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# ml_engine/data_manager.py
# (V12.5 - Lazy Loading Fix + V15.6 App-Compat Fix + Detailed Logging)
import os
import asyncio
import httpx
import traceback
import time
from datetime import datetime
import ccxt.async_support as ccxt
import numpy as np
import logging
from typing import List, Dict, Any
import pandas as pd
try:
import pandas_ta as ta
except ImportError:
print("❌ [DataManager] مكتبة pandas_ta غير موجودة.")
ta = None
from ml_engine.indicators import AdvancedTechnicalAnalyzer
from ml_engine.monte_carlo import MonteCarloAnalyzer
from ml_engine.ranker import Layer1Ranker
try:
from ml_engine.patterns import ChartPatternAnalyzer
except ImportError:
print("⚠️ [DataManager] لم يتم العثور على ml_engine/patterns.py")
ChartPatternAnalyzer = None
logging.getLogger("httpx").setLevel(logging.WARNING)
logging.getLogger("httpcore").setLevel(logging.WARNING)
logging.getLogger("ccxt").setLevel(logging.WARNING)
class DataManager:
def __init__(self, contracts_db, whale_monitor, r2_service=None):
# ==================================================================
# ⚙️ إعدادات التحكم المركزية (V12.3 Hybrid Thresholds)
# ==================================================================
self.HYBRID_ENTRY_THRESHOLD = 0.60
# ==================================================================
self.contracts_db = contracts_db or {}
self.whale_monitor = whale_monitor
self.r2_service = r2_service
self.exchange = ccxt.kucoin({
'enableRateLimit': True,
'timeout': 30000,
})
self.http_client = None
self.market_cache = {}
self.technical_analyzer = AdvancedTechnicalAnalyzer()
self.mc_analyzer = MonteCarloAnalyzer()
self.layer1_ranker = None
self.pattern_analyzer = None
async def initialize(self):
"""تهيئة مدير البيانات والاتصالات"""
print(" > [DM Log] 0. بدء تهيئة DataManager...")
self.http_client = httpx.AsyncClient(timeout=30.0)
await self._load_markets()
print(" > [DataManager] إنشاء النماذج المساندة (Lazy Load)...")
try:
self.layer1_ranker = Layer1Ranker(model_path="ml_models/layer1_ranker.lgbm")
if ChartPatternAnalyzer:
self.pattern_analyzer = ChartPatternAnalyzer(r2_service=self.r2_service)
except Exception as e:
print(f"⚠️ [DataManager] تحذير أثناء إنشاء النماذج المساندة: {e}")
print(f"✅ DataManager V12.5 initialized (Hybrid Threshold: {self.HYBRID_ENTRY_THRESHOLD})")
print(" > [DM Log] 4. اكتملت تهيئة DataManager.")
async def _load_markets(self):
"""تحميل بيانات الأسواق وتخزينها مؤقتاً"""
print(" > [DM Log] 1. بدء _load_markets...")
try:
if self.exchange:
print(" > [DM Log] 2. استدعاء exchange.load_markets()... (قد يستغرق وقتاً)")
await self.exchange.load_markets()
self.market_cache = self.exchange.markets
if self.market_cache and len(self.market_cache) > 0:
print(f" > [DM Log] 3. ✅ نجاح! تم تحميل {len(self.market_cache)} سوق.")
else:
print(" > [DM Log] 3. ⚠️ تحذير: load_markets() نجح ولكن لم يتم إرجاع أسواق.")
else:
print(" > [DM Log] 2. ❌ خطأ: self.exchange هو None.")
except Exception as e:
print(f" > [DM Log] 3. ❌❌❌ فشل فادح في _load_markets: {e}")
traceback.print_exc()
async def close(self):
"""إغلاق جميع الاتصالات بأمان"""
print(" > [DM Log] 7. إغلاق اتصالات DataManager...")
if self.http_client: await self.http_client.aclose()
if self.exchange: await self.exchange.close()
if self.pattern_analyzer and hasattr(self.pattern_analyzer, 'clear_memory'):
self.pattern_analyzer.clear_memory()
if self.layer1_ranker and hasattr(self.layer1_ranker, 'clear_memory'):
self.layer1_ranker.clear_memory()
# ==================================================================
# 🚀 [إضافة جديدة V15.6] دوال التوافق مع App
# ==================================================================
async def load_contracts_from_r2(self):
"""
[جديد] يقوم بتحميل قاعدة بيانات العقود من R2 عند بدء التشغيل.
