jackyu66gitandCursor
8ee11317d3
自动刷新改用 tail update 与 scrollToPosition 恢复视窗，避免 setData 后跳到最右；拆分 chart_tv 模块并扩展 analyze/recent API。同步威科夫分析、pipeline 增量构建及相关策略与配置。 Co-authored-by: Cursor <cursoragent@cursor.com>
129 lines
3.8 KiB
Python
129 lines
3.8 KiB
Python
from __future__ import annotations
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from collections import OrderedDict
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from .state import DEFAULT_TIMEFRAME_LABELS
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def _zone_cache_ttl(tf_name: str) -> int:
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"""根据时间周期返回缓存过期时间（秒）"""
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minutes = timeframe_to_minutes(tf_name) or 5
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if minutes <= 5:
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return 120 # 5m及以下: 2分钟
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elif minutes <= 15:
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return 300 # 15m: 5分钟
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elif minutes <= 60:
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return 600 # 1h: 10分钟
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else:
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return 1800 # 4h+: 30分钟
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def timeframe_to_minutes(tf: str):
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"""将时间周期转换为分钟数，用于排序。"""
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if not tf:
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return None
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unit = tf[-1]
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try:
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value = int(tf[:-1])
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except (ValueError, TypeError):
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return None
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multiplier = {
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'm': 1,
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'h': 60,
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'd': 1440,
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'w': 10080,
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'M': 43200, # 30天近似
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}.get(unit)
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if multiplier is None:
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return None
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return value * multiplier
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def format_timeframe_label(tf: str) -> str:
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"""将时间周期转换为可读标签。"""
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if not tf:
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return tf
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unit = tf[-1]
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try:
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value = int(tf[:-1])
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except (ValueError, TypeError):
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return tf
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if unit == 'm':
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return f"{value}分钟"
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if unit == 'h':
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return f"{value}小时"
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if unit == 'd':
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return "日线" if value == 1 else f"{value}日线"
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if unit == 'w':
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return "周线" if value == 1 else f"{value}周线"
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if unit == 'M':
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return "月线" if value == 1 else f"{value}月线"
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return tf
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def build_timeframe_labels(timeframes):
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ordered = sorted(
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timeframes,
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key=lambda tf: timeframe_to_minutes(tf) if timeframe_to_minutes(tf) is not None else float('inf'),
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)
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labels = OrderedDict()
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for tf in ordered:
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labels[tf] = format_timeframe_label(tf)
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return labels
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def _adjacent_smaller(timeframe_keys, ceiling_tf):
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"""取排序列表中严格小于 ceiling 的相邻周期。"""
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if not timeframe_keys:
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return ceiling_tf
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try:
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idx = timeframe_keys.index(ceiling_tf)
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return timeframe_keys[idx - 1] if idx > 0 else timeframe_keys[0]
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except ValueError:
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return timeframe_keys[0]
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def _prefer_smaller(candidates, labels_ordered, ceiling_tf, timeframe_keys):
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"""从候选中选第一个存在且严格小于 ceiling 的周期，否则回退相邻更小。"""
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ceil_m = timeframe_to_minutes(ceiling_tf)
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for tf in candidates:
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m = timeframe_to_minutes(tf)
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if tf in labels_ordered and m is not None and ceil_m is not None and m < ceil_m:
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return tf
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return _adjacent_smaller(timeframe_keys, ceiling_tf)
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def compute_timeframe_defaults(labels_ordered):
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"""
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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。
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默认偏好：主 4h、次 1h、次次 15m。
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labels_ordered: OrderedDict 或按插入顺序排列的 dict。
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"""
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if not labels_ordered:
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labels_ordered = DEFAULT_TIMEFRAME_LABELS.copy()
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timeframe_keys = list(labels_ordered.keys())
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preferred_main = next((tf for tf in ['4h', '1h', '15m'] if tf in labels_ordered), None)
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default_main = preferred_main or (timeframe_keys[0] if timeframe_keys else '1m')
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if default_main not in labels_ordered and timeframe_keys:
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default_main = timeframe_keys[0]
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default_element = _prefer_smaller(['1h', '15m'], labels_ordered, default_main, timeframe_keys)
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default_sub_sub = _prefer_smaller(['15m', '5m'], labels_ordered, default_element, timeframe_keys)
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return default_main, default_element, default_sub_sub, timeframe_keys
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def is_smaller_timeframe(tf1, tf2):
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"""判断时间周期tf1是否小于tf2"""
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tf1_value = timeframe_to_minutes(tf1)
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tf2_value = timeframe_to_minutes(tf2)
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if tf1_value is None or tf2_value is None:
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return False
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return tf1_value < tf2_value
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def is_smaller_or_equal_timeframe(tf1, tf2):
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"""判断时间周期tf1是否小于等于tf2"""
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tf1_value = timeframe_to_minutes(tf1)
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tf2_value = timeframe_to_minutes(tf2)
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if tf1_value is None or tf2_value is None:
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return False
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return tf1_value <= tf2_value
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