enhance validation ranges and improve news processing with GDELT support

app/features/validation.py

@@ -24,8 +24,8 @@ FACTOR_LIMITS = {
     # 估值评分类因子：标准化评分，限制在 -3到3 (Z-score标准化范围)
     "val_": (-3.0, 3.0),
     
-    # 量价类因子：成交量比率，限制在 0-10倍
+    # 量价类因子：成交量比率，允许 -1 到 10（考虑相关性类因子）
-    "volume_": (0, 10.0),
+    "volume_": (-1.0, 10.0),
     "volume_ratio": (0, 10.0),
     
     # 市场状态类因子：标准化状态指标，限制在 -3到3
@@ -52,8 +52,8 @@ FACTOR_LIMITS = {
     # 风险类因子：风险惩罚因子
     "risk_": (0, 1.0),
     
-    # 价格比率类因子：价格与均线比率，限制在 0.5-2.0 (50%-200%)
+    # 价格比率类因子：价格与均线比率，扩大到 0.2-5.0 以涵盖极端波动
-    "price_ma_": (0.5, 2.0),
+    "price_ma_": (0.2, 5.0),
     
     # 成交量比率类因子：成交量与均线比率，限制在 0.1-10.0
     "volume_ma_": (0.1, 10.0),
@@ -97,7 +97,7 @@ def validate_factor_value(
     exact_matches = {
         # 技术指标精确范围
         "tech_rsi_14": (0, 100.0),           # RSI指标范围 0-100
-        "tech_macd_signal": (-5, 5),     # MACD信号范围
+        "tech_macd_signal": (-20, 20),     # MACD信号范围（扩大以适配极端行情）
         "tech_bb_position": (-3.0, 3.0),     # 布林带位置，标准差倍数
         "tech_obv_momentum": (-10.0, 10.0),  # OBV动量标准化
         "tech_pv_trend": (-1.0, 1.0),       # 量价趋势相关性
@@ -108,8 +108,8 @@ def validate_factor_value(
         "trend_price_channel": (-1.0, 1.0),     # 价格通道位置
         
         # 波动率指标精确范围
-        "vol_garch": (0, 50),               # GARCH波动率预测，限制在50%以内
+        "vol_garch": (0, 400),               # GARCH波动率预测，限制在更宽范围
-        "vol_range_pred": (0, 20),          # 波动率范围预测，限制在20%以内
+        "vol_range_pred": (0, 100),          # 波动率范围预测
         "vol_regime": (0, 1.0),              # 波动率状态，0-1之间
         
         # 微观结构精确范围
@@ -120,6 +120,7 @@ def validate_factor_value(
         "sent_impact": (0, 1.0),             # 情绪影响度
         "sent_divergence": (-1.0, 1.0),      # 情绪分歧度
         "volume_price_diverge": (-1.0, 1.0), # 量价背离度
+        "volume_price_corr": (-1.0, 1.0),    # 量价相关性
     }
     
     # 检查精确匹配
@@ -127,26 +128,26 @@ def validate_factor_value(
         min_val, max_val = exact_matches[name]
         if min_val <= value <= max_val:
             return value
-        else:
+        clipped = max(min(value, max_val), min_val)
-            LOGGER.warning(
+        LOGGER.warning(
-                "因子值超出精确范围 factor=%s value=%f range=[%f,%f] ts_code=%s date=%s",
+            "因子值超出精确范围 factor=%s value=%f range=[%f,%f] ts_code=%s date=%s -> clipped=%f",
-                name, value, min_val, max_val, ts_code, trade_date,
+            name, value, min_val, max_val, ts_code, trade_date, clipped,
-                extra=LOG_EXTRA
+            extra=LOG_EXTRA,
-            )
+        )
-            return None
+        return clipped
     
     # 检查前缀模式匹配
     for prefix, (min_val, max_val) in FACTOR_LIMITS.items():
         if name.startswith(prefix):
             if min_val <= value <= max_val:
                 return value
-            else:
+            clipped = max(min(value, max_val), min_val)
-                LOGGER.warning(
+            LOGGER.warning(
-                    "因子值超出前缀范围 factor=%s value=%f range=[%f,%f] ts_code=%s date=%s",
+                "因子值超出前缀范围 factor=%s value=%f range=[%f,%f] ts_code=%s date=%s -> clipped=%f",
-                    name, value, min_val, max_val, ts_code, trade_date,
+                name, value, min_val, max_val, ts_code, trade_date, clipped,
-                    extra=LOG_EXTRA
+                extra=LOG_EXTRA,
-                )
+            )
-                return None
+            return clipped
     
