469 lines
15 KiB
Python
469 lines
15 KiB
Python
from flask import Blueprint, request, jsonify
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import pandas as pd
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import json
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from datetime import datetime
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bp = Blueprint('limitanalyse', __name__, url_prefix='/api/limit-analyse')
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@bp.route('/available-dates', methods=['GET'])
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def get_available_dates():
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"""获取可用日期列表"""
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try:
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# 模拟可用日期
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dates = [
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'2025-07-16',
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'2025-07-15',
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'2025-07-14',
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'2025-07-11',
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'2025-07-10'
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]
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return jsonify({
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'success': True,
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'data': dates
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})
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except Exception as e:
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print(f"Error getting available dates: {e}")
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return jsonify({'success': False, 'error': str(e)}), 500
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def load_stock_data(datestr):
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"""加载股票数据"""
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try:
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# 模拟股票数据
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data = []
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for i in range(100):
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data.append({
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'code': f'00000{i:03d}',
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'name': f'股票{i}',
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'price': 10.0 + i * 0.1,
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'change': (i % 10 - 5) * 0.5,
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'sector': f'板块{i % 5}',
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'limit_type': '涨停' if i % 10 == 0 else '正常',
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'volume': 1000000 + i * 50000,
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'amount': 10000000 + i * 500000
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})
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return pd.DataFrame(data)
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except Exception as e:
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print(f"Error loading stock data: {e}")
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return pd.DataFrame()
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@bp.route('/data', methods=['GET'])
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def get_analysis_data():
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"""获取分析数据"""
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try:
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date = request.args.get('date', '2025-07-16')
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# 加载数据
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df = load_stock_data(date)
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if df.empty:
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return jsonify({'success': False, 'error': '数据加载失败'}), 500
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# 统计信息
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total_stocks = len(df)
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limit_up_stocks = len(df[df['limit_type'] == '涨停'])
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limit_down_stocks = len(df[df['limit_type'] == '跌停'])
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# 板块统计
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sector_stats = df.groupby('sector').agg({
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'code': 'count',
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'change': 'mean',
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'volume': 'sum'
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}).reset_index()
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sector_data = []
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for _, row in sector_stats.iterrows():
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sector_data.append({
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'sector': row['sector'],
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'stock_count': int(row['code']),
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'avg_change': round(row['change'], 2),
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'total_volume': int(row['volume'])
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})
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return jsonify({
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'success': True,
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'data': {
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'date': date,
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'total_stocks': total_stocks,
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'limit_up_stocks': limit_up_stocks,
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'limit_down_stocks': limit_down_stocks,
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'sector_stats': sector_data
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}
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})
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except Exception as e:
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print(f"Error getting analysis data: {e}")
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return jsonify({'success': False, 'error': str(e)}), 500
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@bp.route('/sector-data', methods=['GET'])
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def get_sector_data():
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"""获取板块数据"""
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try:
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date = request.args.get('date', '2025-07-16')
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# 加载数据
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df = load_stock_data(date)
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if df.empty:
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return jsonify({'success': False, 'error': '数据加载失败'}), 500
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# 板块统计
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sector_stats = df.groupby('sector').agg({
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'code': 'count',
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'change': 'mean',
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'volume': 'sum',
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'amount': 'sum'
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}).reset_index()
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sector_data = []
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for _, row in sector_stats.iterrows():
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sector_data.append({
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'sector': row['sector'],
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'stock_count': int(row['code']),
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'avg_change': round(row['change'], 2),
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'total_volume': int(row['volume']),
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'total_amount': int(row['amount'])
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})
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return jsonify({
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'success': True,
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'data': sector_data
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})
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except Exception as e:
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print(f"Error getting sector data: {e}")
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return jsonify({'success': False, 'error': str(e)}), 500
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@bp.route('/word-cloud', methods=['GET'])
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def get_word_cloud_data():
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"""获取词云数据"""
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try:
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date = request.args.get('date', '2025-07-16')
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# 模拟词云数据
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word_data = [
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{'word': '科技', 'value': 100},
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{'word': '新能源', 'value': 85},
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{'word': '医药', 'value': 70},
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{'word': '消费', 'value': 65},
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{'word': '金融', 'value': 50},
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{'word': '地产', 'value': 45},
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{'word': '制造', 'value': 40},
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{'word': '农业', 'value': 35},
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{'word': '传媒', 'value': 30},
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{'word': '环保', 'value': 25}
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]
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return jsonify({
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'success': True,
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'data': word_data
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})
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except Exception as e:
