Merge branch 'dev'

Author: lbitto-sdg

.dockerignore

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+# .dockerignore
+.git
+.gitignore
+.env
+__pycache__
+*.pyc
+*.pyo
+*.pyd
+
+# Ignora cartelle dati e log (fondamentale per evitare errori permessi)
+data/
+logs/
+config/credentials/

dashboard/home.py

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+# dashboard/Home.py
+import streamlit as st
+import pandas as pd
+from dashboard.utils import load_portfolio_data, load_ohlc_summary
+
+st.set_page_config(page_title="Petunia Dashboard", page_icon="🌸", layout="wide")
+
+st.title("🌸 Petunia | System Overview")
+st.markdown("---")
+
+# 1. KPI Portafoglio
+data = load_portfolio_data()
+df_cash = data.get('cash', pd.DataFrame())
+df_port = data.get('portfolio', pd.DataFrame())
+
+col1, col2, col3, col4 = st.columns(4)
+
+# Calcolo Totali
+cash = float(df_cash.iloc[0]['cash']) if not df_cash.empty else 0.0
+invested = (df_port['price'] * df_port['size']).sum() if not df_port.empty else 0.0
+total_equity = cash + invested
+active_tickers = len(df_port) if not df_port.empty else 0
+
+col1.metric("Total Equity", f"€ {total_equity:,.2f}")
+col2.metric("Cash Available", f"€ {cash:,.2f}")
+col3.metric("Invested Capital", f"€ {invested:,.2f}")
+col4.metric("Active Positions", f"{active_tickers}")
+
+st.markdown("---")
+
+# 2. Stato Sistema
+st.subheader("📡 System Status")
+
+# Tabella riassuntiva Ticker
+df_ohlc = load_ohlc_summary()
+
+c1, c2 = st.columns([2, 1])
+
+with c1:
+    if not df_ohlc.empty:
+        # Ci assicuriamo che 'count' sia un intero
+        df_ohlc['count'] = df_ohlc['count'].astype(int)
+        
+        st.dataframe(
+            df_ohlc,
+            column_config={
+                "ticker": "Ticker",
+                "last_date": "Last Update",
+                "count": st.column_config.ProgressColumn(
+                    "Data Points",
+                    help="Numero di candele OHLC salvate",
+                    format="%d",
+                    min_value=0,
+                    max_value=int(df_ohlc['count'].max())
+                ),
+            },
+            use_container_width=True,
+            hide_index=True
+        )
+    else:
+        st.warning("Nessun dato OHLC nel database.")
+
+with c2:
+    st.info("ℹ️ **Quick Actions**")
+    if st.button("🔄 Refresh Data View"):
+        st.rerun()
+    
+    st.markdown("Per operazioni di scrittura o log, vai al **Control Panel**.")

