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feat: Implement backtest source management and enhance candle data handling

Changes:
- Introduced a new function `_apply_backtest_source_env_from_request` to manage the environment variables for candle, tick, and order book sources based on incoming requests.
- Added a teardown function `_teardown_backtest_source_env` to ensure that environment variables do not persist between requests, enhancing the stability of the backtesting environment.
- Refactored existing code to utilize the new source management functions, improving code readability and maintainability.
- Added new utility functions in `bt_candle_source.py` for fetching and managing candle data, ensuring consistency with live trading data sources.

Impact:
- These changes improve the flexibility and reliability of the backtesting framework, allowing for better management of data sources and reducing the risk of cross-request contamination.

kis_trader/backtest/breakout_backtest_common.py

@@ -283,6 +283,7 @@ def prepend_breakout_candle_warmup(
     ps = str(period_start_key)[:12]
     ind_cols = ws_candles_select_indicator_cols(db)
     total_prepended = 0
+    from kis_trader.backtest.bt_candle_source import fetch_ws_candles_warmup_before
     for code, rows in list(candles_by_code.items()):
         if not rows:
             continue
@@ -299,15 +300,13 @@ def prepend_breakout_candle_warmup(
         first_ct = str(rows[first_period_idx].get("candle_time") or "")
         if not first_ct:
             continue
-        warm_rows = db.conn.execute(
-            f"SELECT candle_time, open, high, low, close, volume, is_confirmed{ind_cols} "
-            "FROM ws_candles WHERE timeframe=1 AND code=%s "
-            "AND candle_time < %s ORDER BY candle_time DESC LIMIT %s",
-            [code, first_ct, wb],
-        ).fetchall()
+        warm_rows = fetch_ws_candles_warmup_before(
+            db, code, 1, first_ct, wb,
+            extra_select=ind_cols,
+        )
         if not warm_rows:
             continue
-        prefix = [dict(r) for r in reversed(warm_rows)]
+        prefix = warm_rows
         candles_by_code[code] = prefix + [dict(r) for r in rows]
         total_prepended += len(prefix)
     if total_prepended > 0:
@@ -380,30 +379,26 @@ def load_breakout_candles_by_code(
             db, start_key, end_key, min_bars=min_bars,
         )
 
-    candle_src = os.environ.get("CANDLE_SOURCE", "kis") or "kis"
-    
+    from kis_trader.backtest.bt_candle_source import (
+        fetch_ws_candles_for_code,
+        list_ws_candle_codes,
+    )
+
     ind_cols = ws_candles_select_indicator_cols(db)
-    codes_raw = db.conn.execute(
-        "SELECT DISTINCT code FROM ws_candles WHERE timeframe=1 "
-        "AND candle_time >= %s AND candle_time <= %s ORDER BY code",
-        [start_key, end_key],
-    ).fetchall()
-    codes = [r["code"] for r in codes_raw]
+    codes = list_ws_candle_codes(db, 1, start_key, end_key)
 
     candles_by_code: Dict[str, List[Dict]] = {}
     total_candles = 0
 
     for code in codes:
-        rows = db.conn.execute(
-            f"SELECT candle_time, open, high, low, close, volume {ind_cols} "
-            f"FROM ws_candles WHERE timeframe=1 AND code=%s "
-            f"AND candle_time >= %s AND candle_time <= %s AND is_confirmed=1 "
-            f"ORDER BY candle_time ASC",
-            [code, start_key, end_key],
-        ).fetchall()
+        rows = fetch_ws_candles_for_code(
+            db, code, 1, start_key, end_key,
+            extra_select=ind_cols,
+            confirmed_only=True,
+        )
         if len(rows) < min_bars:
             continue
-        candles_by_code[code] = [dict(r) for r in rows]
+        candles_by_code[code] = rows
         total_candles += len(rows)
 
     materialize_ws_candles_batch(db, candles_by_code, 1)