341 lines
12 KiB
Python
341 lines
12 KiB
Python
"""
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山寨币监控 — 数据库层
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全量记录筛选结果 + 价格跟踪 + 盈亏验证
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"""
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import json
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from datetime import datetime, timedelta
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from app.config.config_loader import get_meta
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from app.db import recommendation_commands as _recommendation_commands
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from app.db.coin_state_queries import expire_old_states, get_all_active, update_state
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from app.db.cron_queries import get_cron_run_logs, get_cron_run_summary, log_cron_run
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from app.db.postgres_connection import apply_migrations, connect as pg_connect
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from app.db.recommendation_state import (
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classify_recommendation_result as _classify_recommendation_result,
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derive_execution_fields as _derive_execution_fields,
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is_actionable_execution_status as _is_actionable_execution_status,
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is_executed_trade as _is_executed_trade,
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)
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from app.db.push_queries import PUSH_COOLDOWN_HOURS, get_recommendation_for_push, log_push, should_push
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from app.db.review_basic_queries import (
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get_signal_weights,
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record_missed_explosion,
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record_review,
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update_signal_performance,
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)
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from app.db.screening_queries import get_candidates_for_confirm, get_screening_history, log_screening
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from app.db.strategy_rule_queries import (
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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_iteration_dashboard,
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get_strategy_rule_candidates,
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record_strategy_failure_pattern,
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refresh_strategy_candidate_performance,
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update_strategy_rule_candidate_status,
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upsert_strategy_rule_candidate,
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)
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from app.db.strategy_insights import get_strategy_insights
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from app.db.tracking_queries import (
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get_latest_price_cache,
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update_entry_timing,
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update_latest_price_cache,
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update_recommendation_tracking,
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)
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def get_conn():
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return pg_connect()
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def init_db():
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apply_migrations()
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print("PostgreSQL schema migrations checked")
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def _sync_command_compat_hooks():
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"""Keep legacy altcoin_db monkeypatch hooks effective after command extraction."""
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_recommendation_commands.get_meta = get_meta
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_recommendation_commands.datetime = datetime
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def create_recommendation(*args, **kwargs):
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_sync_command_compat_hooks()
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return _recommendation_commands.create_recommendation(*args, **kwargs)
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def expire_old_recommendations(*args, **kwargs):
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_sync_command_compat_hooks()
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return _recommendation_commands.expire_old_recommendations(*args, **kwargs)
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def apply_recommendation_state_transition(*args, **kwargs):
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_sync_command_compat_hooks()
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return _recommendation_commands.apply_recommendation_state_transition(*args, **kwargs)
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def recompute_all_recommendation_state_fields(*args, **kwargs):
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_sync_command_compat_hooks()
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return _recommendation_commands.recompute_all_recommendation_state_fields(*args, **kwargs)
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def update_recommendation_action_status(*args, **kwargs):
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_sync_command_compat_hooks()
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return _recommendation_commands.update_recommendation_action_status(*args, **kwargs)
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# ==================== 查询API ====================
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def get_active_recommendations(actionable_only=False):
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"""获取所有active推荐。默认保留全量，实时页请使用去重视图的可执行口径。"""
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conn = get_conn()
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rows = conn.execute("""
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SELECT * FROM recommendation
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WHERE status='active' AND COALESCE(display_bucket,'watch_pool') != 'history'
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ORDER BY rec_time DESC
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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 = _derive_execution_fields(dict(row))
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if actionable_only and not _is_actionable_execution_status(item.get("execution_status")):
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continue
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result.append(item)
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return result
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def get_active_recommendations_deduped(actionable_only=True, version="", hours=0, watch_symbols=None, limit=0, offset=0, with_meta=False):
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"""获取去重后的active推荐（同symbol只保留最新一条），并附带推荐结果判定。
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version 为空时不按版本过滤；hours>0 时只取最近 N 小时信号。
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with_meta=True 时返回分页对象，兼容实时看板首屏分页加载。"""
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conn = get_conn()
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where = "status='active' AND COALESCE(display_bucket,'watch_pool') != 'history'"
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params = []
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version = str(version or "").strip()
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if version:
