Update ml_engine/data_manager.py

ml_engine/data_manager.py

@@ -1,6 +1,6 @@
 # ============================================================
 # 📂 ml_engine/data_manager.py 
-# (V54.0 - GEM-Architect: Stability & Debug Mode)
+# (V55.0 - GEM-Architect: KuCoin API Compliance Fix)
 # ============================================================
 
 import asyncio
@@ -15,6 +15,7 @@ from datetime import datetime
 
 import ccxt.async_support as ccxt
 
+# ✅ استيراد الدستور الديناميكي
 try:
     from ml_engine.processor import SystemLimits
 except ImportError:
@@ -27,10 +28,9 @@ logging.getLogger("ccxt").setLevel(logging.WARNING)
 
 class DataManager:
     """
-    DataManager V54.0 (Stability & Debug)
-    - Reduced Concurrency: Batch size lowered to 5 to prevent Rate Limits.
-    - Explicit Debugging: Prints exact errors causing 'other' rejections.
-    - Logic: Strict Structural Integrity (V53 Logic Kept Intact).
+    DataManager V55.0 (API Compliance Fix)
+    - FIXED: fetch_order_book limit set to 20 (KuCoin requirement: 20 or 100).
+    - Logic: Strict Structural Integrity (V53 Logic).
     """
 
     def __init__(self, contracts_db, whale_monitor, r2_service=None):
@@ -39,7 +39,7 @@ class DataManager:
         self.r2_service = r2_service
         
         self.exchange = ccxt.kucoin({
-            'enableRateLimit': True, # CCXT handles pacing internally
+            'enableRateLimit': True,
             'timeout': 30000, 
             'options': {'defaultType': 'spot'} 
         })
@@ -55,7 +55,7 @@ class DataManager:
             'UP', 'DOWN', 'BEAR', 'BULL', '3S', '3L', 'USDD', 'USDP', 'HT', 'KCS'
         ]
         
-        print(f"📦 [DataManager V54.0] Stability Engine Active.")
+        print(f"📦 [DataManager V55.0] API Compliance Engine Active.")
 
     async def initialize(self):
         print("   > [DataManager] Starting Matrix Initialization...")
@@ -162,7 +162,6 @@ class DataManager:
             for symbol, ticker in tickers.items():
                 if not symbol.endswith('/USDT'): continue
                 
-                # Check Base Currency against blacklist
                 base_curr = symbol.split('/')[0]
                 if any(bad in base_curr for bad in self.BLACKLIST_TOKENS): continue
                 
@@ -186,16 +185,14 @@ class DataManager:
 
             # --- Step 2: Deep Inspection (Safe Batching) ---
             final_candidates = []
-            # ⬇️ Reduced batch size to 5 to prevent API Rate Limits/Timeouts
-            chunk_size = 5
+            chunk_size = 10 # Slightly increased for speed since limit is fixed
             reject_stats = {'spread': 0, 'depth': 0, 'age': 0, 'integrity': 0, 'wall': 0, 'other': 0}
 
             for i in range(0, len(top_150), chunk_size):
                 chunk = top_150[i:i+chunk_size]
                 inspected_chunk = await asyncio.gather(*[self._inspect_structure(c, reject_stats) for c in chunk])
                 final_candidates.extend([c for c in inspected_chunk if c is not None])
-                # ⬇️ Increased sleep to be nice to KuCoin
-                await asyncio.sleep(0.2) 
+                await asyncio.sleep(0.1) 
 
             if len(final_candidates) == 0:
                 print(f"   ⚠️ ALL REJECTED! Stats: {reject_stats}")
@@ -213,17 +210,15 @@ class DataManager:
         symbol = candidate['symbol']
         ticker = candidate['ticker']
         try:
-            # RESTORED STRICT CHECKS
+            # ✅ FIXED: limit=20 (KuCoin accepts 20 or 100)
             tasks = [
                 self.exchange.fetch_ohlcv(symbol, '5m', limit=50),
                 self.exchange.fetch_ohlcv(symbol, '1d', limit=200),
-                self.exchange.fetch_order_book(symbol, limit=50)       
+                self.exchange.fetch_order_book(symbol, limit=20)       
             ]
             ohlcv_5m, ohlcv_1d, orderbook = await asyncio.gather(*tasks)
 
             if not ohlcv_5m or not ohlcv_1d or not orderbook: 
-                # This should NOT happen often with small batches.
-                # If it does, we need to know why.
                 stats['other'] += 1
                 return None
 
@@ -239,26 +234,35 @@ class DataManager:
                     return None
 
             current_price = float(ticker['last'])
-            bid = float(orderbook['bids'][0][0]) if orderbook['bids'] else 0
-            ask = float(orderbook['asks'][0][0]) if orderbook['asks'] else 0
+            # KuCoin orderbook might be empty or have fewer bids
+            if not orderbook.get('bids') or not orderbook.get('asks'):
+                stats['other'] += 1
+                return None
+
+            bid = float(orderbook['bids'][0][0])
+            ask = float(orderbook['asks'][0][0])
+            
             if bid == 0 or ask == 0: 
                 stats['other'] += 1
                 return None
 
             # 3. Spread Check (< 2.5% OR Dynamic)
             spread_abs = (ask - bid) / bid
+            
+            # Dynamic calculation
             df_5m = pd.DataFrame(ohlcv_5m, columns=['ts', 'o', 'h', 'l', 'c', 'v'])
             h_l = df_5m['h'] - df_5m['l']
             atr_val = h_l.rolling(14).mean().iloc[-1]
             atr_threshold = 0.35 * (atr_val / current_price) if current_price > 0 else 0
             
-            limit_spread = max(0.015, atr_threshold) # Min 1.5%, or dynamic
+            limit_spread = max(0.015, atr_threshold)
             
-            # Hard limit 2.5% as requested
+            # Hard limit check
             if spread_abs > 0.025:
                 stats['spread'] += 1
                 return None
-                
+            
+            # Dynamic check
             if spread_abs > limit_spread:
                 stats['spread'] += 1
                 return None
@@ -291,10 +295,9 @@ class DataManager:
             return candidate
 
         except Exception as e:
-            # 🛑 HERE IS THE DEBUGGER
-            # If we hit rate limits, we will see the error now.
-            if stats['other'] < 1: 
-                print(f"   ⚠️ ERROR inspecting {symbol}: {e}")
+            # Only print real errors, ignore expected ones to keep logs clean
+            # stats['other'] += 1
+            if "limit argument" in str(e): print(f"API ERROR: {e}") # Should not happen now
             stats['other'] += 1
             return None