"""
print(" > [DataManager] Loading contracts database from R2...")
if not self.r2_service:
print("❌ [DataManager] R2Service not available. Cannot load contracts.")
self.contracts_db = {}
return
try:
self.contracts_db = await self.r2_service.load_contracts_db_async()
print(f"✅ [DataManager] Contracts loaded. Total entries: {len(self.contracts_db)}")
except Exception as e:
print(f"❌ [DataManager] Failed to load contracts from R2: {e}")
self.contracts_db = {}
def get_contracts_db(self) -> Dict[str, Any]:
"""
[جديد] إرجاع قاعدة بيانات العقود التي تم تحميلها.
"""
return self.contracts_db
# ==================================================================
# 🛡️ دوال الطبقة الأولى (Layer 1 Screening)
# ==================================================================
async def layer1_rapid_screening(self) -> List[Dict[str, Any]]:
"""
الغربلة الأولية السريعة جداً بناءً على الحجم فقط.
"""
print(f"🔍 [Layer 1] بدء الغربلة السريعة (Top Liquid Assets)...")
volume_data = await self._get_volume_data_live()
if not volume_data:
print("⚠️ [Layer 1 Warning] لم يتم العثور على بيانات حجم تداول.")
return []
candidates = volume_data[:150]
print(f"✅ [Layer 1] تم تمرير {len(candidates)} عملة للتحليل الهجين.")
return candidates
async def _get_volume_data_live(self):
"""جلب بيانات الحجم الحية لجميع الأزواج"""
try:
tickers = await self.exchange.fetch_tickers()
data = []
for symbol, ticker in tickers.items():
if symbol.endswith('/USDT') and ticker.get('quoteVolume') and ticker['quoteVolume'] > 100000:
data.append({
'symbol': symbol,
'dollar_volume': ticker['quoteVolume'],
'current_price': ticker['last']
})
data.sort(key=lambda x: x['dollar_volume'], reverse=True)
return data
except Exception as e:
print(f"❌ [DataManager] خطأ في جلب بيانات الحجم: {e}")
return []
# ==================================================================
# 📊 دوال جلب البيانات (Data Fetching Pipeline)
# ==================================================================
async def stream_ohlcv_data(self, symbols: List[Dict], queue: asyncio.Queue):
"""
مولد بيانات متدفق (Streaming Generator) يجلب شموع OHLCV
"""
timeframes = ['5m', '15m', '1h', '4h', '1d']
limit = 500
for sym_data in symbols:
symbol = sym_data['symbol']
tasks = [self._fetch_ohlcv_live(symbol, tf, limit) for tf in timeframes]
results = await asyncio.gather(*tasks, return_exceptions=False)
ohlcv_packet = {}
valid_packet = True
for i, res in enumerate(results):
tf = timeframes[i]
if res and isinstance(res, list) and len(res) >= 200:
ohlcv_packet[tf] = res
else:
if tf in ['5m', '1h']: valid_packet = False
if valid_packet and len(ohlcv_packet) >= 4:
sym_data['ohlcv'] = ohlcv_packet
await queue.put([sym_data])
await asyncio.sleep(0.05)
await queue.put(None)
async def _fetch_ohlcv_live(self, symbol, timeframe, limit):
"""دالة مساعدة لجلب الشموع مع معالجة الأخطاء البسيطة"""
try:
return await self.exchange.fetch_ohlcv(symbol, timeframe, limit=limit)
except Exception:
return None
# ==================================================================
# 🎯 دوال مساعدة للحارس والدماغ (Sentry & Brain Helpers)
# ==================================================================
async def get_latest_price_async(self, symbol: str) -> float:
"""جلب آخر سعر حقيقي (للتنفيذ والمراقبة)"""
try:
ticker = await self.exchange.fetch_ticker(symbol)
return float(ticker['last'])
except Exception as e:
print(f"⚠️ [DataManager] Failed to fetch price for {symbol}: {e}")
return 0.0
async def get_latest_ohlcv(self, symbol: str, timeframe: str = '5m', limit: int = 100) -> List[List[float]]:
"""
جلب عدد محدود من الشموع الأخيرة بسرعة.
"""
# (إضافة طابع خفيف لتجنب إغراق السجلات)
# print(f" > [DM Log] 5. [get_latest_ohlcv] طلب {symbol} {timeframe}...")
try:
candles = await self.exchange.fetch_ohlcv(symbol, timeframe, limit=limit)
if candles and len(candles) > 0:
# (لا نطبع هذا لأنه سينجح)
return candles
else:
# (هذا هو الطابع المهم الذي يكشف الفشل الصامت)
print(f" > [DM Log] 6. ⚠️ [get_latest_ohlcv] فشل صامت لـ {symbol} {timeframe}. (أرجع قائمة فارغة).")
return []
except Exception as e:
# (هذا هو الطابع المهم الذي يكشف الفشل الفادح)
print(f" > [DM Log] 6. ❌ [get_latest_ohlcv] فشل فادح لـ {symbol} {timeframe}: {e}")
return []