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where += " AND strategy_version=%s"
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params.append(version)
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if watch_symbols:
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symbols = [str(s).strip().upper() for s in watch_symbols if str(s).strip()]
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if symbols:
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where += " AND symbol IN (" + ",".join(["%s"] * len(symbols)) + ")"
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params.extend(symbols)
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try:
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hours = float(hours or 0)
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except Exception:
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hours = 0
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if hours > 0:
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cutoff = (datetime.now() - timedelta(hours=hours)).isoformat()
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where += " AND rec_time >= %s"
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params.append(cutoff)
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try:
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limit = max(0, int(limit or 0))
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except Exception:
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limit = 0
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try:
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offset = max(0, int(offset or 0))
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except Exception:
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offset = 0
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rows = conn.execute(f"""
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SELECT r.*,
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lpc.price AS latest_cache_price,
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lpc.updated_at AS latest_cache_updated_at
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FROM recommendation r
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LEFT JOIN latest_price_cache lpc ON lpc.symbol = r.symbol
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JOIN (
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SELECT symbol, MAX(id) AS max_id
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FROM recommendation
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WHERE {where}
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GROUP BY symbol
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) latest ON latest.max_id = r.id
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ORDER BY r.rec_time DESC
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""", tuple(params)).fetchall()
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conn.close()
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all_items = []
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# 实时看板只输出当前有效机会；过期/失效样本属于历史/复盘，不再进入实时列表或 summary。
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summary = {
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"buy_now": 0,
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"wait_pullback": 0,
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"observe": 0,
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"observe_strong": 0,
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"observe_weak": 0,
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"expired": 0,
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"total": 0,
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"discovery_burst": 0,
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"executable_now": 0,
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"planned_entry": 0,
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"watch_pool": 0,
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}
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now = datetime.now()
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for row in rows:
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item = dict(row)
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rec_result, rec_result_label = _classify_recommendation_result(item)
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item["recommendation_result"] = rec_result
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item["recommendation_result_label"] = rec_result_label
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_derive_execution_fields(item)
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is_expired = False
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if hours > 0:
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try:
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rec_time = item.get("rec_time")
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if rec_time:
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is_expired = (now - datetime.fromisoformat(str(rec_time))).total_seconds() > hours * 3600
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except Exception:
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is_expired = False
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if item.get("execution_status") == "invalid" or item.get("status") in ("invalid", "expired", "archived") or item.get("display_bucket") == "history":
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is_expired = True
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# 带 hours 的实时看板请求必须过滤旧/脏/过期；不带 hours 的内部/测试查询保留全量派生结果。
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if is_expired:
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summary["expired"] += 1
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continue
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if actionable_only and not _is_actionable_execution_status(item.get("execution_status")):
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continue
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all_items.append(item)
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if item.get("is_discovery_burst"):
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summary["discovery_burst"] += 1
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if item.get("is_executable_now"):
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summary["executable_now"] += 1
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if item.get("execution_status") == "wait_pullback":
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summary["planned_entry"] += 1
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if item.get("is_watch_pool"):
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summary["watch_pool"] += 1
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if item.get("execution_status") == "buy_now":
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summary["buy_now"] += 1
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elif item.get("execution_status") == "wait_pullback":
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summary["wait_pullback"] += 1
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else:
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summary["observe"] += 1
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if item.get("observe_tier") == "weak":
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summary["observe_weak"] += 1
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else:
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summary["observe_strong"] += 1
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summary["total"] = len(all_items)
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# expired 仅作内部审计计数，不属于实时机会流；API 对外不暴露，避免前端/用户继续看到过期入口。
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summary["expired_filtered"] = summary.pop("expired", 0)
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if not with_meta:
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try:
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from app.services.llm_insights import attach_recommendation_insights
