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app/routes/limitanalyse.py Normal file
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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