Web 加上资金面/情绪叠图，并收紧默认图面。

默认主/次/次次改为 45m/15m/5m、开始时间一周；SD/CD 按 hist 摆位置和箭头；去掉笔线段背驰与第四类勾选。

Co-authored-by: Cursor <cursoragent@cursor.com>

web/services/runtime/__init__.py

@@ -54,6 +54,9 @@ from .market_data import (  # noqa: F401
 	get_crypto_kl_data,
 	get_a_stock_kl_data,
 	load_crypto_symbols,
+	fetch_derivatives,
+	fetch_sentiment_metrics,
+	fetch_sentiment_latest,
 )
 from .indicators import (  # noqa: F401
 	add_indicators,

web/services/runtime/market_data.py

@@ -319,3 +319,34 @@ def load_crypto_symbols(limit=200):
 	except Exception:
 		return DEFAULT_SYMBOLS[:limit]
 
+
+def _provider_get(path, params, timeout=8):
+	resp = requests.get(f"{DATA_SERVICE_URL}{path}", params=params, timeout=timeout)
+	resp.raise_for_status()
+	return resp.json()
+
+
+def fetch_derivatives(symbol, exchange=None):
+	"""当前资金面快照。只打 data_provider，不打交易所。"""
+	params = {"symbol": symbol}
+	if exchange:
+		params["exchange"] = exchange
+	return _provider_get("/api/derivatives", params)
+
+
+def fetch_sentiment_metrics(metric, symbol, start=None, end=None, limit=None):
+	"""情绪/资金面序列。只打 data_provider。"""
+	params = {"metric": metric, "symbol": symbol}
+	if start is not None:
+		params["start"] = int(start)
+	if end is not None:
+		params["end"] = int(end)
+	if limit is not None:
+		params["limit"] = int(limit)
+	return _provider_get("/api/sentiment/metrics", params)
+
+
+def fetch_sentiment_latest(symbol):
+	"""情绪面最新快照。只打 data_provider。"""
+	return _provider_get("/api/sentiment/latest", {"symbol": symbol})
+

web/services/runtime/state.py

@@ -46,6 +46,7 @@ DEFAULT_TIMEFRAME_LABELS = OrderedDict([
     ("5m", "5分钟"),
     ("15m", "15分钟"),
     ("30m", "30分钟"),
+    ("45m", "45分钟"),
     ("1h", "1小时"),
     ("2h", "2小时"),
     ("4h", "4小时"),

web/services/runtime/timeframes.py

@@ -94,19 +94,19 @@ def _prefer_smaller(candidates, labels_ordered, ceiling_tf, timeframe_keys):
 def compute_timeframe_defaults(labels_ordered):
 	"""
 	根据已排序的「周期 → 中文标签」映射，计算主 / 次 / 次次周期默认值。
-	默认偏好：主 4h、次 1h、次次 15m。
+	默认偏好：主 45m、次 15m、次次 5m。
 	labels_ordered: OrderedDict 或按插入顺序排列的 dict。
 	"""
 	if not labels_ordered:
 		labels_ordered = DEFAULT_TIMEFRAME_LABELS.copy()
 	timeframe_keys = list(labels_ordered.keys())
-	preferred_main = next((tf for tf in ['4h', '1h', '15m'] if tf in labels_ordered), None)
+	preferred_main = next((tf for tf in ['45m', '30m', '1h'] if tf in labels_ordered), None)
 	default_main = preferred_main or (timeframe_keys[0] if timeframe_keys else '1m')
 	if default_main not in labels_ordered and timeframe_keys:
 		default_main = timeframe_keys[0]
 
-	default_element = _prefer_smaller(['1h', '15m'], labels_ordered, default_main, timeframe_keys)
-	default_sub_sub = _prefer_smaller(['15m', '5m'], labels_ordered, default_element, timeframe_keys)
+	default_element = _prefer_smaller(['15m', '5m', '30m'], labels_ordered, default_main, timeframe_keys)
+	default_sub_sub = _prefer_smaller(['5m', '1m', '15m'], labels_ordered, default_element, timeframe_keys)
 
 	return default_main, default_element, default_sub_sub, timeframe_keys