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return attach_recommendation_insights(all_items)
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except Exception:
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return all_items
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page_items = all_items[offset: offset + limit] if limit else all_items[offset:]
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try:
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from app.services.llm_insights import attach_recommendation_insights
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attach_recommendation_insights(page_items)
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except Exception:
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pass
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return {
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"items": page_items,
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"total": len(all_items),
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"limit": limit,
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"offset": offset,
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"has_more": bool(limit and offset + len(page_items) < len(all_items)),
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"summary": summary,
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}
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def get_all_recommendations(limit=50, decision_only=False, version="", offset=0, with_meta=False):
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"""兼容导出：推荐列表查询已迁移到 analytics 模块。"""
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from app.db.analytics import get_all_recommendations as _get_all_recommendations
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return _get_all_recommendations(
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limit=limit,
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decision_only=decision_only,
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version=version,
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offset=offset,
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with_meta=with_meta,
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)
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def get_stats():
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"""兼容导出：统计聚合已迁移到 analytics 模块。"""
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from app.db.analytics import get_stats as _get_stats
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return _get_stats()
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def get_review_stats():
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"""兼容导出：复盘统计已迁移到 analytics 模块。"""
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from app.db.analytics import get_review_stats as _get_review_stats
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return _get_review_stats(
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conn_provider=get_conn,
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iteration_logs_getter=get_strategy_iteration_logs,
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iteration_summary_getter=get_strategy_iteration_summary,
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)
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def _loads_json_field(value, fallback):
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try:
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return json.loads(value) if isinstance(value, str) else (value if value is not None else fallback)
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except Exception:
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return fallback
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def log_strategy_iteration(run_date=None, trigger_source="daily_review", title="", summary="",
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findings=None, problems=None, actions=None, changed_rules=None,
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metrics=None, related_symbols=None, config_diff=None, effect_summary=None,
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pollution_summary=None,
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strategy_version="", version_change_summary="",
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success_analysis=None, failure_analysis=None, candidate_rules=None,
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release_decision="", release_reason="", confidence_level="",
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promotion_state="research_only"):
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"""兼容导出：策略迭代写入已迁移到 review_queries 模块。"""
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from app.db.review_queries import log_strategy_iteration as _log_strategy_iteration
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return _log_strategy_iteration(
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run_date=run_date,
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trigger_source=trigger_source,
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title=title,
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summary=summary,
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findings=findings,
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problems=problems,
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actions=actions,
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changed_rules=changed_rules,
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metrics=metrics,
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related_symbols=related_symbols,
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config_diff=config_diff,
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effect_summary=effect_summary,
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pollution_summary=pollution_summary,
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strategy_version=strategy_version,
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version_change_summary=version_change_summary,
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success_analysis=success_analysis,
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failure_analysis=failure_analysis,
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candidate_rules=candidate_rules,
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release_decision=release_decision,
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release_reason=release_reason,
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confidence_level=confidence_level,
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promotion_state=promotion_state,
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conn_provider=get_conn,
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)
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def get_strategy_iteration_logs(limit=30):
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"""兼容导出：策略迭代日志查询已迁移到 review_queries 模块。"""
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from app.db.review_queries import get_strategy_iteration_logs as _get_strategy_iteration_logs
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return _get_strategy_iteration_logs(limit=limit, conn_provider=get_conn, json_loader=_loads_json_field)
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def get_strategy_iteration_summary(days=30):
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"""兼容导出：策略迭代汇总已迁移到 review_queries 模块。"""
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from app.db.review_queries import get_strategy_iteration_summary as _get_strategy_iteration_summary
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return _get_strategy_iteration_summary(days=days, conn_provider=get_conn, json_loader=_loads_json_field)
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if __name__ == "__main__":
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init_db()
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stats = get_stats()
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print(f"DB初始化完成: {stats}")
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