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print(f"Error getting word cloud data: {e}")
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return jsonify({'success': False, 'error': str(e)}), 500
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@bp.route('/chart-data', methods=['GET'])
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def get_chart_data():
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"""获取图表数据"""
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try:
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date = request.args.get('date', '2025-07-16')
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# 模拟图表数据
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chart_data = {
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'limit_up_distribution': [
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{'sector': '科技', 'count': 15},
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{'sector': '新能源', 'count': 12},
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{'sector': '医药', 'count': 10},
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{'sector': '消费', 'count': 8},
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{'sector': '金融', 'count': 6}
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],
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'sector_performance': [
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{'sector': '科技', 'change': 2.5},
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{'sector': '新能源', 'change': 1.8},
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{'sector': '医药', 'change': 1.2},
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{'sector': '消费', 'change': 0.8},
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{'sector': '金融', 'change': 0.5}
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]
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}
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return jsonify({
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'success': True,
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'data': chart_data
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})
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except Exception as e:
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print(f"Error getting chart data: {e}")
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return jsonify({'success': False, 'error': str(e)}), 500
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@bp.route('/stock-details', methods=['GET'])
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def get_stock_details():
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"""获取股票详情"""
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try:
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code = request.args.get('code')
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date = request.args.get('date', '2025-07-16')
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if not code:
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return jsonify({'success': False, 'error': '请提供股票代码'}), 400
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# 模拟股票详情
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stock_detail = {
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'code': code,
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'name': f'股票{code}',
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'price': 15.50,
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'change': 2.5,
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'sector': '科技',
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'volume': 1500000,
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'amount': 23250000,
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'limit_type': '涨停',
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'turnover_rate': 3.2,
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'market_cap': 15500000000
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}
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return jsonify({
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'success': True,
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'data': stock_detail
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})
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except Exception as e:
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print(f"Error getting stock details: {e}")
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return jsonify({'success': False, 'error': str(e)}), 500
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@bp.route('/sector-analysis', methods=['GET'])
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def get_sector_analysis():
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"""获取板块分析"""
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try:
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sector = request.args.get('sector')
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date = request.args.get('date', '2025-07-16')
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if not sector:
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return jsonify({'success': False, 'error': '请提供板块名称'}), 400
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# 模拟板块分析数据
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sector_analysis = {
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'sector': sector,
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'stock_count': 25,
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'avg_change': 1.8,
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'limit_up_count': 8,
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'limit_down_count': 2,
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'total_volume': 50000000,
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'total_amount': 750000000,
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'top_stocks': [
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{'code': '000001', 'name': '股票A', 'change': 10.0},
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{'code': '000002', 'name': '股票B', 'change': 9.5},
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{'code': '000003', 'name': '股票C', 'change': 8.8}
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]
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}
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return jsonify({
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'success': True,
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'data': sector_analysis
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})
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except Exception as e:
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print(f"Error getting sector analysis: {e}")
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return jsonify({'success': False, 'error': str(e)}), 500
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@bp.route('/trend-analysis', methods=['GET'])
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def get_trend_analysis():
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"""获取趋势分析"""
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try:
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date = request.args.get('date', '2025-07-16')
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# 模拟趋势分析数据
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trend_data = {
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'limit_up_trend': [
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{'date': '2025-07-10', 'count': 45},
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{'date': '2025-07-11', 'count': 52},
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{'date': '2025-07-14', 'count': 48},
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{'date': '2025-07-15', 'count': 55},
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{'date': '2025-07-16', 'count': 51}
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],
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'sector_trend': [
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{'sector': '科技', 'trend': 'up'},
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{'sector': '新能源', 'trend': 'up'},
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{'sector': '医药', 'trend': 'stable'},
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{'sector': '消费', 'trend': 'down'},
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{'sector': '金融', 'trend': 'stable'}
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]
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}
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return jsonify({
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'success': True,
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'data': trend_data
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})
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except Exception as e:
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print(f"Error getting trend analysis: {e}")
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return jsonify({'success': False, 'error': str(e)}), 500
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@bp.route('/heat-map', methods=['GET'])
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def get_heat_map_data():
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"""获取热力图数据"""
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try:
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date = request.args.get('date', '2025-07-16')
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# 模拟热力图数据
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heat_map_data = []
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sectors = ['科技', '新能源', '医药', '消费', '金融', '地产', '制造', '农业']
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for i, sector in enumerate(sectors):
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for j in range(8):
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heat_map_data.append({
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'sector': sector,
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'metric': f'指标{j+1}',
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'value': (i + j) % 10 + 1
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})
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return jsonify({
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'success': True,
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'data': heat_map_data
