Update app.py

app.py

@@ -66,6 +66,7 @@ ALIASES = {
     "exchange": ["exchange"],
     "limit": ["limit", "count", "n", "bars"],
     "until": ["until", "end", "end_time", "endTime", "to", "before"],
+    "include_series": ["include_series", "includeSeries", "series", "with_series"],
 }
 
 EXTRA_TOOLS = ["detect_divergence", "detect_patterns", "analyze_structure",
@@ -146,6 +147,69 @@ async def fetch_ohlcv(session, tools, symbol, timeframe, exchange, total):
     return out.to_dict("records")
 
 
+def _numeric_list(o, min_len):
+    return (isinstance(o, list) and len(o) >= min_len and
+            all(x is None or (isinstance(x, (int, float)) and not isinstance(x, bool)) for x in o[:50]))
+
+
+def extract_series(payload, n):
+    """compute_indicators çıktısında gezinip bar bazlı sayısal serileri bulur (şemadan bağımsız)."""
+    min_len = max(50, int(n * 0.5))
+    out = {}
+
+    def walk(o, path):
+        if isinstance(o, list):
+            if _numeric_list(o, min_len):
+                out[path] = o
+            elif len(o) >= min_len and all(isinstance(x, dict) for x in o[:3]):
+                for key in o[0]:
+                    vals = [r.get(key) if isinstance(r, dict) else None for r in o]
+                    if _numeric_list(vals, min_len) and key.lower() not in ("ts", "time", "timestamp", "t"):
+                        out[f"{path}.{key}"] = vals
+        elif isinstance(o, dict):
+            for k, v in o.items():
+                walk(v, f"{path}.{k}" if path else str(k))
+
+    walk(payload, "")
+    return out
+
+
+def indicator_features(ind, df: pd.DataFrame):
+    """Tickscope'un 73 göstergesinin zaman serilerini (varsa) df'e hizalı özellik tablosuna çevirir.
+    Fiyat seviyesi gibi duran (SMA/EMA/bant vb.) seriler kapanışa göre normalize edilir."""
+    if not isinstance(ind, dict) or "error" in ind:
+        return None
+    n = len(df)
+    close = df["close"].values
+    cols = {}
+    for path, vals in extract_series(ind, n).items():
+        s = pd.to_numeric(pd.Series(vals), errors="coerce").values.astype(float)
+        arr = np.full(n, np.nan)
+        m = min(len(s), n)
+        arr[-m:] = s[-m:]                      # seriler sondan hizalanır
+        if np.isnan(arr).all() or np.nanstd(arr) == 0:
+            continue
+        ref = np.nanmedian(close[-m:])
+        if ref and abs(np.nanmedian(arr) / ref - 1) < 0.5:   # fiyat seviyesi -> göreli mesafe
+            arr = arr / close - 1
+        name = "ts_" + "".join(ch if ch.isalnum() else "_" for ch in path).strip("_")
+        cols[name] = arr
+    if not cols:
+        return None
+    return pd.DataFrame(cols, index=df.index)
+
+
+def _strip_series(o, keep=3):
+    """Ham çıktıyı okunur tutmak için uzun serileri son `keep` değere kısaltır."""
+    if isinstance(o, list) and len(o) > 20:
+        return [f"... {len(o)} değer, son {keep}:"] + o[-keep:]
+    if isinstance(o, list):
+        return [_strip_series(x, keep) for x in o]
+    if isinstance(o, dict):
+        return {k: _strip_series(v, keep) for k, v in o.items()}
+    return o
+
+
 def to_df(payload) -> pd.DataFrame:
     rows = payload
     if isinstance(payload, dict):
@@ -304,8 +368,16 @@ def _backtest(p, fwd, horizon, thr, fee):
             "hit": float((tr > 0).mean()), "pf": float(gp / gl) if gl > 0 else np.inf}
 
