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Testbased performance monitor
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# Test Performance Monitoring
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Date: 2026-05-05
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Status: lightweight pytest performance history for local situational awareness.
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## Purpose
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The test suite records a compact performance history on every pytest run. The
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goal is not detailed profiling. It is a small scorekeeping loop that helps us
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notice negative drift while the engine grows.
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The monitor captures:
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- run start and finish timestamps,
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- total test run duration,
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- per-test duration and outcome,
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- Python and platform identity,
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- logical CPU count,
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- load averages and load-per-CPU where available,
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- memory total, available memory, and available ratio from `/proc/meminfo`
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where available,
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- process user/system CPU deltas and peak resident memory.
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## Storage
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Default history path:
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```text
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.pytest_cache/kontextual/performance-history.json
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```
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`.pytest_cache/` is ignored by git, so regular test runs do not dirty the
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repository. A different path can be supplied with `--perf-history-path` or
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`KONTEXTUAL_PERF_HISTORY`.
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## Retention Model
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The JSON file keeps a bounded, compact record:
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- the last `N` raw runs,
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- the last `N` rolling averages over the retained runs,
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- the average of the last `N` rolling averages,
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- one compact daily average record per day, updated on every run,
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- daily records retained for a configurable number of days.
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Defaults:
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- `N = 20`,
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- daily retention = `730` days,
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- drift warning ratio = `35%`,
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- minimum duration delta before warning = `0.05s`.
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Skipped tests are recorded in raw runs and aggregate counts, but they are not
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used as per-test duration baselines. This keeps optional Markitect and capacity
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tests from producing false regressions when they switch from skipped to
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executed.
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## Warnings
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At the end of the pytest run, the monitor compares the current run with the
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previous average-of-averages. It prints warnings for:
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- total run duration drift, when the executed test count is comparable,
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- individual test duration drift,
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- materially higher normalized start load,
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- materially lower available-memory ratio.
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Warnings do not fail the test run. They are meant to create attention, not gate
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development.
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## Configuration
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Disable monitoring:
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```bash
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python3 -m pytest --perf-history-disable
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```
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or:
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```bash
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KONTEXTUAL_PERF_MONITOR=0 python3 -m pytest
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```
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Override retention and warning thresholds:
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```bash
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python3 -m pytest \
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--perf-history-window 30 \
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--perf-history-drift-ratio 0.50 \
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--perf-history-min-delta 0.10
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```
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Environment equivalents:
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- `KONTEXTUAL_PERF_HISTORY`,
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- `KONTEXTUAL_PERF_WINDOW`,
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- `KONTEXTUAL_PERF_DAILY_RETENTION_DAYS`,
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- `KONTEXTUAL_PERF_DRIFT_RATIO`,
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- `KONTEXTUAL_PERF_MIN_DELTA_SECONDS`.
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## When To Profile Instead
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Use this monitor to spot drift and identify candidate tests or areas. If a
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warning points to a real bottleneck, create a focused profiling experiment or a
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capacity sentinel. Do not add large traces or per-function profiling data to
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the rolling history.
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