dashboard/pages/backtest_lab.py

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+import streamlit as st
+import pandas as pd
+from pathlib import Path
+import json
+from services.backtest import run_backtest # Importiamo la funzione backend
+
+st.set_page_config(page_title="Backtest Lab", page_icon="🧪", layout="wide")
+
+st.title("🧪 Backtest Laboratory")
+
+# Sidebar: Configurazione
+with st.sidebar:
+    st.header("⚙️ Configuration")
+    
+    strategy = st.selectbox("Strategy", ["RSI", "MACD (Coming Soon)"])
+    
+    st.subheader("Parameters")
+    initial_cap = st.number_input("Initial Capital (€)", value=10000, step=1000)
+    years = st.slider("Years History", 1, 5, 2)
+    
+    # Parametri Dinamici per RSI
+    params = {}
+    if strategy == "RSI":
+        params['rsi_period'] = st.slider("RSI Period", 5, 30, 14)
+        params['rsi_lower'] = st.slider("Oversold (<)", 10, 45, 30)
+        params['rsi_upper'] = st.slider("Overbought (>)", 55, 90, 70)
+        params['atr_period'] = st.slider("ATR Period", 5, 30, 14)
+    
+    run_btn = st.button("🚀 RUN BACKTEST", type="primary")
+
+# Main Area
+tab_run, tab_history = st.tabs(["Current Run", "History Archive"])
+
+with tab_run:
+    if run_btn:
+        with st.spinner("Running simulation... (This may take a moment)"):
+            try:
+                # Eseguiamo il backtest
+                result_path = run_backtest(
+                    strategy_name=strategy,
+                    initial_capital=initial_cap,
+                    days_history=years*365,
+                    strategy_params=params
+                )
+                st.success(f"Simulation completed! Saved in: {result_path}")
+                
+                # Visualizzazione Rapida Risultati
+                p = Path(result_path)
+                
+                # Immagine
+                if (p / "chart.png").exists():
+                    # CORRETTO: use_container_width invece di width
+                    st.image(str(p / "chart.png"), use_container_width=True)
+                
+                # Metriche da JSON
+                if (p / "config.json").exists():
+                    with open(p / "config.json") as f:
+                        res = json.load(f)
+                    
+                    m1, m2, m3 = st.columns(3)
+                    m1.metric("Final Equity", f"€ {res.get('final_equity', 0):,.2f}")
+                    m2.metric("Total Trades", res.get('total_trades', 0))
+                    # Calcolo ROI al volo
+                    roi = ((res.get('final_equity', 0) - initial_cap) / initial_cap) * 100
+                    m3.metric("Total ROI", f"{roi:+.2f}%")
+                    
+            except Exception as e:
+                st.error(f"Errore durante il backtest: {e}")
+
+with tab_history:
+    st.write("📂 **Previous Runs Browser**")
+    base_dir = Path("data/backtests")
+    
+    if base_dir.exists():
+        # Logica per esplorare le cartelle
+        strategies = [x.name for x in base_dir.iterdir() if x.is_dir()]
+        
+        # --- LAYOUT A COLONNE PER I SELETTORI ---
+        c_strat, c_run = st.columns(2)
+        
+        with c_strat:
+            sel_strat = st.selectbox("Select Strategy Folder", strategies)
+        
+        sel_run = None
+        if sel_strat:
+            with c_run:
+                # Controllo se la cartella esiste e non è vuota
+                strat_path = base_dir / sel_strat
+                if strat_path.exists():
+                     runs = sorted([x.name for x in strat_path.iterdir()], reverse=True)
+                     sel_run = st.selectbox("Select Timestamp", runs)
+            
+            if sel_run:
+                run_path = base_dir / sel_strat / sel_run
+                st.caption(f"Path: {run_path}")
+                st.markdown("---")
+                
+                # Visualizzazione Dati
+                col_img, col_data = st.columns([1, 1])
+                
+                with col_img:
+                    if (run_path / "chart.png").exists():
+                        # CORRETTO: use_container_width
+                        st.image(str(run_path / "chart.png"), use_container_width=True)
+                
+                with col_data:
+                    if (run_path / "config.json").exists():
+                        with open(run_path / "config.json") as f:
+                            conf = json.load(f)
+                        st.json(conf, expanded=False)
+
+                    if (run_path / "trades.csv").exists():
+                        # CORRETTO: use_container_width e height numerico
+                        st.dataframe(pd.read_csv(run_path / "trades.csv"), use_container_width=True, height=300)

