try:
        ticker_upper = ticker.upper().strip()
        if not ticker_upper or len(ticker_upper) > 10:
            raise HTTPException(
                status_code=400, 
                detail=f"Invalid ticker format: {ticker}. Must be 1-10 characters."
            )
        
        logger.info(f"Fetching news-only data for {ticker_upper}")
        
        # Get data with social media disabled
        result = await news_social_service.get_ticker_news_and_social(
            ticker=ticker_upper,
            days_back=days_back,
            max_articles=max_articles,
            max_social_posts=0,
            include_social=False
        )
        
        # Return only news portion
        news_only_result = {
            "ticker": result["ticker"],
            "retrieved_at": result["retrieved_at"],
            "news": result["news"],
            "summary": {
                "total_articles": result["news"]["total_articles"],
                "time_range_days": days_back,
                "sources": result["news"]["sources"]
            }
        }
        
        logger.info(f"Successfully retrieved {result['news']['total_articles']} articles for {ticker_upper}")
        
        return news_only_result
        
    except ValueError as e:
        logger.error(f"Invalid input for {ticker}: {e}")
        raise HTTPException(status_code=400, detail=str(e))
        
    except Exception as e:
        logger.error(f"Error fetching news for {ticker}: {e}")
        raise HTTPException(
            status_code=500,
            detail=f"Failed to retrieve news for {ticker}. Please try again later."
        )


@router.get("/{ticker}/social-only", response_model=Dict[str, Any])
async def get_ticker_social_only(
    ticker: str,
    days_back: int = Query(7, ge=1, le=30, description="Number of days to look back for posts (1-30)"),
    max_social_posts: int = Query(20, ge=1, le=50, description="Maximum number of social media posts to return (1-50)")
):
    """
    Get only social media posts for a ticker
    
    - **ticker**: Stock ticker symbol (e.g., AAPL, TSLA, QQQ)
    - **days_back**: Number of days to look back for posts (default: 7, max: 30)
    - **max_social_posts**: Maximum number of social media posts to return (default: 20, min: 1, max: 50)
    
    ## Social Media Sources
    - Reddit: r/stocks, r/investing, r/SecurityAnalysis, r/StockMarket, r/ValueInvesting, r/financialindependence, r/wallstreetbets
    
    ## Use Cases
    - Retail investor sentiment monitoring
    - Social media trend analysis
    - Community discussion tracking
    """
    
    try:
        ticker_upper = ticker.upper().strip()
        if not ticker_upper or len(ticker_upper) > 10:
            raise HTTPException(
                status_code=400, 
                detail=f"Invalid ticker format: {ticker}. Must be 1-10 characters."
            )
        
        logger.info(f"Fetching social-only data for {ticker_upper}")
        
        # Get data with minimal news articles
        result = await news_social_service.get_ticker_news_and_social(
            ticker=ticker_upper,
            days_back=days_back,
            max_articles=0,  # Minimal news data
            max_social_posts=max_social_posts,
            include_social=True
        )
        
        # Return only social media portion
        social_only_result = {
            "ticker": result["ticker"],
            "retrieved_at": result["retrieved_at"],
            "social_media": result["social_media"],
            "summary": {
                "total_posts": result["social_media"]["total_posts"],
                "time_range_days": days_back,
                "platforms": result["social_media"]["platforms"]
            }
        }
        
        logger.info(f"Successfully retrieved {result['social_media']['total_posts']} social posts for {ticker_upper}")
        
        return social_only_result
        
    except ValueError as e:
        logger.error(f"Invalid input for {ticker}: {e}")
        raise HTTPException(status_code=400, detail=str(e))
        
    except Exception as e:
        logger.error(f"Error fetching social media data for {ticker}: {e}")
        raise HTTPException(
            status_code=500,
            detail=f"Failed to retrieve social media data for {ticker}. Please try again later."
        )