320 lines
13 KiB
Python
320 lines
13 KiB
Python
"""Review and strategy iteration-facing DB API."""
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import json
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import re
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from datetime import datetime, timedelta
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from app.db.altcoin_db import (
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_loads_json_field,
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backfill_strategy_failure_patterns,
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dry_run_strategy_candidate_performance,
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generate_candidates_from_review_history,
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get_strategy_failure_patterns,
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get_strategy_insights,
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get_strategy_iteration_dashboard,
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get_strategy_rule_candidates,
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refresh_strategy_candidate_performance,
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)
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from app.db.schema import get_conn
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def log_strategy_iteration(
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run_date=None,
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trigger_source="daily_review",
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title="",
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summary="",
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findings=None,
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problems=None,
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actions=None,
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changed_rules=None,
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metrics=None,
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related_symbols=None,
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config_diff=None,
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effect_summary=None,
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pollution_summary=None,
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strategy_version="",
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version_change_summary="",
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success_analysis=None,
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failure_analysis=None,
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candidate_rules=None,
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release_decision="",
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release_reason="",
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confidence_level="",
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promotion_state="research_only",
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conn_provider=None,
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):
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"""记录一次策略复盘/迭代日志"""
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conn_factory = conn_provider or get_conn
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conn = conn_factory()
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now = datetime.now().isoformat()
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run_date = run_date or now[:10]
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conn.execute(
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"""
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INSERT INTO strategy_iteration_log (
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run_date, created_at, trigger_source, title, summary,
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findings_json, problems_json, actions_json, changed_rules_json,
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metrics_json, related_symbols_json, config_diff_json, effect_summary_json,
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pollution_summary_json,
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strategy_version, version_change_summary,
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success_analysis_json, failure_analysis_json, candidate_rules_json,
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release_decision, release_reason, confidence_level, promotion_state
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) VALUES (%s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s)
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""",
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(
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run_date,
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now,
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trigger_source or "daily_review",
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title or "未命名迭代",
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summary or "",
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json.dumps(findings or [], ensure_ascii=False, default=str),
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json.dumps(problems or [], ensure_ascii=False, default=str),
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json.dumps(actions or [], ensure_ascii=False, default=str),
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json.dumps(changed_rules or [], ensure_ascii=False, default=str),
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json.dumps(metrics or {}, ensure_ascii=False, default=str),
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json.dumps(related_symbols or [], ensure_ascii=False, default=str),
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json.dumps(config_diff or {}, ensure_ascii=False, default=str),
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json.dumps(effect_summary or {}, ensure_ascii=False, default=str),
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json.dumps(pollution_summary or {}, ensure_ascii=False, default=str),
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(strategy_version or "").strip(),
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(version_change_summary or "").strip(),
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json.dumps(success_analysis or {}, ensure_ascii=False, default=str),
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json.dumps(failure_analysis or {}, ensure_ascii=False, default=str),
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json.dumps(candidate_rules or [], ensure_ascii=False, default=str),
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(release_decision or "").strip(),
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(release_reason or "").strip(),
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(confidence_level or "").strip(),
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(promotion_state or "research_only").strip(),
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),
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)
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conn.commit()
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conn.close()
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def get_strategy_iteration_logs(limit=30, conn_provider=None, json_loader=None):
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conn_factory = conn_provider or get_conn
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loader = json_loader or _loads_json_field
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conn = conn_factory()
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rows = conn.execute(
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"""
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SELECT * FROM strategy_iteration_log
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ORDER BY created_at DESC, id DESC
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LIMIT %s
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""",
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(limit,),
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).fetchall()
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conn.close()
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result = []
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for row in rows:
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item = dict(row)
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item["findings"] = loader(item.get("findings_json"), [])
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item["problems"] = loader(item.get("problems_json"), [])
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item["actions"] = loader(item.get("actions_json"), [])
