将 web/services/runtime.py 拆为 runtime/ 子模块并保持门面兼容;补齐 ESS 文档、门面/契约/TF_DF 测试与 CODE_REVIEW Approve。 Co-authored-by: Cursor <cursoragent@cursor.com>
122 lines
3.3 KiB
Python
122 lines
3.3 KiB
Python
from __future__ import annotations
|
|
|
|
from collections import OrderedDict
|
|
from .state import DEFAULT_TIMEFRAME_LABELS
|
|
|
|
def _zone_cache_ttl(tf_name: str) -> int:
|
|
"""根据时间周期返回缓存过期时间(秒)"""
|
|
minutes = timeframe_to_minutes(tf_name) or 5
|
|
if minutes <= 5:
|
|
return 120 # 5m及以下: 2分钟
|
|
elif minutes <= 15:
|
|
return 300 # 15m: 5分钟
|
|
elif minutes <= 60:
|
|
return 600 # 1h: 10分钟
|
|
else:
|
|
return 1800 # 4h+: 30分钟
|
|
|
|
|
|
def timeframe_to_minutes(tf: str):
|
|
"""将时间周期转换为分钟数,用于排序。"""
|
|
if not tf:
|
|
return None
|
|
unit = tf[-1]
|
|
try:
|
|
value = int(tf[:-1])
|
|
except (ValueError, TypeError):
|
|
return None
|
|
multiplier = {
|
|
'm': 1,
|
|
'h': 60,
|
|
'd': 1440,
|
|
'w': 10080,
|
|
'M': 43200, # 30天近似
|
|
}.get(unit)
|
|
if multiplier is None:
|
|
return None
|
|
return value * multiplier
|
|
|
|
|
|
def format_timeframe_label(tf: str) -> str:
|
|
"""将时间周期转换为可读标签。"""
|
|
if not tf:
|
|
return tf
|
|
unit = tf[-1]
|
|
try:
|
|
value = int(tf[:-1])
|
|
except (ValueError, TypeError):
|
|
return tf
|
|
if unit == 'm':
|
|
return f"{value}分钟"
|
|
if unit == 'h':
|
|
return f"{value}小时"
|
|
if unit == 'd':
|
|
return "日线" if value == 1 else f"{value}日线"
|
|
if unit == 'w':
|
|
return "周线" if value == 1 else f"{value}周线"
|
|
if unit == 'M':
|
|
return "月线" if value == 1 else f"{value}月线"
|
|
return tf
|
|
|
|
|
|
def build_timeframe_labels(timeframes):
|
|
ordered = sorted(
|
|
timeframes,
|
|
key=lambda tf: timeframe_to_minutes(tf) if timeframe_to_minutes(tf) is not None else float('inf'),
|
|
)
|
|
labels = OrderedDict()
|
|
for tf in ordered:
|
|
labels[tf] = format_timeframe_label(tf)
|
|
return labels
|
|
|
|
|
|
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。
|
|
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 ['5m', '15m', '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]
|
|
|
|
if timeframe_keys:
|
|
try:
|
|
idx = timeframe_keys.index(default_main)
|
|
default_element = timeframe_keys[idx - 1] if idx > 0 else timeframe_keys[0]
|
|
except ValueError:
|
|
default_element = timeframe_keys[0]
|
|
else:
|
|
default_element = default_main
|
|
|
|
if timeframe_keys:
|
|
try:
|
|
idx_el = timeframe_keys.index(default_element)
|
|
default_sub_sub = timeframe_keys[idx_el - 1] if idx_el > 0 else timeframe_keys[0]
|
|
except ValueError:
|
|
default_sub_sub = timeframe_keys[0]
|
|
else:
|
|
default_sub_sub = default_element
|
|
|
|
return default_main, default_element, default_sub_sub, timeframe_keys
|
|
|
|
def is_smaller_timeframe(tf1, tf2):
|
|
"""判断时间周期tf1是否小于tf2"""
|
|
tf1_value = timeframe_to_minutes(tf1)
|
|
tf2_value = timeframe_to_minutes(tf2)
|
|
if tf1_value is None or tf2_value is None:
|
|
return False
|
|
return tf1_value < tf2_value
|
|
|
|
def is_smaller_or_equal_timeframe(tf1, tf2):
|
|
"""判断时间周期tf1是否小于等于tf2"""
|
|
tf1_value = timeframe_to_minutes(tf1)
|
|
tf2_value = timeframe_to_minutes(tf2)
|
|
if tf1_value is None or tf2_value is None:
|
|
return False
|
|
return tf1_value <= tf2_value
|
|
|