d7848df6f7
Phase C/dry-run·미사용 모듈·재생성 HTML을 제거하고, 운영 체결을 sim_causal_hybrid와 동일한 hybrid 로직으로 통합한다. Co-authored-by: Cursor <cursoragent@cursor.com>
149 lines
5.1 KiB
Python
149 lines
5.1 KiB
Python
"""
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general_analysis 봉 데이터 전구간 enrich + 최신봉·기법 점검 리포트.
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python scripts/03_analyze_enrich.py
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python scripts/03_analyze_enrich.py --interval 1440
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"""
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from __future__ import annotations
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import argparse
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from pathlib import Path
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import pandas as pd
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from config import CHART_LOOKBACK_DAYS, GA_DEFAULT_TAIL_EXPORT, SYMBOL
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from deepcoin.analysis.general_analysis_align import (
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general_analysis_mtf_scores,
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general_analysis_mtf_vote_latest,
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)
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from deepcoin.analysis.general_analysis_config import (
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DEFAULT_CAPABILITY_HTML,
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DEFAULT_LATEST_DIR,
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GENERAL_ANALYSIS_INTERVALS,
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)
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from deepcoin.analysis.general_analysis_core import ga_col, interval_tf_prefix
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from deepcoin.analysis.general_analysis_pipeline import general_analysis_enrich_bars
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from deepcoin.ops.monitor import Monitor
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from deepcoin.data.mtf_bb import load_frames_from_db
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def _latest_row_summary(df: pd.DataFrame, prefix: str) -> dict[str, object]:
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"""최신 봉의 ga_·핵심 레거시 컬럼 요약."""
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if df.empty:
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return {}
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row = df.iloc[-1]
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out: dict[str, object] = {"dt": str(df.index[-1]), "tf": prefix}
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for c in df.columns:
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if c.startswith("ga_") or c in ("RSI", "bb_pos", "macd_hist", "stoch_k"):
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v = row[c]
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if pd.isna(v):
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continue
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out[c] = v
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return out
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def write_capability_html(
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summaries: dict[str, dict[str, object]],
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vote: dict[str, object],
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path: Path,
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) -> None:
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"""기법 컬럼 존재 여부·최신값 요약 HTML."""
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rows = ""
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for tf, snap in summaries.items():
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ga_cols = [k for k in snap if str(k).startswith("ga_")]
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rows += f"<tr><td>{tf}</td><td>{snap.get('dt','')}</td><td>{len(ga_cols)}</td></tr>"
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vote_rows = "".join(f"<li><code>{k}</code>: {v}</li>" for k, v in vote.items())
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html = f"""<!DOCTYPE html>
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<html lang="ko"><head><meta charset="utf-8"/>
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<title>general_analysis 기법 점검</title>
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<style>
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body {{ font-family: "Malgun Gothic", Arial, sans-serif; margin: 24px; background: #f5f5f5; }}
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table {{ border-collapse: collapse; width: 100%; background: #fff; }}
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th, td {{ border: 1px solid #e2e8f0; padding: 8px; font-size: 0.88rem; }}
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th {{ background: #e2e8f0; }}
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</style></head><body>
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<h1>general_analysis 기법 점검 ({SYMBOL})</h1>
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<p>3분~일봉 enrich 완료. 최신 봉 기준 컬럼 수·MTF 투표.</p>
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<h2>간격별 ga_ 컬럼 수</h2>
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<table><thead><tr><th>TF</th><th>최신 시각</th><th>ga_ 컬럼 수</th></tr></thead>
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<tbody>{rows}</tbody></table>
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<h2>MTF 투표 (최신 봉)</h2>
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<ul>{vote_rows}</ul>
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<p>상세 CSV: <code>{DEFAULT_LATEST_DIR}/</code></p>
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</body></html>"""
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path.parent.mkdir(parents=True, exist_ok=True)
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path.write_text(html, encoding="utf-8")
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def main() -> None:
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parser = argparse.ArgumentParser(description="general_analysis 8TF enrich")
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parser.add_argument("--interval", type=int, default=0, help="단일 간격만 (0=전체)")
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parser.add_argument(
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"--tail-export",
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type=int,
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default=GA_DEFAULT_TAIL_EXPORT,
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help="CSV 저장 최근 N봉",
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)
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args = parser.parse_args()
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from deepcoin.paths import ANALYSIS_CAPABILITY_HTML, ANALYSIS_LATEST_DIR
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intervals = (
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(args.interval,)
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if args.interval > 0
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else GENERAL_ANALYSIS_INTERVALS
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)
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print(f"=== general_analysis enrich {SYMBOL} ===")
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mon = Monitor(cooldown_file=None)
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frames = load_frames_from_db(mon, SYMBOL, lookback_days=CHART_LOOKBACK_DAYS)
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if not frames:
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raise RuntimeError("coins.db 데이터 없음")
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enriched: dict[int, pd.DataFrame] = {}
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summaries: dict[str, dict[str, object]] = {}
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out_dir = ANALYSIS_LATEST_DIR
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out_dir.mkdir(parents=True, exist_ok=True)
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for iv in intervals:
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raw = frames.get(iv)
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if raw is None or raw.empty:
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print(f" skip {iv}: no data")
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continue
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p = interval_tf_prefix(iv)
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print(f" [{p}] enrich {len(raw)} bars...")
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ef = general_analysis_enrich_bars(raw, iv, full_context=True)
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enriched[iv] = ef
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tail = ef.tail(args.tail_export)
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csv_path = out_dir / f"{p}_latest.csv"
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tail.to_csv(csv_path, encoding="utf-8-sig")
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print(f" -> {csv_path} ({len(tail)} rows x {len(tail.columns)} cols)")
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summaries[p] = _latest_row_summary(ef, p)
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flat_vote: dict[str, object] = {}
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if len(enriched) >= 2:
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for k, v in general_analysis_mtf_vote_latest(enriched).items():
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flat_vote[ga_col(k)] = v
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prefixed = {}
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for iv, ef in enriched.items():
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p = interval_tf_prefix(iv)
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row = ef.iloc[-1]
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for c in ("RSI", "bb_pos"):
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if c in row.index:
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prefixed[f"{p}_{c}"] = row[c]
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st = row.get(ga_col("struct_trend"))
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if st is not None:
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prefixed[f"{p}_{ga_col('struct_trend')}"] = st
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flat_vote.update(general_analysis_mtf_scores(prefixed))
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write_capability_html(summaries, flat_vote, ANALYSIS_CAPABILITY_HTML)
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print(f"점검 리포트: {ANALYSIS_CAPABILITY_HTML}")
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print("완료.")
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if __name__ == "__main__":
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main()
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