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item["changed_rules"] = loader(item.get("changed_rules_json"), [])
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item["metrics"] = loader(item.get("metrics_json"), {})
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item["related_symbols"] = loader(item.get("related_symbols_json"), [])
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item["config_diff"] = loader(item.get("config_diff_json"), {})
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item["effect_summary"] = loader(item.get("effect_summary_json"), {})
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item["pollution_summary"] = loader(item.get("pollution_summary_json"), {})
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item["success_analysis"] = loader(item.get("success_analysis_json"), {})
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item["failure_analysis"] = loader(item.get("failure_analysis_json"), {})
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item["candidate_rules"] = loader(item.get("candidate_rules_json"), [])
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item["release_decision"] = (item.get("release_decision") or "").strip()
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item["release_reason"] = (item.get("release_reason") or "").strip()
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item["confidence_level"] = (item.get("confidence_level") or "").strip()
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item["promotion_state"] = (item.get("promotion_state") or "research_only").strip()
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item["strategy_version"] = (item.get("strategy_version") or "").strip()
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item["version_change_summary"] = (item.get("version_change_summary") or "").strip()
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result.append(item)
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return result
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def get_strategy_iteration_summary(days=30, conn_provider=None, json_loader=None):
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conn_factory = conn_provider or get_conn
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loader = json_loader or _loads_json_field
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conn = conn_factory()
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cutoff = (datetime.now() - timedelta(days=float(days or 30))).isoformat()
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rows = conn.execute(
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"""
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SELECT * FROM strategy_iteration_log
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WHERE created_at >= %s
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ORDER BY created_at DESC, id DESC
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""",
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(cutoff,),
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).fetchall()
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rec_rows = conn.execute(
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"""
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SELECT strategy_version, status, pnl_pct, max_pnl_pct, max_drawdown_pct
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FROM recommendation
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WHERE strategy_version IS NOT NULL AND trim(strategy_version) != ''
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"""
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).fetchall()
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conn.close()
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def classify_recommendation_result(row):
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status = row.get("status") or ""
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pnl_pct = row.get("pnl_pct") or 0
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max_pnl_pct = row.get("max_pnl_pct") or 0
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max_drawdown_pct = row.get("max_drawdown_pct") or 0
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if status in ("hit_tp1", "hit_tp2"):
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return "success"
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if status == "stopped_out":
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return "failed"
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if status == "expired":
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if max_pnl_pct >= 5:
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return "success"
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if pnl_pct <= -3 or max_drawdown_pct <= -5:
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return "failed"
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return "pending"
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if status == "active":
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if max_pnl_pct >= 5:
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return "success"
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if pnl_pct <= -3 or max_drawdown_pct <= -5:
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return "failed"
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return "pending"
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return "pending"
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version_stats_map = {}
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for row in rec_rows:
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item = dict(row)
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strategy_version = (item.get("strategy_version") or "").strip()
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if not strategy_version:
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continue
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bucket = version_stats_map.setdefault(
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strategy_version,
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{
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"strategy_version": strategy_version,
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"recommendation_count": 0,
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"success_count": 0,
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"failed_count": 0,
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"pending_count": 0,
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"pnl_values": [],
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},
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)
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bucket["recommendation_count"] += 1
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bucket["pnl_values"].append(float(item.get("pnl_pct") or 0))
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outcome = classify_recommendation_result(item)
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if outcome == "success":
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bucket["success_count"] += 1
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elif outcome == "failed":
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bucket["failed_count"] += 1
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else:
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bucket["pending_count"] += 1
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logs = []
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trigger_counts = {}
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changed_rule_count = 0
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unique_days = set()
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titles = []
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problem_keywords = {}
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total_config_change_count = 0
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hit_rates = []
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avg_pnls = []
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version_changelog = []
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for row in rows:
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item = dict(row)
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item["findings"] = loader(item.get("findings_json"), [])
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item["problems"] = loader(item.get("problems_json"), [])
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item["actions"] = loader(item.get("actions_json"), [])
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item["changed_rules"] = loader(item.get("changed_rules_json"), [])
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item["metrics"] = loader(item.get("metrics_json"), {})
