update pay function
This commit is contained in:
315
app_vx.py
315
app_vx.py
@@ -2497,272 +2497,12 @@ def api_get_events():
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paginated = query.paginate(page=page, per_page=per_page, error_out=False)
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# ==================== 批量获取股票行情数据（优化版） ====================
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# 1. 收集当前页所有事件的ID
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event_ids = [event.id for event in paginated.items]
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# 2. 获取所有相关股票
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all_related_stocks = {}
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if event_ids:
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related_stocks = RelatedStock.query.filter(
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RelatedStock.event_id.in_(event_ids)
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).all()
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# 按事件ID分组
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for stock in related_stocks:
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if stock.event_id not in all_related_stocks:
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all_related_stocks[stock.event_id] = []
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all_related_stocks[stock.event_id].append(stock)
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# 3. 收集所有股票代码
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all_stock_codes = []
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stock_code_mapping = {} # 清理后的代码 -> 原始代码的映射
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for stocks in all_related_stocks.values():
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for stock in stocks:
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clean_code = stock.stock_code.replace('.SH', '').replace('.SZ', '').replace('.BJ', '')
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all_stock_codes.append(clean_code)
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stock_code_mapping[clean_code] = stock.stock_code
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# 去重
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all_stock_codes = list(set(all_stock_codes))
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# 4. 批量查询最近7个交易日的数据（用于计算日涨跌和周涨跌）
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stock_price_data = {}
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if all_stock_codes:
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# 构建SQL查询 - 获取最近7个交易日的数据
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codes_str = "'" + "', '".join(all_stock_codes) + "'"
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# 获取最近7个交易日的数据
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recent_trades_sql = f"""
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SELECT
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SECCODE,
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SECNAME,
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F007N as close_price,
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F010N as daily_change,
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TRADEDATE,
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ROW_NUMBER() OVER (PARTITION BY SECCODE ORDER BY TRADEDATE DESC) as rn
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FROM ea_trade
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WHERE SECCODE IN ({codes_str})
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AND F007N IS NOT NULL
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AND TRADEDATE >= DATE_SUB(CURDATE(), INTERVAL 10 DAY)
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ORDER BY SECCODE, TRADEDATE DESC
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"""
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result = db.session.execute(text(recent_trades_sql))
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# 整理数据
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for row in result.fetchall():
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sec_code = row[0]
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if sec_code not in stock_price_data:
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stock_price_data[sec_code] = {
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'stock_name': row[1],
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'prices': []
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}
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stock_price_data[sec_code]['prices'].append({
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'close_price': float(row[2]) if row[2] else 0,
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'daily_change': float(row[3]) if row[3] else 0,
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'trade_date': row[4],
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'rank': row[5]
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})
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# 5. 计算日涨跌和周涨跌
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stock_changes = {}
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for sec_code, data in stock_price_data.items():
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prices = data['prices']
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# 最新日涨跌（第1条记录）
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daily_change = 0
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if prices and prices[0]['rank'] == 1:
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daily_change = prices[0]['daily_change']
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# 计算周涨跌（最新价 vs 5个交易日前的价格）
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week_change = 0
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if len(prices) >= 2:
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latest_price = prices[0]['close_price']
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# 找到第5个交易日的数据（如果有）
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week_ago_price = None
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for price_data in prices:
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if price_data['rank'] >= 5:
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week_ago_price = price_data['close_price']
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break
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# 如果没有第5天的数据，使用最早的数据
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if week_ago_price is None and len(prices) > 1:
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week_ago_price = prices[-1]['close_price']
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if week_ago_price and week_ago_price > 0:
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week_change = (latest_price - week_ago_price) / week_ago_price * 100
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stock_changes[sec_code] = {
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'stock_name': data['stock_name'],
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'daily_change': daily_change,
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'week_change': week_change
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}
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# ==================== 获取整体统计信息（应用所有筛选条件） ====================
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overall_distribution = {
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'limit_down': 0,
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'down_over_5': 0,
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'down_5_to_1': 0,
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'down_within_1': 0,
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'flat': 0,
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'up_within_1': 0,
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'up_1_to_5': 0,
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'up_over_5': 0,
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'limit_up': 0
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}
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# 使用当前筛选条件的query，但不应用分页限制，获取所有符合条件的事件
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# 这样统计数据会跟随用户的筛选条件变化
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all_filtered_events = query.limit(1000).all() # 限制最多1000个事件，避免查询过慢
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week_event_ids = [e.id for e in all_filtered_events]
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if week_event_ids:
