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2
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| Author | SHA1 | Date | |
|---|---|---|---|
 xavierk
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6917a658cb | ||
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xavierk
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d790ff84c5 |
+3
-23
@@ -32,25 +32,13 @@ _Avoid_: Data directory, history.jsonl, the database (generic)
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The condition where the observation store is present but cannot be read or trusted — unreadable, corrupt, or written by a newer Fenris — degrading every view that depends on it rather than crashing or guessing.
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_Avoid_: Database error, corruption, broken data
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**Usage interval**:
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The elapsed span between two compatible counter observations, with a measured usage total whose distribution within that span may be unknown.
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_Avoid_: Estimated hourly usage, interpolated sample
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**Unallocated usage**:
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Measured usage whose share in a particular hour, calendar day, or monitoring period cannot be established from the available evidence.
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_Avoid_: Zero usage, evenly distributed writes
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**Hour observation**:
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The usage-habit evidence for a UTC hour's represented elapsed span: active, idle, powered-off, and unknown time, measured usage, thermal evidence, and coverage. A partial hour does not describe future time.
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One row per UTC hour in the observation store, recording that hour's usage-habit split into active, idle, powered-off, and unknown seconds, plus write/read deltas, thermal evidence, and coverage.
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_Avoid_: Hourly record, hourly.jsonl entry
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**Day aggregate**:
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The UTC-day summary at which usage-habit evidence is judged; distinct from a local display day.
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_Avoid_: Local daily total, daily stats
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**Local display day**:
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A calendar day in the user's current system timezone, used to browse observation history; its elapsed length can vary with timezone transitions.
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_Avoid_: UTC evidence day, fixed 24-hour day
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One row per UTC day derived from hour observations; the grain at which usage-habit evidence is judged.
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_Avoid_: Daily summary, daily stats
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**Controller segment**:
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A span of observation history within which the drive's controller identity is unchanged and counters are monotonic; write deltas are never computed across a segment boundary.
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@@ -88,14 +76,6 @@ _Avoid_: Confidence interval, error bar
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The share of wall-clock seconds inside monitoring periods whose usage-habit classification is known rather than unknown.
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_Avoid_: Uptime, sample count
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**Byte-allocation completeness**:
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Whether the available evidence establishes all monitored writes attributable to a specified span, without missing counter evidence or unknown boundary shares; distinct from usage-habit classification coverage.
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_Avoid_: Coverage, estimated allocation
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**Qualifying day**:
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A UTC date whose represented monitored time meets the coverage requirement for projection evidence. Qualification is provisional while the date is in progress and does not establish byte-allocation completeness.
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_Avoid_: Completed day, supported day, calibration day
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**Collection run**:
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One scheduled or on-demand execution of the collector that interrogates the drive and extends the observation history.
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_Avoid_: Poll, daemon tick
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@@ -144,19 +144,3 @@ Decided in [Write the dashboard clarity acceptance criteria](https://git.bongbet
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- **DC-6** (A) CHANGELOG.md shape (Keep a Changelog 1.1): `## [Unreleased]` always present at top, even empty; version headings `## [X.Y.Z] - YYYY-MM-DD` with strict ISO date; categories Added/Changed/Fixed only, security folding into Fixed; entries are single `- ` bullets, imperative mood, user-facing, no commit hashes or issue numbers.
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- **DC-7** (A) Extraction fails closed: `scripts/extract_changelog.py` slices the requested version's section verbatim and never reads `[Unreleased]`; a missing or empty section or a malformed date produces `::error::` and a nonzero exit; the release workflow fails when the pushed tag ≠ `v{version from pyproject.toml}` (guard skipped on `workflow_dispatch`).
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- **DC-8** (A/P) Release body: the body is the extracted section verbatim plus the standing footer from `packaging/release-footer.md`; a re-run against an existing release PATCHes the body (re-sync is a feature) while uploaded assets skip idempotently. A covers assembly/PATCH-logic unit tests; P is one scripted `workflow_dispatch` verification of body assembly.
