分拆了index
This commit is contained in:
jackyu66git
+1
-138
@@ -2128,144 +2128,7 @@ def debug_replay_structure():
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except Exception as e:
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return jsonify({'error': str(e)})
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@app.route('/api/filter_stocks', methods=['POST'])
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def filter_stocks():
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"""筛选满足条件的A股股票"""
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try:
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data = request.get_json()
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start_time = data.get('start_time')
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end_time = data.get('end_time')
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timeframe = data.get('timeframe', '1d')
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fx_strength_threshold = data.get('fx_strength_threshold', 1.0)
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if not start_time or not end_time:
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return jsonify({'error': '开始时间和结束时间不能为空'})
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# 获取所有A股股票列表，如果失败则使用热门股票作为备用
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stock_list = []
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data_source = ""
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try:
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stock_list = china_stock.get_stock_list()
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if stock_list and len(stock_list) > 0:
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data_source = "完整股票列表"
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else:
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raise Exception("获取到的股票列表为空")
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except Exception as e:
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try:
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popular_stocks = china_stock.get_popular_stocks()
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stock_list = [{'symbol': stock['symbol'], 'name': stock['name']} for stock in popular_stocks]
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data_source = "热门股票列表"
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except Exception as e2:
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# 检查是否是网络连接问题
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if "timeout" in str(e).lower() or "connection" in str(e).lower() or "network" in str(e).lower():
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return jsonify({
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'error': '网络连接超时，无法获取股票数据。请检查网络连接后重试。',
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'error_type': 'network_error',
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'suggestion': '请确保网络连接正常，或稍后重试。'
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})
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else:
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return jsonify({'error': f'无法获取股票列表: {str(e)}'})
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if not stock_list:
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return jsonify({
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'error': '无法获取股票列表，请检查网络连接后重试',
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'error_type': 'network_error',
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'suggestion': '请确保网络连接正常，或稍后重试。'
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})
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results = []
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processed_count = 0
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total_count = len(stock_list)
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failed_count = 0
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for stock in stock_list:
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try:
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symbol = stock['symbol']
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name = stock['name']
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processed_count += 1
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# 获取股票K线数据
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df = get_a_stock_kl_data(symbol, timeframe, start_time=start_time, end_time=end_time)
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if df is None or len(df) < 3:
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failed_count += 1
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# 如果连续失败太多，可能是网络问题
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if failed_count > 10 and len(results) == 0:
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return jsonify({
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'error': '网络连接不稳定，无法获取股票数据。请检查网络连接后重试。',
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'error_type': 'network_error',
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'processed_count': processed_count,
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'failed_count': failed_count
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})
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continue
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# 进行缠论分析
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analysis_result = analyze_chan(df, symbol, timeframe)
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if not analysis_result or 'klc_fx_info' not in analysis_result:
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continue
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klc_fx_info = analysis_result['klc_fx_info']
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# 检查最近2个KLC是否有满足条件的分型
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recent_klcs = klc_fx_info[-2:] if len(klc_fx_info) >= 2 else klc_fx_info
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for klc_info in recent_klcs:
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fx_strength = klc_info.get('fx_strength', 0)
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fx_type = klc_info.get('fx_type', 'UNKNOWN')
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# 检查是否满足条件：分型强度>=阈值 且 分型类型不为UNKNOWN
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if fx_strength >= fx_strength_threshold and fx_type != 'UNKNOWN':
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# 获取当前价格（最新收盘价）
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current_price = df['close'].iloc[-1] if len(df) > 0 else None
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fx_price = klc_info.get('price', 0)
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# 计算涨跌幅
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change_percent = 0
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if current_price and fx_price and fx_price > 0:
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change_percent = ((current_price - fx_price) / fx_price) * 100
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# 格式化分型类型显示
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fx_type_display = format_fx_type(fx_type)
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results.append({
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'symbol': symbol,
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'name': name,
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'fx_time': klc_info.get('time', ''),
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'fx_type': fx_type_display,
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'fx_strength': fx_strength,
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'fx_price': fx_price,
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'current_price': current_price,
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'change_percent': change_percent
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})
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break # 找到一个满足条件的就跳出循环
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except Exception as e:
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failed_count += 1
