Add FastAPI backend for energy trading system

Implements FastAPI backend with ML model support for energy trading,
including price prediction models and RL-based battery trading policy.
Features dashboard, trading, backtest, and settings API routes with
WebSocket support for real-time updates.

backend/app/ml/utils/data_split.py

@@ -0,0 +1,25 @@
+from typing import Tuple
+import pandas as pd
+from datetime import datetime
+
+
+def time_based_split(
+    df: pd.DataFrame,
+    timestamp_col: str = "timestamp",
+    train_pct: float = 0.70,
+    val_pct: float = 0.85,
+) -> Tuple[pd.DataFrame, pd.DataFrame, pd.DataFrame]:
+    df_sorted = df.sort_values(timestamp_col)
+
+    n_total = len(df_sorted)
+    n_train = int(n_total * train_pct)
+    n_val = int(n_total * val_pct)
+
+    train = df_sorted.iloc[:n_train]
+    val = df_sorted.iloc[n_train:n_val]
+    test = df_sorted.iloc[n_val:]
+
+    return train, val, test
+
+
+__all__ = ["time_based_split"]