     # 如果没有匹配，使用更严格的默认范围
     default_min, default_max = -5.0, 5.0
@@ -157,13 +158,14 @@ def validate_factor_value(
             extra=LOG_EXTRA
         )
         return value
-    else:
+
-        LOGGER.warning(
+    clipped = max(min(value, default_max), default_min)
-            "因子值超出默认范围 factor=%s value=%f range=[%f,%f] ts_code=%s date=%s",
+    LOGGER.warning(
-            name, value, default_min, default_max, ts_code, trade_date,
+        "因子值超出默认范围 factor=%s value=%f range=[%f,%f] ts_code=%s date=%s -> clipped=%f",
-            extra=LOG_EXTRA
+        name, value, default_min, default_max, ts_code, trade_date, clipped,
-        )
+        extra=LOG_EXTRA,
-        return None
+    )
+    return clipped
 
 def detect_outliers(
     values: Dict[str, float],

app/ingest/coverage.py

@@ -209,6 +209,17 @@ def ensure_data_coverage(
             progress_hook(message, progress)
         LOGGER.info(message, extra=LOG_EXTRA)
 
+    if news_enabled:
+        advance("拉取 GDELT 新闻数据")
+        try:
+            ingest_configured_gdelt(
+                start=start,
+                end=end,
+                incremental=not force,
+            )
+        except Exception as exc:  # noqa: BLE001
+            LOGGER.warning("GDELT 新闻拉取失败：%s", exc, extra=LOG_EXTRA)
+
     advance("准备股票基础信息与交易日历")
     ensure_stock_basic()
     ensure_trade_calendar(start, end)
@@ -363,17 +374,6 @@ def ensure_data_coverage(
         _save_with_codes("hk_daily", fetch_hk_daily, targets=HK_CODES)
         _save_with_codes("us_daily", fetch_us_daily, targets=US_CODES)
 
-    if news_enabled:
-        advance("拉取 GDELT 新闻数据")
-        try:
-            ingest_configured_gdelt(
-                start=start,
-                end=end,
-                incremental=not force,
-            )
-        except Exception as exc:  # noqa: BLE001
-            LOGGER.warning("GDELT 新闻拉取失败：%s", exc, extra=LOG_EXTRA)
-
     if progress_hook:
         progress_hook("数据覆盖检查完成", 1.0)
 

app/ingest/gdelt.py

@@ -214,7 +214,7 @@ def _build_rss_item(record: Dict[str, object], config: GdeltSourceConfig) -> Opt
         source = config.label or "GDELT"
     source = source.strip()
 
-    fingerprint = f"{url}|{published.isoformat()}"
+    fingerprint = f"{url}|{published.isoformat()}|{config.key}"
     article_id = hashlib.blake2s(fingerprint.encode("utf-8"), digest_size=16).hexdigest()
 
     return rss_ingest.RssItem(
@@ -227,6 +227,7 @@ def _build_rss_item(record: Dict[str, object], config: GdeltSourceConfig) -> Opt
         metadata={
             "source_key": config.key,
             "source_label": config.label,
+            "source_type": "gdelt",
         },
     )
 
@@ -418,7 +419,10 @@ def ingest_configured_gdelt(
     fetched = 0
     for config in sources:
         source_start = start_dt
-        if incremental:
+        effective_incremental = incremental
+        if start_dt is not None or end_dt is not None:
+            effective_incremental = False
+        elif incremental:
             last_seen = _load_last_published(config.key)
             if last_seen:
                 candidate = last_seen + timedelta(seconds=1)
@@ -429,10 +433,21 @@ def ingest_configured_gdelt(
             config.label,
             source_start.isoformat() if source_start else None,
             end_dt.isoformat() if end_dt else None,
-            incremental,
+            effective_incremental,
             extra=LOG_EXTRA,
         )
-        items = fetch_gdelt_articles(config, start=source_start, end=end_dt)
+
+        items: List[rss_ingest.RssItem] = []
+        if source_start and end_dt and source_start <= end_dt:
+            chunk_start = source_start
+            while chunk_start <= end_dt:
+                chunk_end = min(chunk_start + timedelta(days=1) - timedelta(seconds=1), end_dt)
+                chunk_items = fetch_gdelt_articles(config, start=chunk_start, end=chunk_end)
+                if chunk_items:
+                    items.extend(chunk_items)
+                chunk_start = chunk_end + timedelta(seconds=1)
+        else:
+            items = fetch_gdelt_articles(config, start=source_start, end=end_dt)
         if not items:
             continue
         aggregated.extend(items)

app/ingest/rss.py

@@ -7,7 +7,7 @@ import sqlite3
 from dataclasses import dataclass, field, replace
 from datetime import datetime, timedelta, timezone
 from email.utils import parsedate_to_datetime
-from typing import Dict, Iterable, List, Optional, Sequence, Tuple
+from typing import Dict, Iterable, List, Optional, Sequence, Set, Tuple
 from urllib.parse import urlparse, urljoin
 from xml.etree import ElementTree as ET
 