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continue
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# 按分型强度降序排列
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results.sort(key=lambda x: x['fx_strength'], reverse=True)
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return jsonify({
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'results': results,
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'total_processed': processed_count,
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'total_found': len(results),
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'failed_count': failed_count,
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'data_source': data_source,
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'message': f'使用{data_source}进行筛选，共处理{processed_count}只股票，找到{len(results)}只满足条件的股票'
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})
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except Exception as e:
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# 检查是否是网络连接问题
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if "timeout" in str(e).lower() or "connection" in str(e).lower() or "network" in str(e).lower():
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return jsonify({
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'error': '网络连接超时，请检查网络连接后重试。',
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'error_type': 'network_error',
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'suggestion': '请确保网络连接正常，或稍后重试。'
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})
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else:
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return jsonify({'error': str(e)})
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# 已移除：/api/filter_stocks 路由
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def get_uncompleted_seg_list(seg_list, client_tz):
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"""获取未完成线段列表，正确处理倒数第二个和最后一个未完成线段"""
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@@ -0,0 +1,69 @@
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// Namespace setup
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window.App = window.App || {};
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window.App.Charts = (function() {
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// 依赖 Indicators
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const Indicators = (window.App && window.App.Indicators) || {};
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function addMovingAveragesToChart(candleData) {
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if (!window.tvWidget || !tvWidget.mainChart || !candleData || candleData.length === 0) return;
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if (!window.movingAverages) return;
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if (!tvWidget.series) tvWidget.series = {};
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if (tvWidget.series.maSeries && tvWidget.series.maSeries.length > 0) {
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tvWidget.series.maSeries.forEach(series => {
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try { tvWidget.mainChart.removeSeries(series); } catch(e) {}
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});
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}
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tvWidget.series.maSeries = [];
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window.movingAverages.forEach(maConfig => {
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if (!maConfig.visible) return;
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try {
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const maData = Indicators.calculateMA(candleData, maConfig.type, maConfig.length, maConfig.source);
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const smoothedData = maConfig.smoothType !== 'none' ? (window.applySmoothToMA ? window.applySmoothToMA(maData, maConfig.smoothType, maConfig.smoothLength) : maData) : maData;
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const maSeries = tvWidget.mainChart.addLineSeries({
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color: maConfig.color,
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lineWidth: maConfig.lineWidth || 2,
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lineStyle: maConfig.lineStyle || 0,
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title: `${maConfig.type}(${maConfig.length})`,
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lastValueVisible: false,
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priceLineVisible: false,
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crosshairMarkerVisible: true,
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});
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maSeries.setData(smoothedData);
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maConfig.data = smoothedData;
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tvWidget.series.maSeries.push(maSeries);
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} catch(e) {}
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});
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}
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function addBollingerBandsToChart(candleData) {
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if (!window.tvWidget || !tvWidget.mainChart || !candleData || candleData.length === 0) return;
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if (!window.bollingerBands) return;
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if (!tvWidget.series) tvWidget.series = {};
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if (tvWidget.series.bbSeries && tvWidget.series.bbSeries.length > 0) {
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tvWidget.series.bbSeries.forEach(series => { try { tvWidget.mainChart.removeSeries(series); } catch(e) {} });
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}
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tvWidget.series.bbSeries = [];
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window.bollingerBands.forEach(bbConfig => {
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if (!bbConfig.visible) return;
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try {
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const bbData = Indicators.calculateBB(candleData, bbConfig.length, bbConfig.upperMultiplier, bbConfig.lowerMultiplier, bbConfig.source);
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const upperSeries = tvWidget.mainChart.addLineSeries({ color: bbConfig.upperColor, lineWidth: bbConfig.lineWidth || 2, lineStyle: bbConfig.lineStyle || 0, lastValueVisible: false, priceLineVisible: false, crosshairMarkerVisible: true });
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const middleSeries = tvWidget.mainChart.addLineSeries({ color: bbConfig.middleColor, lineWidth: bbConfig.lineWidth || 2, lineStyle: bbConfig.lineStyle || 0, lastValueVisible: false, priceLineVisible: false, crosshairMarkerVisible: true });
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const lowerSeries = tvWidget.mainChart.addLineSeries({ color: bbConfig.lowerColor, lineWidth: bbConfig.lineWidth || 2, lineStyle: bbConfig.lineStyle || 0, lastValueVisible: false, priceLineVisible: false, crosshairMarkerVisible: true });
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upperSeries.setData(bbData.map(item => ({ time: item.time, value: item.upper })));
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middleSeries.setData(bbData.map(item => ({ time: item.time, value: item.middle })));
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lowerSeries.setData(bbData.map(item => ({ time: item.time, value: item.lower })));
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bbConfig.data = bbData;
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tvWidget.series.bbSeries.push(upperSeries, middleSeries, lowerSeries);
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} catch(e) {}
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});
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}
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return { addMovingAveragesToChart, addBollingerBandsToChart };
