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trace sampler

Language: Python · Sphere: programming · Category: Monitoring

Signature: (sampler_type: str) → Sampler

What it does

Distributed Tracing Sampler Module

This module provides a complete implementation of a distributed tracing sampler with support for rate limiting, priority traces, and adaptive sampling.

Guarantee

When it runs, trace sampler guarantees first == 5; second == 5; all((on.should_sample(_ctx(i)).decision == SamplingDecision.SAMPLE for i in range(50))) (proven by run).

Checkable constraints:

  • all((on.should_sample(_ctx(i)).decision == SamplingDecision.SAMPLE for i in range(50)))
  • all((off.should_sample(_ctx(i)).decision == SamplingDecision.DROP for i in range(50)))
  • all((ProbabilisticSampler(1.0).should_sample(_ctx(i)).decision == SamplingDecision.SAMPLE for i in range(50)))
  • all((ProbabilisticSampler(0.0).should_sample(_ctx(i)).decision == SamplingDecision.DROP for i in range(50)))
  • 140 <= hits <= 260
  • first == 5
  • second == 5
  • pr.should_sample(_ctx(1, priority=True)).decision == SamplingDecision.SAMPLE

Verification evidence

  • Green-run: ✓ passes (re-run under the extractor's gate)
  • Constraint strength: recovery (truth-pinned)
  • Independent oracle: — none yet (green-run candidate; not an axiom under the frozen ruler)
  • Peer review: unreviewed

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