@@ -472,31 +472,62 @@ def _fetch_feed_items(
     return items
 
 
-def deduplicate_items(items: Iterable[RssItem]) -> List[RssItem]:
+def _canonical_link(item: RssItem) -> str:
-    """Drop duplicate stories by link/id fingerprint and process entities."""
+    link = (item.link or "").strip().lower()
+    if link:
+        return link
+    if item.id:
+        return item.id
+    fingerprint = f"{item.title}|{item.published.isoformat() if item.published else ''}"
+    return hashlib.sha1(fingerprint.encode("utf-8")).hexdigest()
+
+
+def _is_gdelt_item(item: RssItem) -> bool:
+    metadata = item.metadata or {}
+    return metadata.get("source_type") == "gdelt" or bool(metadata.get("source_key"))
+
+
+def deduplicate_items(items: Iterable[RssItem]) -> List[RssItem]:
+    """Drop duplicate stories by canonical link while preferring GDELT sources."""
+
+    selected: Dict[str, RssItem] = {}
+    order: List[str] = []
 
-    seen = set()
-    unique: List[RssItem] = []
     for item in items:
-        key = item.id or item.link
-        if key in seen:
-            continue
-        seen.add(key)
         preassigned_codes = list(item.ts_codes or [])
         # 提取实体和相关信息
         item.extract_entities()
 
-        # 如果找到了相关股票，则保留这条新闻
+        keep = False
-        if item.stock_mentions:
+        if _is_gdelt_item(item):
-            unique.append(item)
+            keep = True
-            continue
+        elif item.stock_mentions:
-
+            keep = True
-        # 否则如果配置了预设股票代码，则保留这些代码
+        elif preassigned_codes:
-        if preassigned_codes:
             if not item.ts_codes:
                 item.ts_codes = preassigned_codes
-            unique.append(item)
+            keep = True
-    return unique
+
+        if not keep:
+            continue
+
+        key = _canonical_link(item)
+        existing = selected.get(key)
+        if existing is None:
+            selected[key] = item
+            order.append(key)
+            continue
+
+        if _is_gdelt_item(item) and not _is_gdelt_item(existing):
+            selected[key] = item
+        elif _is_gdelt_item(item) == _is_gdelt_item(existing):
+            if item.published and existing.published:
+                if item.published > existing.published:
+                    selected[key] = item
+            else:
+                selected[key] = item
+
+    return [selected[key] for key in order if key in selected]
 
 
 def save_news_items(items: Iterable[RssItem]) -> int:
@@ -507,6 +538,7 @@ def save_news_items(items: Iterable[RssItem]) -> int:
     rows: List[Tuple[object, ...]] = []
 
     processed = 0
+    gdelt_urls: Set[str] = set()
     for item in items:
         text_payload = f"{item.title}\n{item.summary}"
         sentiment = _estimate_sentiment(text_payload)
@@ -530,6 +562,8 @@ def save_news_items(items: Iterable[RssItem]) -> int:
         }
         if item.metadata:
             entity_payload["metadata"] = dict(item.metadata)
+            if _is_gdelt_item(item) and item.link:
+                gdelt_urls.add(item.link.strip())
         entities = json.dumps(entity_payload, ensure_ascii=False)
         resolved_codes = base_codes or (None,)
         for ts_code in resolved_codes:
@@ -556,9 +590,19 @@ def save_news_items(items: Iterable[RssItem]) -> int:
     inserted = 0
     try:
         with db_session() as conn:
+            if gdelt_urls:
+                conn.executemany(
+                    """
+                    DELETE FROM news
+                    WHERE url = ?
+                      AND (json_extract(entities, '$.metadata.source_type') IS NULL
+                           OR json_extract(entities, '$.metadata.source_type') != 'gdelt')
+                    """,
+                    [(url,) for url in gdelt_urls],
+                )
             conn.executemany(
                 """
-                INSERT OR IGNORE INTO news
+                INSERT OR REPLACE INTO news
                 (id, ts_code, pub_time, source, title, summary, url, entities, sentiment, heat)
                 VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
                 """,

app/ingest/tushare.py

@@ -5,7 +5,7 @@ from dataclasses import dataclass
 from datetime import date
 from typing import Callable, Iterable, List, Optional, Sequence
 
-from app.features.factors import compute_factor_range
+from app.features.factors import compute_factors_incremental
 from app.utils import alerts
 from app.utils.logging import get_logger
 
@@ -44,11 +44,10 @@ def _default_post_tasks(job: FetchJob) -> List[PostTask]:
 
 def _run_factor_backfill(job: FetchJob) -> None:
     LOGGER.info("开始计算因子：%s", job.name, extra=LOG_EXTRA)
-    compute_factor_range(
+    compute_factors_incremental(
-        job.start,
-        job.end,
         ts_codes=job.ts_codes,
-        skip_existing=False,
+        skip_existing=True,
+        persist=True,
     )
     alerts.clear_warnings("Factors")