 
-def predict(df: pd.DataFrame, horizon: int, fee: float = 0.0006, n_folds: int = 5):
+def predict(df: pd.DataFrame, horizon: int, fee: float = 0.0006, n_folds: int = 5, ext=None):
     feats, atr = make_features(df)
+    n_ext = 0
+    if ext is not None:
+        ext = ext.replace([np.inf, -np.inf], np.nan)
+        w0 = min(60, len(df) // 5)
+        # ısınma sonrası %10'dan fazla boş olan Tickscope kolonlarını at
+        ext = ext.loc[:, ext.iloc[w0:].isna().mean() <= 0.10]
+        n_ext = ext.shape[1]
+        feats = pd.concat([feats, ext], axis=1)
     close = df["close"]
     fwd = close.shift(-horizon) / close - 1
     y = (fwd > 0).astype(float)
@@ -374,6 +446,7 @@ def predict(df: pd.DataFrame, horizon: int, fee: float = 0.0006, n_folds: int =
         "p_up": p_up, "acc": acc, "baseline": base, "auc": auc, "price": price, "atr": a,
         "center": center, "low": center - move, "high": center + move,
         "thr": best["thr"], "bt": best, "n_oos": len(oos_p), "fee": fee,
+        "n_ext": n_ext, "n_feat": len(cols),
     }
 
 
@@ -394,7 +467,8 @@ async def run_async(symbol, timeframe, exchange, horizon, limit):
             deep = await call_tool(session, tools, "deep_analyze", symbol=symbol,
                                    timeframe=timeframe, exchange=exchange)
             ind = await call_tool(session, tools, "compute_indicators", symbol=symbol,
-                                  timeframe=timeframe, exchange=exchange)
+                                  timeframe=timeframe, exchange=exchange,
+                                  limit=int(limit), include_series=True)
 
             # Tickscope'un diğer tüm analiz/piyasa araçları (canlı bağlam; şema uyuşmazsa hata olarak kaydedilir)
             extra = {}
@@ -421,7 +495,8 @@ def run(symbol, timeframe, exchange, horizon, limit):
     try:
         ohlcv, deep, ind, extra = asyncio.run(run_async(symbol, timeframe, exchange, horizon, limit))
         df = to_df(ohlcv)
-        res = predict(df, int(horizon))
+        ext = indicator_features(ind, df)
+        res = predict(df, int(horizon), ext=ext)
     except BaseException as e:  # noqa: BLE001
         import traceback
         traceback.print_exc()
@@ -441,6 +516,7 @@ def run(symbol, timeframe, exchange, horizon, limit):
 | OOS AUC / doğruluk | {res['auc']:.3f} / {res['acc']:.1%} (baseline {res['baseline']:.1%}) |
 | OOS işlem sayısı | {bt['n']} (hit {bt['hit']:.1%}, PF {bt['pf']:.2f}) |
 | Ort. net getiri / işlem | {bt['mean']:.3%} (t = {bt['t']:.2f}, ücret {res['fee']:.2%}/işlem) |
+| Özellik sayısı | {res['n_feat']} (Tickscope göstergesi: {res['n_ext']}) |
 | Model edge | {edge} |
 
 *Walk-forward (purged) out-of-sample sonuçlar. Eşik OOS'ta seçildiği için hafif iyimser olabilir. Eğitim/araştırma amaçlıdır; yatırım tavsiyesi değildir.*"""
@@ -458,7 +534,7 @@ def run(symbol, timeframe, exchange, horizon, limit):
                                           arrayminus=[res["center"] - res["low"]])))
     fig.update_layout(height=450, xaxis_rangeslider_visible=False, margin=dict(l=10, r=10, t=30, b=10))
 
-    raw = json.dumps({"deep_analyze": deep, "compute_indicators": ind, **extra},
+    raw = json.dumps(_strip_series({"deep_analyze": deep, "compute_indicators": ind, **extra}),
                      indent=2, ensure_ascii=False, default=str)
     return md, fig, raw