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})();
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@@ -0,0 +1,99 @@
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// Namespace setup
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window.App = window.App || {};
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window.App.Indicators = (function() {
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function computeEMA(arr, period) {
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const k = 2 / (period + 1);
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const out = [];
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let emaPrev = null;
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for (let i = 0; i < arr.length; i++) {
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const price = arr[i];
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if (price == null || !isFinite(price)) { out.push(null); continue; }
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if (emaPrev == null) {
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const start = Math.max(0, i - period + 1);
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const windowArr = arr.slice(start, i + 1).filter(v => v != null && isFinite(v));
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const sma = windowArr.length ? windowArr.reduce((a,b)=>a+b,0)/windowArr.length : price;
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emaPrev = sma;
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}
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const ema = price * k + emaPrev * (1 - k);
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out.push(ema);
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emaPrev = ema;
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}
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return out;
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}
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function calculateMA(data, type, length, source) {
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if (!data || data.length < length) return [];
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const sourceData = data.map(candle => {
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switch(source) {
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case 'open': return candle.open;
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case 'high': return candle.high;
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case 'low': return candle.low;
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case 'close': return candle.close;
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case 'hl2': return (candle.high + candle.low) / 2;
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case 'hlc3': return (candle.high + candle.low + candle.close) / 3;
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case 'ohlc4': return (candle.open + candle.high + candle.low + candle.close) / 4;
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default: return candle.close;
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}
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});
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const result = [];
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for (let i = length - 1; i < sourceData.length; i++) {
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let value;
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switch(type) {
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case 'SMA':
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value = sourceData.slice(i - length + 1, i + 1).reduce((sum, v) => sum + v, 0) / length;
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break;
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case 'EMA':
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const multiplier = 2 / (length + 1);
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if (result.length === 0) {
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value = sourceData.slice(i - length + 1, i + 1).reduce((sum, v) => sum + v, 0) / length;
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} else {
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value = sourceData[i] * multiplier + result[result.length - 1].value * (1 - multiplier);
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}
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break;
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case 'WMA':
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let weightSum = 0;
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let valueSum = 0;
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for (let j = 0; j < length; j++) {
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const weight = j + 1;
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weightSum += weight;
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valueSum += sourceData[i - length + 1 + j] * weight;
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}
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value = valueSum / weightSum;
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break;
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default:
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value = sourceData[i];
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}
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result.push({ time: data[i].time, value });
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}
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return result;
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}
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function calculateBB(data, length, upperMultiplier, lowerMultiplier, source) {
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if (!data || data.length < length) return [];
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const sourceData = data.map(candle => {
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switch(source) {
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case 'open': return candle.open;
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case 'high': return candle.high;
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case 'low': return candle.low;
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case 'close': return candle.close;
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case 'hl2': return (candle.high + candle.low) / 2;
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case 'hlc3': return (candle.high + candle.low + candle.close) / 3;
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case 'ohlc4': return (candle.open + candle.high + candle.low + candle.close) / 4;
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default: return candle.close;
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}
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});
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const result = [];
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for (let i = length - 1; i < sourceData.length; i++) {
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const start = Math.max(0, i - length + 1);
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const slice = sourceData.slice(start, i + 1);
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const avg = slice.reduce((sum, v) => sum + v, 0) / length;
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const std = Math.sqrt(slice.reduce((sum, v) => sum + Math.pow(v - avg, 2), 0) / length);
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result.push({ time: data[i].time, upper: avg + upperMultiplier * std, middle: avg, lower: avg - lowerMultiplier * std });
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}
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return result;
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}
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return { computeEMA, calculateMA, calculateBB };
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})();
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+117
-1451
File diff suppressed because it is too large
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