from flask import Blueprint, request, jsonify
import pandas as pd
import json
from datetime import datetime

bp = Blueprint('limitanalyse', __name__, url_prefix='/api/limit-analyse')

@bp.route('/available-dates', methods=['GET'])
def get_available_dates():
    """获取可用日期列表"""
    try:
        # 模拟可用日期
        dates = [
            '2025-07-16',
            '2025-07-15',
            '2025-07-14',
            '2025-07-11',
            '2025-07-10'
        ]
        
        return jsonify({
            'success': True,
            'data': dates
        })
    except Exception as e:
        print(f"Error getting available dates: {e}")
        return jsonify({'success': False, 'error': str(e)}), 500

def load_stock_data(datestr):
    """加载股票数据"""
    try:
        # 模拟股票数据
        data = []
        for i in range(100):
            data.append({
                'code': f'00000{i:03d}',
                'name': f'股票{i}',
                'price': 10.0 + i * 0.1,
                'change': (i % 10 - 5) * 0.5,
                'sector': f'板块{i % 5}',
                'limit_type': '涨停' if i % 10 == 0 else '正常',
                'volume': 1000000 + i * 50000,
                'amount': 10000000 + i * 500000
            })
        
        return pd.DataFrame(data)
    except Exception as e:
        print(f"Error loading stock data: {e}")
        return pd.DataFrame()

@bp.route('/data', methods=['GET'])
def get_analysis_data():
    """获取分析数据"""
    try:
        date = request.args.get('date', '2025-07-16')
        
        # 加载数据
        df = load_stock_data(date)
        if df.empty:
            return jsonify({'success': False, 'error': '数据加载失败'}), 500

        # 统计信息
        total_stocks = len(df)
        limit_up_stocks = len(df[df['limit_type'] == '涨停'])
        limit_down_stocks = len(df[df['limit_type'] == '跌停'])
        
        # 板块统计
        sector_stats = df.groupby('sector').agg({
            'code': 'count',
            'change': 'mean',
            'volume': 'sum'
        }).reset_index()
        
        sector_data = []
        for _, row in sector_stats.iterrows():
            sector_data.append({
                'sector': row['sector'],
                'stock_count': int(row['code']),
                'avg_change': round(row['change'], 2),
                'total_volume': int(row['volume'])
            })

        return jsonify({
            'success': True,
            'data': {
                'date': date,
                'total_stocks': total_stocks,
                'limit_up_stocks': limit_up_stocks,
                'limit_down_stocks': limit_down_stocks,
                'sector_stats': sector_data
            }
        })

    except Exception as e:
        print(f"Error getting analysis data: {e}")
        return jsonify({'success': False, 'error': str(e)}), 500

@bp.route('/sector-data', methods=['GET'])
def get_sector_data():
    """获取板块数据"""
    try:
        date = request.args.get('date', '2025-07-16')
        
        # 加载数据
        df = load_stock_data(date)
        if df.empty:
            return jsonify({'success': False, 'error': '数据加载失败'}), 500

        # 板块统计
        sector_stats = df.groupby('sector').agg({
            'code': 'count',
            'change': 'mean',
            'volume': 'sum',
            'amount': 'sum'
        }).reset_index()
        
        sector_data = []
        for _, row in sector_stats.iterrows():
            sector_data.append({
                'sector': row['sector'],
                'stock_count': int(row['code']),
                'avg_change': round(row['change'], 2),
                'total_volume': int(row['volume']),
                'total_amount': int(row['amount'])
            })

        return jsonify({
            'success': True,
            'data': sector_data
        })

    except Exception as e:
        print(f"Error getting sector data: {e}")
        return jsonify({'success': False, 'error': str(e)}), 500

@bp.route('/word-cloud', methods=['GET'])
def get_word_cloud_data():
    """获取词云数据"""
    try:
        date = request.args.get('date', '2025-07-16')
        
        # 模拟词云数据
        word_data = [
            {'word': '科技', 'value': 100},
            {'word': '新能源', 'value': 85},
            {'word': '医药', 'value': 70},
            {'word': '消费', 'value': 65},
            {'word': '金融', 'value': 50},
            {'word': '地产', 'value': 45},
            {'word': '制造', 'value': 40},
            {'word': '农业', 'value': 35},
            {'word': '传媒', 'value': 30},
            {'word': '环保', 'value': 25}
        ]

        return jsonify({
            'success': True,
            'data': word_data
        })

    except Exception as e:
        print(f"Error getting word cloud data: {e}")
        return jsonify({'success': False, 'error': str(e)}), 500

