Update app.py

app.py

@@ -42,6 +42,8 @@ YF_TF = {
     "1d":  ("1d",  "5y"),
 }
 
+TARGET_BARS = 1000
+
 
 # ---------- Helpers ----------
 def _sig(x):
@@ -74,12 +76,12 @@ def _rsi(c, p=14):
 # ---------- yfinance Data Layer ----------
 def fetch_pairs(n=30):
     """Return fixed 30-coin USDT list (yfinance)."""
-    out = COINS[:max(30, min(30, int(n)))]
+    out = COINS[:30]
     print(f"[RCEA] {len(out)} yfinance pairs resolved", flush=True)
     return out
 
 
-def fetch_klines(inst_id, timeframe, target_bars=1000):
+def fetch_klines(inst_id, timeframe, target_bars=TARGET_BARS):
     """
     Fetch OHLCV from Yahoo Finance via yfinance.
     For 4h, downloads 1h and resamples to 4H.
@@ -362,7 +364,7 @@ def run(timeframe, n_coins, thr, lam, mconf, maxhold, progress=gr.Progress()):
     def err(msg, detail=""):
         return msg, detail, pd.DataFrame(), pd.DataFrame(), pd.DataFrame(), pd.DataFrame()
 
-    n_coins = max(30, min(30, int(n_coins)))   # sabit 30
+    n_coins = 30   # sabit — yfinance 30 parite
     thr = max(0.0, min(1.0, float(thr)))
     lam = max(0.0, min(0.99, float(lam)))
     mconf = max(0.0, min(1.0, float(mconf)))
@@ -475,7 +477,7 @@ with gr.Blocks(title="RCEA Lite v1.0 — yfinance") as demo:
     with gr.Row():
         with gr.Column(scale=1):
             tf = gr.Dropdown(["15m", "1h", "4h", "1d"], value="1h", label="Timeframe")
-            nc = gr.Slider(30, 30, value=30, step=1, label="Coins (fixed 30)")
+            nc = gr.Number(value=30, label="Coins (fixed 30)", interactive=False)
             thr_i = gr.Slider(0.0, 1.0, value=0.06, step=0.01, label="Evidence threshold")
             lam_i = gr.Slider(0.0, 0.99, value=0.70, step=0.01, label="Memory λ")
             mc_i = gr.Slider(0.0, 1.0, value=0.30, step=0.01, label="Min regime confidence")