jackyu66gitandCursor
74dec4e50b
将根目录引擎迁入 chanlun/ 并保留兼容 shim；拆分 TF_DF 与 web 服务； 前端模块化；strategies 改用 chanlun 导入；补充 ESS 文档与 golden 回归。 Co-authored-by: Cursor <cursoragent@cursor.com>
127 lines
3.6 KiB
Python
127 lines
3.6 KiB
Python
"""趋势相关 API。"""
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from flask import Blueprint, jsonify, request
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from services.runtime import * # noqa: F403
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from services import runtime as R
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bp = Blueprint("trend", __name__)
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@bp.route('/api/trend_filter', methods=['GET'])
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def trend_filter():
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"""趋势筛选接口（币对）
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参数:
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timeframe: K线周期
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start_time, end_time: 毫秒时间戳，可选
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direction: bull/bear/sideways 可选
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stage: early/mid/late 可选
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min_strength: 0-100 可选
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symbols: 逗号分隔列表，可选；不传则自动加载部分USDT币对
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返回符合条件的币对与简要统计
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"""
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timeframe = request.args.get('timeframe', '1h')
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start_time = request.args.get('start_time')
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end_time = request.args.get('end_time')
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want_direction = request.args.get('direction') # 可为 None
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want_stage = request.args.get('stage') # 可为 None
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try:
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min_strength = float(request.args.get('min_strength', '0'))
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except ValueError:
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min_strength = 0.0
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symbols_param = request.args.get('symbols')
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if symbols_param:
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symbols_list = [s.strip() for s in symbols_param.split(',') if s.strip()]
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else:
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symbols_list = load_crypto_symbols(limit=150)
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results = []
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for sym in symbols_list:
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try:
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df = get_crypto_kl_data(sym, timeframe, start_time=start_time, end_time=end_time)
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if df is None or len(df) < 60:
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continue
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df = add_indicators(df)
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direction, stage, strength = classify_trend_stage(df)
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if want_direction and direction != want_direction:
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continue
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if want_stage and stage != want_stage:
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continue
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if strength < min_strength:
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continue
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last_row = df.iloc[-1]
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results.append({
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'symbol': sym,
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'time': int(last_row['timestamp']),
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'close': float(last_row['close']),
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'direction': direction,
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'stage': stage,
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'strength': float(round(strength, 2)),
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'ema5': float(last_row['ema5']),
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'ema10': float(last_row['ema10']),
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'ema24': float(last_row['ema24']),
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'ema52': float(last_row['ema52'])
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})
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except Exception:
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continue
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# 按强度降序
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results.sort(key=lambda x: x['strength'], reverse=True)
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return jsonify({
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'count': len(results),
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'results': results
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})
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@bp.route('/api/trend_detail', methods=['GET'])
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def trend_detail():
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"""返回单个币对的K线与EMA、用于前端绘制趋势线
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参数: symbol, timeframe, start_time, end_time
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"""
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symbol = request.args.get('symbol')
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timeframe = request.args.get('timeframe', '1h')
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start_time = request.args.get('start_time')
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end_time = request.args.get('end_time')
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timezone_name = request.args.get('timezone', 'Asia/Shanghai')
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if not symbol:
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return jsonify({'error': 'symbol不能为空'})
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df = get_crypto_kl_data(symbol, timeframe, start_time=start_time, end_time=end_time)
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if df is None or len(df) == 0:
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return jsonify({'error': '获取数据失败'})
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df = add_indicators(df)
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direction, stage, strength = classify_trend_stage(df)
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# 简单趋势线: 用最近N根收盘价做线性拟合
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N = min(80, len(df))
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sub = df.tail(N)
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y = sub['close'].values
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x = np.arange(len(y))
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denom = np.dot(x - x.mean(), x - x.mean())
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if denom != 0:
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m = float(np.dot(y - y.mean(), x - x.mean()) / denom)
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b = float(y.mean() - m * x.mean())
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else:
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m, b = 0.0, float(y[-1])
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client_tz = timezone(timezone_name)
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return jsonify({
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'symbol': symbol,
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'timeframe': timeframe,
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'timezone': timezone_name,
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'direction': direction,
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'stage': stage,
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'strength': float(round(strength, 2)),
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'kline_data': clean_dataframe_for_json(df)[['timestamp','open','high','low','close','volume','ema5','ema10','ema24','ema52']].to_dict('records'),
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'trend_line': {
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'offset': int(df.index[-N]),
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'slope': m,
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'intercept': b,
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'length': int(N)
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}
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})
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