Modify

前置阅读

• 创建订阅请看 创建 Subscription.
• 整条订阅启停 / 单 MI 启停请看 SetMonitoringMode.

sub.modify(...)

修改 Subscription 的发布参数 (ModifySubscription 服务):

def modify(self,
           publishing_interval_ms: float,
           lifetime_count: int = 1200,
           max_keep_alive_count: int = 50,
           max_notifications_per_publish: int = 0,
           priority: int = 0) -> ModifySubscriptionResult: ...

参数	含义
publishing_interval_ms	新发布间隔
lifetime_count	多少个 publish 周期没收到 PublishRequest 就清理订阅
max_keep_alive_count	没新数据时多久发一次空 KeepAlive
max_notifications_per_publish	单次 Publish 最多发多少条通知, 0 = 不限
priority	优先级 (0-255)

返回 ModifySubscriptionResult:

字段	类型	说明
revised_publishing_interval_ms	float	服务端实际发布间隔
revised_lifetime_count	int	服务端实际 lifetime
revised_max_keep_alive_count	int	服务端实际 keepalive

rev = sub.modify(publishing_interval_ms=1000, lifetime_count=600, max_keep_alive_count=30)
print(f"Revised publishing interval = {rev.revised_publishing_interval_ms}ms")

---

sub.modify_monitored_items(requests)

批量修改 MI 采样参数 (ModifyMonitoredItems 服务):

def modify_monitored_items(
        self,
        requests: List[MonitoredItemModifyRequest]
        ) -> List[ModifyMonitoredItemResult]: ...

MonitoredItemModifyRequest 字段:

字段	默认	说明
monitored_item_handle	—	本地 MI 句柄
sampling_interval_ms	-1.0	-1 = 跟订阅, 0 = 尽快
queue_size	1	服务端缓冲队列长度
discard_oldest	True	True = 丢最旧, False = 丢最新

ModifyMonitoredItemResult:

字段	类型	说明
status	StatusCode	修改结果
revised_sampling_interval_ms	float	服务端实际采样间隔
revised_queue_size	int	服务端实际队列大小

from darra_opcua import MonitoredItemModifyRequest

requests = [
    MonitoredItemModifyRequest(
        monitored_item_handle=h,
        sampling_interval_ms=50,
        queue_size=10,
        discard_oldest=True)
    for h in mi_handles
]
results = sub.modify_monitored_items(requests)

---

sub.modify_item(...) 单 MI 简化版

def modify_item(self,
                monitored_item_handle: int,
                sampling_interval_ms: float,
                queue_size: int = 1,
                discard_oldest: bool = True) -> ModifyMonitoredItemResult: ...

r = sub.modify_item(handle, sampling_interval_ms=50)
print(f"Revised sampling = {r.revised_sampling_interval_ms}ms")

---

queue_size 与 discard_oldest

服务端为每个 MI 维护一个先进先出队列. 当客户端 Publish 来不及取时, 队列满了:

• discard_oldest = True (默认) → 丢最旧, 保留最新
• discard_oldest = False → 丢最新, 保留最旧

queue_size = 1 (默认) 只保留最新值, 适合"实时显示"; queue_size = N (N > 1) 适合"采样不能漏"的高频数据.

下一步

• SetMonitoringMode
• Republish