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item["related_symbols"] = loader(item.get("related_symbols_json"), [])
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item["config_diff"] = loader(item.get("config_diff_json"), {})
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item["effect_summary"] = loader(item.get("effect_summary_json"), {})
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item["pollution_summary"] = loader(item.get("pollution_summary_json"), {})
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item["success_analysis"] = loader(item.get("success_analysis_json"), {})
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item["failure_analysis"] = loader(item.get("failure_analysis_json"), {})
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item["candidate_rules"] = loader(item.get("candidate_rules_json"), [])
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item["release_decision"] = (item.get("release_decision") or "").strip()
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item["release_reason"] = (item.get("release_reason") or "").strip()
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item["confidence_level"] = (item.get("confidence_level") or "").strip()
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item["promotion_state"] = (item.get("promotion_state") or "research_only").strip()
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item["strategy_version"] = (item.get("strategy_version") or "").strip()
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item["version_change_summary"] = (item.get("version_change_summary") or "").strip()
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logs.append(item)
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unique_days.add(item.get("run_date") or (item.get("created_at") or "")[:10])
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trigger = item.get("trigger_source") or "unknown"
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trigger_counts[trigger] = trigger_counts.get(trigger, 0) + 1
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changed_rule_count += len(item.get("changed_rules") or [])
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if item.get("title"):
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titles.append(item["title"])
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for problem in item.get("problems") or []:
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key = str(problem).strip()
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if key:
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problem_keywords[key] = problem_keywords.get(key, 0) + 1
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diff = item.get("config_diff") or {}
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total_config_change_count += len(diff.get("changed") or []) + len(diff.get("added") or []) + len(diff.get("removed") or [])
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effect = item.get("effect_summary") or {}
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if isinstance(effect.get("hit_rate_pct"), (int, float)):
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hit_rates.append(effect.get("hit_rate_pct"))
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if isinstance(effect.get("avg_pnl"), (int, float)):
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avg_pnls.append(effect.get("avg_pnl"))
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if item.get("strategy_version"):
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version_changelog.append({
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"strategy_version": item.get("strategy_version"),
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"created_at": item.get("created_at"),
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"run_date": item.get("run_date"),
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"title": item.get("title") or "",
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"summary": item.get("summary") or "",
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"version_change_summary": item.get("version_change_summary") or "",
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"changed_rules_count": len(item.get("changed_rules") or []),
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"config_change_count": len(diff.get("changed") or []) + len(diff.get("added") or []) + len(diff.get("removed") or []),
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})
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top_problems = sorted(problem_keywords.items(), key=lambda x: (-x[1], x[0]))[:5]
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def _version_sort_key(version):
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nums = [int(x) for x in re.findall(r"\d+", str(version or ""))]
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return tuple(nums) if nums else (0,)
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version_stats = []
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for strategy_version, bucket in sorted(version_stats_map.items(), key=lambda kv: _version_sort_key(kv[0]), reverse=True):
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resolved = bucket["success_count"] + bucket["failed_count"]
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version_stats.append({
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"strategy_version": strategy_version,
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"recommendation_count": bucket["recommendation_count"],
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"success_count": bucket["success_count"],
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"failed_count": bucket["failed_count"],
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"pending_count": bucket["pending_count"],
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"success_rate_pct": round(bucket["success_count"] / resolved * 100, 1) if resolved else 0,
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"avg_pnl_pct": round(sum(bucket["pnl_values"]) / len(bucket["pnl_values"]), 2) if bucket["pnl_values"] else 0,
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})
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return {
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"days": days,
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"total_logs": len(logs),
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"unique_run_days": len(unique_days),
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"trigger_counts": trigger_counts,
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"change_rule_count": changed_rule_count,
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"config_change_count": total_config_change_count,
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"recent_titles": titles[:8],
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"top_problems": [{"problem": k, "count": v} for k, v in top_problems],
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"version_stats": version_stats,
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"version_changelog": version_changelog[:12],
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"effect_overview": {
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"avg_hit_rate_pct": round(sum(hit_rates) / len(hit_rates), 1) if hit_rates else 0,
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"avg_pnl": round(sum(avg_pnls) / len(avg_pnls), 2) if avg_pnls else 0,
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"samples": len(logs),
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},
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}
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__all__ = [
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"backfill_strategy_failure_patterns",
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"dry_run_strategy_candidate_performance",
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"generate_candidates_from_review_history",
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"get_strategy_failure_patterns",
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"get_strategy_insights",
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"get_strategy_iteration_dashboard",
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"get_strategy_iteration_logs",
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"get_strategy_iteration_summary",
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"get_strategy_rule_candidates",
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"log_strategy_iteration",
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"refresh_strategy_candidate_performance",
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]
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