mirror of
https://github.com/trustgraph-ai/trustgraph.git
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706e62b7c2
feat: add type hints to all public functions in trustgraph/base Add type annotations to 23 modules covering: - Metrics classes (ConsumerMetrics, ProducerMetrics, etc.) - Spec classes (ConsumerSpec, ProducerSpec, SubscriberSpec, etc.) - Service classes with add_args() and run() methods - Utility functions (logging, pubsub, clients) - AsyncProcessor methods All 93 public functions now fully typed. Refs #785 * refactor: deduplicate imports and move __future__ after docstrings Addresses review feedback on PR #803: - Remove duplicate 'from argparse import ArgumentParser' across 12 files - Move 'from __future__ import annotations' to line 1 in all files - Clean up excessive blank lines
144 lines
4.6 KiB
Python
144 lines
4.6 KiB
Python
from __future__ import annotations
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from typing import Any
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from prometheus_client import start_http_server, Info, Enum, Histogram
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from prometheus_client import Counter
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class ConsumerMetrics:
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"""
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Metrics tracking and reporting for flow consumers.
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This class manages prometheus metrics specifically related to consumers
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within the flow, including state, requests, processing time, and queues.
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"""
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def __init__(self, processor: str, flow: str, name: str) -> None:
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self.processor = processor
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self.flow = flow
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self.name = name
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if not hasattr(__class__, "state_metric"):
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__class__.state_metric = Enum(
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'consumer_state', 'Consumer state',
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["processor", "flow", "name"],
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states=['stopped', 'running']
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)
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if not hasattr(__class__, "request_metric"):
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__class__.request_metric = Histogram(
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'request_latency', 'Request latency (seconds)',
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["processor", "flow", "name"],
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)
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if not hasattr(__class__, "processing_metric"):
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__class__.processing_metric = Counter(
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'processing_count', 'Processing count',
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["processor", "flow", "name", "status"],
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)
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if not hasattr(__class__, "rate_limit_metric"):
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__class__.rate_limit_metric = Counter(
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'rate_limit_count', 'Rate limit event count',
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["processor", "flow", "name"],
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)
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def process(self, status: str) -> None:
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__class__.processing_metric.labels(
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processor = self.processor, flow = self.flow, name = self.name,
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status=status
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).inc()
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def rate_limit(self) -> None:
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__class__.rate_limit_metric.labels(
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processor = self.processor, flow = self.flow, name = self.name,
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).inc()
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def state(self, state: str) -> None:
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__class__.state_metric.labels(
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processor = self.processor, flow = self.flow, name = self.name,
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).state(state)
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def record_time(self) -> Any:
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return __class__.request_metric.labels(
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processor = self.processor, flow = self.flow, name = self.name,
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).time()
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class ProducerMetrics:
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def __init__(self, processor: str, flow: str, name: str) -> None:
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self.processor = processor
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self.flow = flow
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self.name = name
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if not hasattr(__class__, "producer_metric"):
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__class__.producer_metric = Counter(
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'producer_count', 'Output items produced',
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["processor", "flow", "name"],
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)
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def inc(self) -> None:
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__class__.producer_metric.labels(
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processor = self.processor, flow = self.flow, name = self.name
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).inc()
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class ProcessorMetrics:
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def __init__(self, processor: str) -> None:
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self.processor = processor
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if not hasattr(__class__, "processor_metric"):
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__class__.processor_metric = Info(
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'processor', 'Processor configuration',
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["processor"]
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)
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def info(self, info: dict[str, str]) -> None:
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__class__.processor_metric.labels(
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processor = self.processor
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).info(info)
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class SubscriberMetrics:
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def __init__(self, processor: str, flow: str, name: str) -> None:
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self.processor = processor
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self.flow = flow
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self.name = name
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if not hasattr(__class__, "state_metric"):
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__class__.state_metric = Enum(
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'subscriber_state', 'Subscriber state',
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["processor", "flow", "name"],
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states=['stopped', 'running']
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)
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if not hasattr(__class__, "received_metric"):
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__class__.received_metric = Counter(
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'received_count', 'Received count',
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["processor", "flow", "name"],
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)
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if not hasattr(__class__, "dropped_metric"):
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__class__.dropped_metric = Counter(
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'dropped_count', 'Dropped messages count',
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["processor", "flow", "name"],
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)
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def received(self) -> None:
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__class__.received_metric.labels(
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processor = self.processor, flow = self.flow, name = self.name,
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).inc()
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def state(self, state: str) -> None:
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__class__.state_metric.labels(
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processor = self.processor, flow = self.flow, name = self.name,
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).state(state)
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def dropped(self, state: str) -> None:
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__class__.dropped_metric.labels(
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processor = self.processor, flow = self.flow, name = self.name,
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).inc()
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