From 6de29ed2e1a892f7649d2a692b8b807ad5744f31 Mon Sep 17 00:00:00 2001 From: "2569718930@qq.com" <2569718930@qq.com> Date: Mon, 25 May 2026 03:52:07 +0800 Subject: [PATCH] =?UTF-8?q?=E6=B8=85=E7=90=86=E8=B0=83=E8=AF=95=E6=97=A5?= =?UTF-8?q?=E5=BF=97=EF=BC=9A=E7=A7=BB=E9=99=A4=20BIAS=5FDEBUG/SCAN=5FDEBU?= =?UTF-8?q?G=20=E4=B8=B4=E6=97=B6=E6=97=A5=E5=BF=97=EF=BC=8C=E4=BF=9D?= =?UTF-8?q?=E7=95=99=E6=A0=B8=E5=BF=83=E4=BF=AE=E6=AD=A3=E9=80=BB=E8=BE=91?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- src/data_collection/polymarket_readonly.py | 45 ++++++---------------- web/analysis_service.py | 10 ----- 2 files changed, 12 insertions(+), 43 deletions(-) diff --git a/src/data_collection/polymarket_readonly.py b/src/data_collection/polymarket_readonly.py index b12c0fca..e872edab 100644 --- a/src/data_collection/polymarket_readonly.py +++ b/src/data_collection/polymarket_readonly.py @@ -3015,7 +3015,6 @@ class PolymarketReadOnlyLayer: target_date=target_date, primary_market=primary_market, ) - logger.info("SCAN_DEBUG city={} date={} related_markets={}", city_key, target_date, len(related_markets)) if not related_markets: return { "rows": [], @@ -3090,10 +3089,6 @@ class PolymarketReadOnlyLayer: ) broad_quotes = self._batch_get_token_market_data(token_ids, include_books=False) - logger.info( - "SCAN_DEBUG city={} date={} token_ids={} broad_quotes={} entries={}", - city_key, target_date, len(token_ids), len(broad_quotes), len(market_entries), - ) bias_inputs: List[Tuple[float, float]] = [] for entry in market_entries: yes_quote = self._merge_market_quote_fallback( @@ -3351,14 +3346,6 @@ class PolymarketReadOnlyLayer: ask = _clamp_probability(_safe_float(entry.get("yes_ask") if side == "yes" else entry.get("no_ask"))) bid = _clamp_probability(_safe_float(entry.get("yes_bid") if side == "yes" else entry.get("no_bid"))) if model_event_probability is None or ask is None: - logger.info( - "SCAN_DEBUG row_skip city={} date={} side={} model_p={} ask={} bid={} " - "yes_ask={} no_ask={} slug={}", - city_key, target_date, side, - model_event_probability, ask, bid, - entry.get("yes_ask"), entry.get("no_ask"), - str(entry.get("market", {}).get("slug") or "")[:60], - ) return None market = entry["market"] @@ -3682,23 +3669,19 @@ class PolymarketReadOnlyLayer: _safe_float(row.get("book_liquidity")) or 0.0, _safe_float(row.get("market_liquidity")) or 0.0, ) - _reason = None if ask is None or edge_percent is None: - _reason = f"ask_or_edge_none ask={ask} edge={edge_percent}" - elif not row.get("tradable") or row.get("accepting_orders") is False: - _reason = f"not_tradable tradable={row.get('tradable')} accepting={row.get('accepting_orders')}" - elif row.get("enable_order_book") is False: - _reason = "order_book_disabled" - elif ask < filters["min_price"] or ask > filters["max_price"]: - _reason = f"price_range ask={ask} min={filters['min_price']} max={filters['max_price']}" - elif abs(edge_percent) < filters["min_edge_pct"]: - _reason = f"edge_too_low edge={edge_percent} min={filters['min_edge_pct']}" - elif spread is not None and spread > filters["max_spread"]: - _reason = f"spread_too_wide spread={spread} max={filters['max_spread']}" - elif liquidity < filters["min_liquidity"]: - _reason = f"liquidity_too_low liq={liquidity} min={filters['min_liquidity']}" - if _reason: - logger.info("SCAN_DEBUG filter_skip slug={} side={} reason={}", str(row.get("market_slug") or "")[:60], row.get("side"), _reason) + return False + if not row.get("tradable") or row.get("accepting_orders") is False: + return False + if row.get("enable_order_book") is False: + return False + if ask < filters["min_price"] or ask > filters["max_price"]: + return False + if abs(edge_percent) < filters["min_edge_pct"]: + return False + if spread is not None and spread > filters["max_spread"]: + return False + if liquidity < filters["min_liquidity"]: return False side = str(row.get("side") or "").lower() @@ -3754,10 +3737,6 @@ class PolymarketReadOnlyLayer: primary_signal = filtered_rows[0] if filtered_rows else None signal_status = "ready" if primary_signal else "no_signal" - logger.info( - "SCAN_DEBUG result city={} date={} preliminary={} final={} filtered={} signal={}", - city_key, target_date, len(preliminary_rows), len(final_rows), len(filtered_rows), signal_status, - ) return { "rows": filtered_rows[: filters["limit"]], "distribution_bias": distribution_bias, diff --git a/web/analysis_service.py b/web/analysis_service.py index adb1ea31..c23eaab5 100644 --- a/web/analysis_service.py +++ b/web/analysis_service.py @@ -1500,10 +1500,6 @@ def _analyze( peak_first = int(first_peak_h or 14) peak_last_h = int(last_peak_h or 17) - logger.info( - "BIAS_PRE city={} deb_val={} cur_temp={} max_so_far={} local_hour={}", - city, deb_val, cur_temp, max_so_far, _local_hour, - ) if ( deb_val is not None and cur_temp is not None @@ -1541,12 +1537,6 @@ def _analyze( max_correction_clamped = max(-max_correction, min(max_correction, max_so_far_excess * max(0.3, weight))) blended_correction = hourly_correction * 0.6 + max_correction_clamped * 0.4 - logger.info( - "BIAS_DEBUG city={} hour={} current={} model_hourly={} hourly_bias={:.1f} " - "max_excess={:.1f} weight={:.2f} correction={:.1f} deb_before={}", - city, _local_hour, cur_temp, model_hourly_temp, hourly_bias, - _msf - deb_val, weight, blended_correction, deb_val, - ) deb_val = round(deb_val + blended_correction, 1) if mu is not None: mu = round(mu + blended_correction, 1)