refactor: 프로젝트명 bithumb으로 변경 및 futures 파이프라인 제거

deepcoin 패키지를 bithumb으로 rename하고, 3단계 live 운영·사이징 튜닝·텔레그램 알림을 통합한다.

Co-authored-by: Cursor <cursoragent@cursor.com>

scripts/1_tune_order_sizing.py

@@ -0,0 +1,96 @@
+#!/usr/bin/env python3
+"""1단계: 연속 매수·매도 클러스터별 매수·매도 비율 튜닝 (타점 고정)."""
+
+from __future__ import annotations
+
+import argparse
+import json
+import logging
+import sys
+from pathlib import Path
+
+ROOT = Path(__file__).resolve().parents[1]
+SRC = ROOT / "src"
+if str(SRC) not in sys.path:
+    sys.path.insert(0, str(SRC))
+
+from bithumb.config import load_settings
+from bithumb.ground_truth.sizing_rules import save_sizing_rules
+from bithumb.ground_truth.sizing_tune import tune_sizing_rules
+from bithumb.operations.signal_pipeline import run_signal_pipeline
+
+
+def _configure_logging(verbose: bool) -> None:
+    level = logging.DEBUG if verbose else logging.INFO
+    logging.basicConfig(
+        level=level,
+        format="%(asctime)s [%(levelname)s] %(message)s",
+        datefmt="%Y-%m-%d %H:%M:%S",
+    )
+
+
+def main() -> int:
+    """CLI 진입점."""
+    parser = argparse.ArgumentParser(
+        description="연속 매수·매도 클러스터 상태별 사이징 비율 학습",
+    )
+    parser.add_argument(
+        "-o",
+        "--output",
+        type=str,
+        default=None,
+        help="규칙 JSON 경로 (기본: OPS_SIZING_RULES_JSON)",
+    )
+    parser.add_argument(
+        "--min-bucket-samples",
+        type=int,
+        default=5,
+        help="클러스터 버킷별 최소 샘플 수",
+    )
+    parser.add_argument("-v", "--verbose", action="store_true")
+    args = parser.parse_args()
+    _configure_logging(args.verbose)
+
+    settings = load_settings()
+    output_path = Path(args.output) if args.output else settings.ops_sizing_rules_json
+    if not output_path.is_absolute():
+        output_path = ROOT / output_path
+
+    print("\n=== 매수·매도 비율 튜닝 (타점 고정) ===", flush=True)
+    print(
+        f"기법: {settings.ops_technique_id} · sim {settings.gt_sim_lookback_days}일 · "
+        f"기본 {settings.ops_buy_cash_pct:.0%}/{settings.ops_sell_coin_pct:.0%}",
+        flush=True,
+    )
+
+    pipeline = run_signal_pipeline(settings, use_cache=True)
+    rules, final_sim = tune_sizing_rules(
+        settings,
+        pipeline["kept"],
+        data_end=pipeline["data_end"],
+        last_mark_price=pipeline["last_price"],
+        technique_id=pipeline["technique_id"],
+        min_bucket_samples=args.min_bucket_samples,
+    )
+    save_sizing_rules(rules, output_path)
+
+    tuning = rules.get("tuning") or {}
+    print(f"\n기준(고정 10%): {tuning.get('baseline_return_pct'):+.2f}%")
+    print(
+        f"학습 후: {final_sim.get('total_return_pct'):+.2f}% · "
+        f"매수/매도 {final_sim.get('buys_executed')}/{final_sim.get('sells_executed')}"
+    )
+    print(
+        f"전역 비율: 매수 {rules.get('default_buy_cash_pct', 0):.0%} · "
+        f"매도 {rules.get('default_sell_coin_pct', 0):.0%}"
+    )
+    by_cluster = rules.get("by_cluster") or {}
+    if by_cluster.get("buy") or by_cluster.get("sell"):
+        print("클러스터별:")
+        print(json.dumps(by_cluster, ensure_ascii=False, indent=2))
+    print(f"\n규칙 JSON: {output_path}")
+    return 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())