Implement FastAPI backend and Vue 3 frontend for Lowkey Backtest UI

- Added FastAPI backend with core API endpoints for strategies, backtests, and data management.
- Introduced Vue 3 frontend with a dark theme, enabling users to run backtests, adjust parameters, and compare results.
- Implemented Pydantic schemas for request/response validation and SQLAlchemy models for database interactions.
- Enhanced project structure with dedicated modules for services, routers, and components.
- Updated dependencies in `pyproject.toml` and `frontend/package.json` to include FastAPI, SQLAlchemy, and Vue-related packages.
- Improved `.gitignore` to exclude unnecessary files and directories.

api/routers/data.py

@@ -0,0 +1,97 @@
+"""
+Data status and symbol information endpoints.
+"""
+from pathlib import Path
+
+import pandas as pd
+from fastapi import APIRouter
+
+from api.models.schemas import DataStatusResponse, SymbolInfo
+
+router = APIRouter()
+
+# Base path for CCXT data
+DATA_BASE = Path(__file__).parent.parent.parent / "data" / "ccxt"
+
+
+def _scan_available_data() -> list[SymbolInfo]:
+    """
+    Scan the data directory for available symbols and timeframes.
+    
+    Returns list of SymbolInfo with date ranges and row counts.
+    """
+    symbols = []
+    
+    if not DATA_BASE.exists():
+        return symbols
+    
+    # Structure: data/ccxt/{exchange}/{market_type}/{symbol}/{timeframe}.csv
+    for exchange_dir in DATA_BASE.iterdir():
+        if not exchange_dir.is_dir():
+            continue
+        exchange = exchange_dir.name
+        
+        for market_dir in exchange_dir.iterdir():
+            if not market_dir.is_dir():
+                continue
+            market_type = market_dir.name
+            
+            for symbol_dir in market_dir.iterdir():
+                if not symbol_dir.is_dir():
+                    continue
+                symbol = symbol_dir.name
+                
+                # Find all timeframes
+                timeframes = []
+                start_date = None
+                end_date = None
+                row_count = 0
+                
+                for csv_file in symbol_dir.glob("*.csv"):
+                    tf = csv_file.stem
+                    timeframes.append(tf)
+                    
+                    # Read first and last rows for date range
+                    try:
+                        df = pd.read_csv(csv_file, parse_dates=['timestamp'])
+                        if not df.empty:
+                            row_count = len(df)
+                            start_date = df['timestamp'].min().strftime("%Y-%m-%d")
+                            end_date = df['timestamp'].max().strftime("%Y-%m-%d")
+                    except Exception:
+                        pass
+                
+                if timeframes:
+                    symbols.append(SymbolInfo(
+                        symbol=symbol,
+                        exchange=exchange,
+                        market_type=market_type,
+                        timeframes=sorted(timeframes),
+                        start_date=start_date,
+                        end_date=end_date,
+                        row_count=row_count,
+                    ))
+    
+    return symbols
+
+
+@router.get("/symbols", response_model=DataStatusResponse)
+async def get_symbols():
+    """
+    Get list of available symbols with their data ranges.
+    
+    Scans the local data directory for downloaded OHLCV data.
+    """
+    symbols = _scan_available_data()
+    return DataStatusResponse(symbols=symbols)
+
+
+@router.get("/data/status", response_model=DataStatusResponse)
+async def get_data_status():
+    """
+    Get detailed data inventory status.
+    
+    Alias for /symbols with additional metadata.
+    """
+    symbols = _scan_available_data()
+    return DataStatusResponse(symbols=symbols)