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# 获取这些事件的所有关联股票
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week_related_stocks = RelatedStock.query.filter(
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RelatedStock.event_id.in_(week_event_ids)
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).all()
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# 按事件ID分组
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week_stocks_by_event = {}
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for stock in week_related_stocks:
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if stock.event_id not in week_stocks_by_event:
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week_stocks_by_event[stock.event_id] = []
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week_stocks_by_event[stock.event_id].append(stock)
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# 收集所有股票代码（用于批量查询行情）
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week_stock_codes = []
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week_code_mapping = {}
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for stocks in week_stocks_by_event.values():
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for stock in stocks:
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clean_code = stock.stock_code.replace('.SH', '').replace('.SZ', '').replace('.BJ', '')
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week_stock_codes.append(clean_code)
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week_code_mapping[clean_code] = stock.stock_code
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week_stock_codes = list(set(week_stock_codes))
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# 批量查询这些股票的最新行情数据
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week_stock_changes = {}
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if week_stock_codes:
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codes_str = "'" + "', '".join(week_stock_codes) + "'"
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recent_trades_sql = f"""
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SELECT
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SECCODE,
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SECNAME,
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F010N as daily_change,
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ROW_NUMBER() OVER (PARTITION BY SECCODE ORDER BY TRADEDATE DESC) as rn
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FROM ea_trade
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WHERE SECCODE IN ({codes_str})
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AND F010N IS NOT NULL
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AND TRADEDATE >= DATE_SUB(CURDATE(), INTERVAL 3 DAY)
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ORDER BY SECCODE, TRADEDATE DESC
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"""
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result = db.session.execute(text(recent_trades_sql))
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for row in result.fetchall():
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sec_code = row[0]
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if row[3] == 1: # 只取最新的数据（rn=1）
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week_stock_changes[sec_code] = {
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'stock_name': row[1],
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'daily_change': float(row[2]) if row[2] else 0
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}
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# 按事件统计平均涨跌幅分布
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event_avg_changes = {}
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for event in all_filtered_events:
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event_stocks = week_stocks_by_event.get(event.id, [])
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if not event_stocks:
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continue
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total_change = 0
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valid_count = 0
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for stock in event_stocks:
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clean_code = stock.stock_code.replace('.SH', '').replace('.SZ', '').replace('.BJ', '')
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if clean_code in week_stock_changes:
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daily_change = week_stock_changes[clean_code]['daily_change']
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total_change += daily_change
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valid_count += 1
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if valid_count > 0:
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avg_change = total_change / valid_count
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event_avg_changes[event.id] = avg_change
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# 统计事件平均涨跌幅的分布
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for event_id, avg_change in event_avg_changes.items():
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# 对于事件平均涨幅，不使用涨跌停分类，使用通用分类
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if avg_change <= -10:
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overall_distribution['limit_down'] += 1
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elif avg_change >= 10:
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overall_distribution['limit_up'] += 1
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elif avg_change > 5:
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overall_distribution['up_over_5'] += 1
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elif avg_change > 1:
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overall_distribution['up_1_to_5'] += 1
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elif avg_change > 0.1:
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overall_distribution['up_within_1'] += 1
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elif avg_change >= -0.1:
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overall_distribution['flat'] += 1
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elif avg_change > -1:
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overall_distribution['down_within_1'] += 1
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elif avg_change > -5:
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overall_distribution['down_5_to_1'] += 1
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else:
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overall_distribution['down_over_5'] += 1
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# ==================== 构建响应数据 ====================
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events_data = []
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for event in paginated.items:
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event_stocks = all_related_stocks.get(event.id, [])
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stocks_data = []
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total_daily_change = 0
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max_daily_change = -999
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total_week_change = 0
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max_week_change = -999
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valid_stocks_count = 0
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# 处理每个股票的数据
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for stock in event_stocks:
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clean_code = stock.stock_code.replace('.SH', '').replace('.SZ', '').replace('.BJ', '')
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stock_info = stock_changes.get(clean_code, {})
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daily_change = stock_info.get('daily_change', 0)
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week_change = stock_info.get('week_change', 0)
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if stock_info:
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total_daily_change += daily_change
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max_daily_change = max(max_daily_change, daily_change)
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total_week_change += week_change
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max_week_change = max(max_week_change, week_change)
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valid_stocks_count += 1