@bp.route('/chart-data', methods=['GET'])
def get_chart_data():
    """获取图表数据"""
    try:
        date = request.args.get('date', '2025-07-16')
        
        # 模拟图表数据
        chart_data = {
            'limit_up_distribution': [
                {'sector': '科技', 'count': 15},
                {'sector': '新能源', 'count': 12},
                {'sector': '医药', 'count': 10},
                {'sector': '消费', 'count': 8},
                {'sector': '金融', 'count': 6}
            ],
            'sector_performance': [
                {'sector': '科技', 'change': 2.5},
                {'sector': '新能源', 'change': 1.8},
                {'sector': '医药', 'change': 1.2},
                {'sector': '消费', 'change': 0.8},
                {'sector': '金融', 'change': 0.5}
            ]
        }

        return jsonify({
            'success': True,
            'data': chart_data
        })

    except Exception as e:
        print(f"Error getting chart data: {e}")
        return jsonify({'success': False, 'error': str(e)}), 500

@bp.route('/stock-details', methods=['GET'])
def get_stock_details():
    """获取股票详情"""
    try:
        code = request.args.get('code')
        date = request.args.get('date', '2025-07-16')
        
        if not code:
            return jsonify({'success': False, 'error': '请提供股票代码'}), 400

        # 模拟股票详情
        stock_detail = {
            'code': code,
            'name': f'股票{code}',
            'price': 15.50,
            'change': 2.5,
            'sector': '科技',
            'volume': 1500000,
            'amount': 23250000,
            'limit_type': '涨停',
            'turnover_rate': 3.2,
            'market_cap': 15500000000
        }

        return jsonify({
            'success': True,
            'data': stock_detail
        })

    except Exception as e:
        print(f"Error getting stock details: {e}")
        return jsonify({'success': False, 'error': str(e)}), 500

@bp.route('/sector-analysis', methods=['GET'])
def get_sector_analysis():
    """获取板块分析"""
    try:
        sector = request.args.get('sector')
        date = request.args.get('date', '2025-07-16')
        
        if not sector:
            return jsonify({'success': False, 'error': '请提供板块名称'}), 400

        # 模拟板块分析数据
        sector_analysis = {
            'sector': sector,
            'stock_count': 25,
            'avg_change': 1.8,
            'limit_up_count': 8,
            'limit_down_count': 2,
            'total_volume': 50000000,
            'total_amount': 750000000,
            'top_stocks': [
                {'code': '000001', 'name': '股票A', 'change': 10.0},
                {'code': '000002', 'name': '股票B', 'change': 9.5},
                {'code': '000003', 'name': '股票C', 'change': 8.8}
            ]
        }

        return jsonify({
            'success': True,
            'data': sector_analysis
        })

    except Exception as e:
        print(f"Error getting sector analysis: {e}")
        return jsonify({'success': False, 'error': str(e)}), 500

@bp.route('/trend-analysis', methods=['GET'])
def get_trend_analysis():
    """获取趋势分析"""
    try:
        date = request.args.get('date', '2025-07-16')
        
        # 模拟趋势分析数据
        trend_data = {
            'limit_up_trend': [
                {'date': '2025-07-10', 'count': 45},
                {'date': '2025-07-11', 'count': 52},
                {'date': '2025-07-14', 'count': 48},
                {'date': '2025-07-15', 'count': 55},
                {'date': '2025-07-16', 'count': 51}
            ],
            'sector_trend': [
                {'sector': '科技', 'trend': 'up'},
                {'sector': '新能源', 'trend': 'up'},
                {'sector': '医药', 'trend': 'stable'},
                {'sector': '消费', 'trend': 'down'},
                {'sector': '金融', 'trend': 'stable'}
            ]
        }

        return jsonify({
            'success': True,
            'data': trend_data
        })

    except Exception as e:
        print(f"Error getting trend analysis: {e}")
        return jsonify({'success': False, 'error': str(e)}), 500

@bp.route('/heat-map', methods=['GET'])
def get_heat_map_data():
    """获取热力图数据"""
    try:
        date = request.args.get('date', '2025-07-16')
        
        # 模拟热力图数据
        heat_map_data = []
        sectors = ['科技', '新能源', '医药', '消费', '金融', '地产', '制造', '农业']
        
        for i, sector in enumerate(sectors):
            for j in range(8):
                heat_map_data.append({
                    'sector': sector,
                    'metric': f'指标{j+1}',
                    'value': (i + j) % 10 + 1
                })

        return jsonify({
            'success': True,
            'data': heat_map_data
        })

    except Exception as e:
        print(f"Error getting heat map data: {e}")
        return jsonify({'success': False, 'error': str(e)}), 500

