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76 lines
2.1 KiB
Markdown
76 lines
2.1 KiB
Markdown
---
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name: configured-logger-pending-count
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group: api
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category: runtime
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update-time: 20260613
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description: Read the current queued backlog count from a configured runtime logger through RuntimeSink.
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key-word:
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- logger
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- runtime
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- queue
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- public
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---
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## Configured-logger-pending-count
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Read the current queued backlog count from a `ConfiguredLogger`. This is the configured logger wrapper over `RuntimeSink::pending_count(...)` for config-driven queue metrics.
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### Interface
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```moonbit
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pub fn ConfiguredLogger::pending_count(self : ConfiguredLogger) -> Int {}
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```
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#### input
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- `self : ConfiguredLogger` - Config-driven runtime logger whose queue backlog should be inspected.
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#### output
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- `Int` - Current number returned by the wrapped `RuntimeSink::pending_count()` call.
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### Explanation
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Detailed rules explaining key parameters and behaviors
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- This helper delegates directly to `self.sink.pending_count()`.
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- Queue-backed runtime sink variants return their live pending count.
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- Plain console and plain file runtime sink variants return `0` because they do not own a pending queue here.
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- This is a point-in-time metric and may change immediately after it is read.
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### How to Use
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Here are some specific examples provided.
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#### When Need Configured Queue Backlog Visibility
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When a config-built logger should expose queue pressure:
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```moonbit
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let pending = logger.pending_count()
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```
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In this example, queue backlog is observed without reaching into the sink internals.
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#### When Verify Manual Drain Progress
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When drain loops should observe remaining backlog:
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```moonbit
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ignore(logger.drain(max_items=8))
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ignore(logger.pending_count())
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```
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In this example, the queue metric helps verify manual drain progress.
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### Error Case
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e.g.:
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- If the configured logger is not queue-backed, the method simply returns `0`.
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- If callers need richer file-plus-queue state for file sinks, `file_runtime_state()` is the better API.
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### Notes
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1. Use this helper for simple queue visibility on config-built loggers.
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2. Pair it with `dropped_count()` when investigating loss behavior.
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