feat: add EMA strategy, refactor strategy pkg, add full pytest suite

- Refactoring: Spostate strategie in src/strategies con Factory pattern
- New: Implementata strategia EMA Crossover
- Test: Aggiunta infrastruttura Pytest completa (Core + Strategies)
- Test: Aggiunti Integration Test per DB e Mock per servizi esterni
- Ops: Aggiornato manager.sh con comando 'test'
- Ops: Aggiornato requirements.txt e CI workflow

Author: lbitto-sdg

.dockerignore

@@ -10,4 +10,7 @@ __pycache__
 # Ignora cartelle dati e log (fondamentale per evitare errori permessi)
 data/
 logs/
-config/credentials/
+config/credentials/
+.pytest_cache
+htmlcov
+.coverage

manager.sh

@@ -54,6 +54,12 @@ case "$1" in
         docker compose run --rm app python -m services.backtest
         ;;
 
+	test)
+        echo -e "${GREEN}Running Tests (Pytest inside Docker)...${NC}"
+        # Esegue pytest sulla cartella tests/ con verbosità attiva (-v)
+        docker compose run --rm app pytest tests/ -v
+        ;;
+		
     shell)
         echo -e "${GREEN}Opening Shell...${NC}"
         docker compose run --rm -it app /bin/bash
@@ -73,8 +79,8 @@ case "$1" in
         docker compose logs -f dashboard
         ;;
 
-    *)
-        echo "Usage: $0 {setup|start|stop|status|daily|weekly|backtest|shell}"
+	*)
+        echo "Usage: $0 {setup|start|stop|status|daily|weekly|backtest|test|shell|dashboard}"
         exit 1
         ;;
 esac

requirements.txt

@@ -16,4 +16,5 @@ requests>=2.31,<3.0
 yfinance>=0.2,<0.3
 matplotlib>=3.8,<4.0
 streamlit>=1.30,<2.0
-plotly>=5.18,<6.0
+plotly>=5.18,<6.0
+pytest>=7.0,<8.0

services/backtest.py

@@ -15,7 +15,7 @@
 from src.logger import get_logger
 
 # Import Strategie
-from src.strategy_RSI import StrategyRSI
+from src.strategies import StrategyRSI, StrategyEMA
 
 logger = get_logger("Backtester")
 
@@ -79,6 +79,12 @@ def run_backtest(strategy_name: str = "RSI",
             rsi_upper=strategy_params.get('rsi_upper', 70),
             atr_period=strategy_params.get('atr_period', 14)
         )
+    elif strategy_name == "EMA":
+         strategy = StrategyEMA(
+            short_window=strategy_params.get('short_window', 50),
+            long_window=strategy_params.get('long_window', 200),
+            atr_period=strategy_params.get('atr_period', 14)
+        )
     else:
         logger.error(f"Strategia {strategy_name} non implementata.")
         return

services/weekly_run.py

@@ -7,7 +7,7 @@
 from src.drive_manager import DriveManager
 from src.risk_manager import RiskManager
 from src.logger import get_logger
-from src.strategy_RSI import StrategyRSI
+from src.strategies import StrategyRSI, StrategyEMA
 
 logger = get_logger("WeeklyRun")
 

src/strategies/__init__.py

@@ -0,0 +1,5 @@
+from .base import StrategyBase
+from .rsi import StrategyRSI
+from .ema import StrategyEMA
+
+__all__ = ["StrategyBase", "StrategyRSI", "StrategyEMA"]

src/strategy_base.py src/strategies/base.pysrc/strategy_base.py renamed to src/strategies/base.py

@@ -0,0 +1,88 @@
+import pandas as pd
+import numpy as np
+from typing import Dict
+from .base import StrategyBase
+
+class StrategyEMA(StrategyBase):
+    """
+    Strategia Trend Following basata su incrocio medie mobili esponenziali (EMA).
+    Segnale BUY: EMA_short > EMA_long
+    Segnale SELL: EMA_short < EMA_long
+    """
+
+    def __init__(self, short_window: int = 50, long_window: int = 200, atr_period: int = 14):
+        super().__init__("EMA_Crossover")
+        self.short_window = short_window
+        self.long_window = long_window
+        self.atr_period = atr_period
+
+    def _calculate_atr(self, df: pd.DataFrame, period: int) -> pd.Series:
+        """Calcolo ATR manuale (identico a RSI, potremmo portarlo in Base in futuro)."""
+        high = df['high']
+        low = df['low']
+        close = df['close']
+        
+        tr1 = high - low
+        tr2 = (high - close.shift()).abs()
+        tr3 = (low - close.shift()).abs()
+        tr = pd.concat([tr1, tr2, tr3], axis=1).max(axis=1)
+        return tr.ewm(alpha=1.0/period, adjust=False).mean()
+
+    def compute(self, data_map: Dict[str, pd.DataFrame]) -> pd.DataFrame:
+        signals_list = []
+        self.logger.info(f"Avvio strategia EMA Cross ({self.short_window}/{self.long_window}) su {len(data_map)} ticker.")
+
+        for ticker, df in data_map.items():
+            # 1. Validazione Dati
+            if len(df) < self.long_window:
+                continue
+
+            df = df.copy().sort_values('date')
+
+            # 2. Calcolo Indicatori
+            try:
+                df['EMA_short'] = df['close'].ewm(span=self.short_window, adjust=False).mean()
+                df['EMA_long'] = df['close'].ewm(span=self.long_window, adjust=False).mean()
+                df['ATR'] = self._calculate_atr(df, self.atr_period)
+            except Exception as e:
+                self.logger.error(f"Errore calcolo math {ticker}: {e}")
+                continue
+
+            # 3. Analisi Ultima Riga
+            last_row = df.iloc[-1]
+            ema_s = last_row['EMA_short']
+            ema_l = last_row['EMA_long']
+            atr_val = last_row['ATR']
+            price = last_row['close']
+
+            if pd.isna(ema_s) or pd.isna(ema_l) or pd.isna(atr_val):
+                continue
+
+            # 4. Logica Trading
+            # Trend Following: Se short > long siamo in trend UP -> BUY/HOLD
+            # Se short < long siamo in trend DOWN -> SELL
+            
+            signal = "HOLD"
+            if ema_s > ema_l:
+                signal = "BUY"
+            elif ema_s < ema_l:
+                signal = "SELL"
+
+            # 5. Output
+            signals_list.append({
+                "ticker": ticker,
+                "date": last_row['date'],
+                "signal": signal,
+                "atr": atr_val,
+                "price": price,
+                "meta": {
+                    "ema_short": round(ema_s, 2),
+                    "ema_long": round(ema_l, 2),
+                    "diff": round(ema_s - ema_l, 2)
+                }
+            })
+
+        if not signals_list:
+            return pd.DataFrame(columns=['ticker', 'date', 'signal', 'atr', 'meta'])
+            
+        return pd.DataFrame(signals_list)

src/strategies/ema.py

@@ -1,7 +1,7 @@
 import pandas as pd
 import numpy as np
 from typing import Dict
-from src.strategy_base import StrategyBase
+from .base import StrategyBase
 
 class StrategyRSI(StrategyBase):
     """