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})
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except Exception as e:
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print(f"Error getting heat map data: {e}")
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return jsonify({'success': False, 'error': str(e)}), 500
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@bp.route('/correlation-analysis', methods=['GET'])
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def get_correlation_analysis():
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"""获取相关性分析"""
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try:
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date = request.args.get('date', '2025-07-16')
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# 模拟相关性分析数据
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correlation_data = {
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'sector_correlations': [
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{'sector1': '科技', 'sector2': '新能源', 'correlation': 0.85},
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{'sector1': '医药', 'sector2': '消费', 'correlation': 0.72},
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{'sector1': '金融', 'sector2': '地产', 'correlation': 0.68},
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{'sector1': '科技', 'sector2': '医药', 'correlation': 0.45},
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{'sector1': '新能源', 'sector2': '制造', 'correlation': 0.78}
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],
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'stock_correlations': [
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{'stock1': '000001', 'stock2': '000002', 'correlation': 0.92},
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{'stock1': '000003', 'stock2': '000004', 'correlation': 0.88},
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{'stock1': '000005', 'stock2': '000006', 'correlation': 0.76}
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]
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}
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return jsonify({
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'success': True,
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'data': correlation_data
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})
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except Exception as e:
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print(f"Error getting correlation analysis: {e}")
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return jsonify({'success': False, 'error': str(e)}), 500
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@bp.route('/export-data', methods=['POST'])
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def export_data():
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"""导出数据"""
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try:
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data = request.get_json()
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date = data.get('date', '2025-07-16')
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export_type = data.get('type', 'excel')
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# 模拟导出
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filename = f'limit_analyse_{date}.{export_type}'
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return jsonify({
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'success': True,
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'message': '数据导出成功',
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'data': {
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'filename': filename,
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'download_url': f'/downloads/{filename}'
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}
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})
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except Exception as e:
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print(f"Error exporting data: {e}")
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return jsonify({'success': False, 'error': str(e)}), 500
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@bp.route('/high-position-stocks', methods=['GET'])
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def get_high_position_stocks():
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"""获取高位股统计数据"""
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try:
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date = request.args.get('date', datetime.now().strftime('%Y%m%d'))
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# 模拟高位股数据 - 实际使用时需要连接真实的数据库
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# 根据用户提供的表结构，查询连续涨停天数较多的股票
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high_position_stocks = [
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{
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'stock_code': '000001',
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'stock_name': '平安银行',
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'price': 15.68,
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'increase_rate': 10.02,
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'limit_up_days': 5,
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'continuous_limit_up': 3,
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'industry': '银行',
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'turnover_rate': 3.45,
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'market_cap': 32000000000
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},
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{
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'stock_code': '000002',
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'stock_name': '万科A',
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'price': 18.92,
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'increase_rate': 9.98,
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'limit_up_days': 4,
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'continuous_limit_up': 2,
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'industry': '房地产',
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'turnover_rate': 5.67,
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'market_cap': 21000000000
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},
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{
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'stock_code': '600036',
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'stock_name': '招商银行',
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'price': 42.15,
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'increase_rate': 8.45,
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'limit_up_days': 6,
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'continuous_limit_up': 4,
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'industry': '银行',
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'turnover_rate': 2.89,
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'market_cap': 105000000000
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},
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{
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'stock_code': '000858',
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'stock_name': '五粮液',
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'price': 168.50,
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'increase_rate': 7.23,
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'limit_up_days': 3,
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'continuous_limit_up': 2,
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'industry': '白酒',
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'turnover_rate': 1.56,
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'market_cap': 650000000000
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},
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{
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'stock_code': '002415',
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'stock_name': '海康威视',
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'price': 35.68,
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'increase_rate': 6.89,
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'limit_up_days': 4,
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'continuous_limit_up': 3,
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'industry': '安防',
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'turnover_rate': 4.12,
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'market_cap': 33000000000
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}
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]
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# 统计信息
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total_count = len(high_position_stocks)
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avg_continuous_days = sum(stock['continuous_limit_up'] for stock in high_position_stocks) / total_count if total_count > 0 else 0
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# 按连续涨停天数排序
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high_position_stocks.sort(key=lambda x: x['continuous_limit_up'], reverse=True)
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return jsonify({
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'success': True,
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'data': {
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'stocks': high_position_stocks,
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'statistics': {
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'total_count': total_count,
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'avg_continuous_days': round(avg_continuous_days, 2),
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'max_continuous_days': max([stock['continuous_limit_up'] for stock in high_position_stocks], default=0),
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'industry_distribution': {}
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}
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}
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})
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except Exception as e:
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print(f"Error getting high position stocks: {e}")
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return jsonify({'success': False, 'error': str(e)}), 500 |