dashboard/pages/control_panel.py

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+import streamlit as st
+from pathlib import Path
+import time
+
+# Import Servizi Backend
+from src.yfinance_manager import YFinanceManager
+from src.database_manager import DatabaseManager
+from src.drive_manager import DriveManager
+
+st.set_page_config(page_title="Control Panel", page_icon="🕹️", layout="wide")
+st.title("🕹️ Control Panel & Maintenance")
+
+# Layout a due colonne principali
+col_ops, col_logs = st.columns([1, 1.5])
+
+# --- COLONNA SINISTRA: OPERAZIONI ---
+with col_ops:
+    st.subheader("🛠️ Data Management")
+    
+    with st.container(border=True):
+        st.write("### 📥 Fetch Historical Data")
+        st.caption("Scarica dati da Yahoo Finance e popola il DB.")
+        
+        # Form per i parametri
+        years_to_fetch = st.number_input("Years of History", min_value=1, max_value=10, value=1)
+        
+        if st.button("🚀 Start Data Fetch", type="primary"):
+            status_container = st.status("Avvio procedura di download...", expanded=True)
+            try:
+                # 1. Recupero Ticker da GSheets
+                status_container.write("Lettura Universe da Google Sheets...")
+                drive = DriveManager()
+                tickers = drive.get_universe_tickers()
+                
+                if not tickers:
+                    status_container.error("Nessun ticker trovato nel foglio 'Universe'!")
+                else:
+                    status_container.write(f"Trovati {len(tickers)} ticker: {tickers}")
+                    
+                    # 2. Download da YFinance
+                    status_container.write(f"Download di {years_to_fetch} anni di storico...")
+                    yf = YFinanceManager()
+                    data = yf.fetch_history(tickers, years=years_to_fetch)
+                    
+                    if data:
+                        # 3. Salvataggio DB
+                        status_container.write(f"Salvataggio di {len(data)} righe nel Database...")
+                        db = DatabaseManager()
+                        db.upsert_ohlc(data)
+                        
+                        status_container.update(label="✅ Operazione completata con successo!", state="complete", expanded=False)
+                        st.success(f"Database aggiornato con {len(data)} nuovi record!")
+                        time.sleep(2)
+                        st.rerun() # Ricarica per aggiornare eventuali metriche
+                    else:
+                        status_container.error("Nessun dato ricevuto da Yahoo Finance.")
+                        
+            except Exception as e:
+                status_container.error(f"Errore critico: {e}")
+
+    st.markdown("---")
+    
+    with st.container(border=True):
+        st.write("### ⚠️ Danger Zone")
+        if st.button("🗑️ Reset Database Schema"):
+            if st.checkbox("Confermo di voler cancellare TUTTI i dati"):
+                db = DatabaseManager()
+                db.drop_schema()
+                db.init_schema()
+                st.warning("Database resettato e tabelle ricreate.")
+
+# --- COLONNA DESTRA: LOGS ---
+with col_logs:
+    st.subheader("📜 System Logs Inspector")
+    
+    # 1. Trova tutti i file .log nella cartella logs/
+    log_dir = Path("logs")
+    if log_dir.exists():
+        # Glob restituisce i file, ne prendiamo solo il nome
+        log_files = [f.name for f in log_dir.glob("*.log")]
+        
+        if log_files:
+            # Selectbox per scegliere IL servizio
+            selected_file = st.selectbox("Select Log File:", log_files, index=0)
+            
+            # Slider per quante righe leggere
+            lines_count = st.slider("Lines to view:", 10, 200, 50)
+            
+            # Tasto refresh manuale
+            if st.button("🔄 Refresh Logs"):
+                st.rerun()
+            
+            # Lettura e Visualizzazione
+            log_path = log_dir / selected_file
+            try:
+                with open(log_path, "r", encoding="utf-8") as f:
+                    # Leggiamo tutto e prendiamo le ultime N righe
+                    all_lines = f.readlines()
+                    tail_lines = all_lines[-lines_count:]
+                    
+                # Mostriamo in un blocco di codice scrollabile
+                log_content = "".join(tail_lines)
+                if not log_content.strip():
+                    st.info("File di log vuoto.")
+                else:
+                    st.code(log_content, language="log")
+                    
+            except Exception as e:
+                st.error(f"Impossibile leggere il file: {e}")
+        else:
+            st.warning("Nessun file .log trovato. Esegui qualche operazione prima!")
+    else:
+        st.error("Cartella 'logs' non trovata. Verifica il volume Docker.")