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stocks_data.append({
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"stock_code": stock.stock_code,
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"stock_name": stock.stock_name,
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"sector": stock.sector,
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"week_change": round(week_change, 2),
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"daily_change": round(daily_change, 2)
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})
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avg_daily_change = total_daily_change / valid_stocks_count if valid_stocks_count > 0 else 0
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avg_week_change = total_week_change / valid_stocks_count if valid_stocks_count > 0 else 0
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if max_daily_change == -999:
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max_daily_change = 0
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if max_week_change == -999:
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max_week_change = 0
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# 构建事件数据
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# 构建事件数据（简化版，只包含基本信息和涨跌幅）
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event_dict = {
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'id': event.id,
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'title': event.title,
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@@ -2774,34 +2514,26 @@ def api_get_events():
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'updated_at': event.updated_at.isoformat() if event.updated_at else None,
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'start_time': event.start_time.isoformat() if event.start_time else None,
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'end_time': event.end_time.isoformat() if event.end_time else None,
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'related_stocks': stocks_data,
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'stocks_stats': {
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'stocks_count': len(event_stocks),
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'valid_stocks_count': valid_stocks_count,
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# 周涨跌统计
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'avg_week_change': round(avg_week_change, 2),
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'max_week_change': round(max_week_change, 2),
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# 日涨跌统计
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'avg_daily_change': round(avg_daily_change, 2),
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'max_daily_change': round(max_daily_change, 2)
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}
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# 涨跌幅数据（从数据库字段直接获取）
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'related_avg_chg': event.related_avg_chg, # 平均涨跌幅
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'related_max_chg': event.related_max_chg, # 最大涨跌幅
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'related_week_chg': event.related_week_chg, # 周涨跌幅
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# 关联股票数量（固定值）
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'stocks_count': 10
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}
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# 统计信息
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# 统计信息（可选）
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if include_stats:
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event_dict.update({
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'hot_score': event.hot_score,
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'view_count': event.view_count,
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'post_count': event.post_count,
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'follower_count': event.follower_count,
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'related_avg_chg': event.related_avg_chg,
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'related_max_chg': event.related_max_chg,
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'related_week_chg': event.related_week_chg,
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'invest_score': event.invest_score,
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'trending_score': event.trending_score,
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})
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# 创建者信息
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# 创建者信息（可选）
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if include_creator:
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event_dict['creator'] = {
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'id': event.creator.id if event.creator else None,
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@@ -2815,25 +2547,6 @@ def api_get_events():
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event_dict['keywords'] = event.keywords if isinstance(event.keywords, list) else []
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event_dict['related_industries'] = event.related_industries
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# 包含统计信息
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if include_stats:
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event_dict['stats'] = {
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'related_stocks_count': len(event_stocks),
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'historical_events_count': 0, # 需要额外查询
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'related_data_count': 0, # 需要额外查询
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'related_concepts_count': 0 # 需要额外查询
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}
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# 包含关联数据
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if include_related_data:
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event_dict['related_stocks'] = [{
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'id': stock.id,
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'stock_code': stock.stock_code,
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'stock_name': stock.stock_name,
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'sector': stock.sector,
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'correlation': float(stock.correlation) if stock.correlation else 0
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} for stock in event_stocks[:5]] # 限制返回5个
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events_data.append(event_dict)
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# ==================== 构建筛选信息 ====================
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@@ -2860,7 +2573,7 @@ def api_get_events():
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applied_filters['search_query'] = search_query
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applied_filters['search_type'] = search_type
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# ==================== 返回结果（保持完全兼容） ====================
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# ==================== 返回结果（简化版） ====================
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return jsonify({
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'success': True,
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@@ -2884,14 +2597,6 @@ def api_get_events():
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'sort': sort_by,
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'order': order
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}
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},
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# 整体股票涨跌幅分布统计
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'overall_stats': {
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'total_stocks': len(all_stocks_for_stats) if 'all_stocks_for_stats' in locals() else 0,
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'change_distribution': overall_distribution,
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'change_distribution_percentages': {
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k: v for k, v in overall_distribution.items()
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}
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}
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}
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})
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