@bp.route('/correlation-analysis', methods=['GET'])
def get_correlation_analysis():
    """获取相关性分析"""
    try:
        date = request.args.get('date', '2025-07-16')
        
        # 模拟相关性分析数据
        correlation_data = {
            'sector_correlations': [
                {'sector1': '科技', 'sector2': '新能源', 'correlation': 0.85},
                {'sector1': '医药', 'sector2': '消费', 'correlation': 0.72},
                {'sector1': '金融', 'sector2': '地产', 'correlation': 0.68},
                {'sector1': '科技', 'sector2': '医药', 'correlation': 0.45},
                {'sector1': '新能源', 'sector2': '制造', 'correlation': 0.78}
            ],
            'stock_correlations': [
                {'stock1': '000001', 'stock2': '000002', 'correlation': 0.92},
                {'stock1': '000003', 'stock2': '000004', 'correlation': 0.88},
                {'stock1': '000005', 'stock2': '000006', 'correlation': 0.76}
            ]
        }

        return jsonify({
            'success': True,
            'data': correlation_data
        })

    except Exception as e:
        print(f"Error getting correlation analysis: {e}")
        return jsonify({'success': False, 'error': str(e)}), 500

@bp.route('/export-data', methods=['POST'])
def export_data():
    """导出数据"""
    try:
        data = request.get_json()
        date = data.get('date', '2025-07-16')
        export_type = data.get('type', 'excel')
        
        # 模拟导出
        filename = f'limit_analyse_{date}.{export_type}'
        
        return jsonify({
            'success': True,
            'message': '数据导出成功',
            'data': {
                'filename': filename,
                'download_url': f'/downloads/{filename}'
            }
        })

    except Exception as e:
        print(f"Error exporting data: {e}")
        return jsonify({'success': False, 'error': str(e)}), 500 

@bp.route('/high-position-stocks', methods=['GET'])
def get_high_position_stocks():
    """获取高位股统计数据"""
    try:
        date = request.args.get('date', datetime.now().strftime('%Y%m%d'))
        
        # 模拟高位股数据 - 实际使用时需要连接真实的数据库
        # 根据用户提供的表结构，查询连续涨停天数较多的股票
        high_position_stocks = [
            {
                'stock_code': '000001',
                'stock_name': '平安银行',
                'price': 15.68,
                'increase_rate': 10.02,
                'limit_up_days': 5,
                'continuous_limit_up': 3,
                'industry': '银行',
                'turnover_rate': 3.45,
                'market_cap': 32000000000
            },
            {
                'stock_code': '000002',
                'stock_name': '万科A',
                'price': 18.92,
                'increase_rate': 9.98,
                'limit_up_days': 4,
                'continuous_limit_up': 2,
                'industry': '房地产',
                'turnover_rate': 5.67,
                'market_cap': 21000000000
            },
            {
                'stock_code': '600036',
                'stock_name': '招商银行',
                'price': 42.15,
                'increase_rate': 8.45,
                'limit_up_days': 6,
                'continuous_limit_up': 4,
                'industry': '银行',
                'turnover_rate': 2.89,
                'market_cap': 105000000000
            },
            {
                'stock_code': '000858',
                'stock_name': '五粮液',
                'price': 168.50,
                'increase_rate': 7.23,
                'limit_up_days': 3,
                'continuous_limit_up': 2,
                'industry': '白酒',
                'turnover_rate': 1.56,
                'market_cap': 650000000000
            },
            {
                'stock_code': '002415',
                'stock_name': '海康威视',
                'price': 35.68,
                'increase_rate': 6.89,
                'limit_up_days': 4,
                'continuous_limit_up': 3,
                'industry': '安防',
                'turnover_rate': 4.12,
                'market_cap': 33000000000
            }
        ]
        
        # 统计信息
        total_count = len(high_position_stocks)
        avg_continuous_days = sum(stock['continuous_limit_up'] for stock in high_position_stocks) / total_count if total_count > 0 else 0
        
        # 按连续涨停天数排序
        high_position_stocks.sort(key=lambda x: x['continuous_limit_up'], reverse=True)

        return jsonify({
            'success': True,
            'data': {
                'stocks': high_position_stocks,
                'statistics': {
                    'total_count': total_count,
                    'avg_continuous_days': round(avg_continuous_days, 2),
                    'max_continuous_days': max([stock['continuous_limit_up'] for stock in high_position_stocks], default=0),
                    'industry_distribution': {}
                }
            }
        })

    except Exception as e:
        print(f"Error getting high position stocks: {e}")
        return jsonify({'success': False, 'error': str(e)}), 500