anti
627fa59c15
Bucket ctx.duration_s against SESSION_DURATION_SHORT_MAX (60s) / MEDIUM_MAX (600s) / LONG_MAX (3600s); else marathon. Direct measurement, confidence 0.85. Skip emission only when no commands and zero duration. New _features/temporal.py module opens Phase E.
51 lines
1.7 KiB
Python
51 lines
1.7 KiB
Python
"""``temporal.*`` feature functions — per-session subset.
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Phase E ships the four ``temporal.*`` primitives that don't need
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observation history. The other three (``session_timing``,
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``persistence``, ``lifecycle_markers.idle_periodicity``) are Tier B
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and computed by the attribution engine, not the extractor.
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Step E.1: ``temporal.session_duration``.
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"""
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from __future__ import annotations
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from typing import Iterator
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from decnet_behave_core.spec.envelope import Observation
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from decnet.profiler.behave_shell._ctx import SessionContext
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from decnet.profiler.behave_shell._features._emit import make_observation
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from decnet.profiler.behave_shell._thresholds import (
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SESSION_DURATION_LONG_MAX,
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SESSION_DURATION_MEDIUM_MAX,
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SESSION_DURATION_SHORT_MAX,
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)
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def session_duration(ctx: SessionContext) -> Iterator[Observation]:
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"""Emit ``temporal.session_duration`` ∈ {short, medium, long, marathon}.
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Direct measurement off ``ctx.duration_s``. Skip emission only when
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the session has neither commands nor any duration to speak of —
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a one-event session with ``duration_s == 0`` and no commands has
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nothing honest to bucket. Confidence is high — duration is a fact,
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not an inference.
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"""
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if ctx.duration_s <= 0.0 and not ctx.commands:
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return
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d = ctx.duration_s
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if d < SESSION_DURATION_SHORT_MAX:
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value = "short"
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elif d < SESSION_DURATION_MEDIUM_MAX:
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value = "medium"
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elif d < SESSION_DURATION_LONG_MAX:
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value = "long"
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else:
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value = "marathon"
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yield make_observation(
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ctx,
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primitive="temporal.session_duration",
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value=value,
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confidence=0.85,
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)
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