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## TUI polish and hourly history ([Fenris TUI polish and hourly history](https://git.bongbetic.com/xavierk/Fenris/issues/65))
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Proposed by [Approve the Fenris TUI polish specification and handoff](https://git.bongbetic.com/xavierk/Fenris/issues/70), from the companion specification [`fenris-tui-polish-hourly-history.md`](fenris-tui-polish-hourly-history.md). This section amends the frozen redesign and prior dashboard-clarity criteria without editing their historical source specs. Where these criteria conflict with older TUI/header/history criteria, these newer criteria win. In particular, **TPH-1** supersedes **DC-1**'s header/credit placement; **TPH-2** and **TPH-3** refine **CI-2**, **LC-10**, and **TUI-4** status rendering; **TPH-4** through **TPH-7** refine **ST-5**, **PR-2** through **PR-9**, and **FL-1** through **FL-4** with the approved hourly-history and UTC-accounting contracts.
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- **TPH-1** (A) *Titlebox and maker credit*: the TUI renders a top titlebox exactly `🐺 Fenris by Bongbetic`, falling back exactly to `Fenris by Bongbetic` when the wolf glyph is unsupported or width-unstable; no replacement-box glyph is shown; the old service-strip `by Bongbetic` credit is absent; `fenris status` renders no titlebox. Continuity, paused, quit, auth, parity, and release-notes behavior from **DC-2** through **DC-8** remains unchanged.
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- **TPH-2** (A) *Status lattice and precedence*: fixture-driven TUI status rendering covers Monitoring, Collecting, Paused, Waiting, Interrupted, Error, Stale, and Unknown with the approved glyphs/text, semantic colours, and reason lines; only Monitoring's dot blinks, never text; reduced motion makes it steady; precedence is Error > Interrupted > Paused > Stale > Waiting > Monitoring > Unknown, with Collecting as an overlay except over store fault.
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- **TPH-3** (A/P) *CLI/status parity and timing*: `fenris status` renders the same status vocabulary, glyphs, precedence, and reason lines statically; freshness, last outcome, boot enablement, and collection activity remain separate facts; a lightweight 5 s unit-state poll can move cached freshness boundaries without a store read, while new samples appear only after the normal store refresh; store faults render `observation store unreadable — see journal` and suppress store-dependent views.
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- **TPH-4** (A) *Warm-up and withheld estimates*: projection warm-up shows `Building evidence — N of 14 days observed · Q qualifying` plus `First lifespan estimate after 12 qualifying days`; the gate is 14 represented UTC dates in the current controller segment with at least 12 qualifying, while Supported separately requires 14 qualifying dates and all existing prerequisites. Missing baseline, unsupported write counters, warm-up, stale evidence, paused days, and unavailable numerators render explicit reason lines, never blank or misleading zero; first graph-data availability is independent of lifespan-estimate availability.
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- **TPH-5** (A) *Collector-owned history publication and first data*: collection publishes validated sample → usage interval → hour observation/day aggregate results consistently before reporting success; the TUI remains read-only. Zero samples show awaiting-first-sample; one sample shows `Awaiting another sample`; the first compatible sample pair can show measured partial-hour `so far`; measured zero is `0 B`; missing, unsupported, invalid, or unavailable evidence is never converted to zero.
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- **TPH-6** (A) *Local display days, attribution, gaps, pauses, and repair*: history browsing groups retained evidence by the current system timezone with the timezone label visible, including DST and fractional-offset cases; timestamped usage intervals are retained indefinitely alongside hour/day summaries, while raw samples keep the 14-day policy except needed boundary anchors. Measured interval totals are preserved once; cross-boundary shares render as unallocated usage rather than interpolation or endpoint assignment; gaps remain distinct from zero; future time is not counted; deliberate-disable time is excluded; pause-crossing bytes are not counted as monitored totals; repair is transactional/idempotent and cannot overwrite valid older history with incomplete reconstruction.
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- **TPH-7** (A) *UTC projection accounting and evaluability*: 7/28/90-day scenario windows end at the latest published usage-evidence endpoint `T` and start exactly 7/28/90 × 86,400 seconds earlier; denominators are monitored wall-clock seconds in the same span; rates are withheld when the monitored numerator cannot be established. Byte-allocation completeness and coverage are independent. Current partial UTC dates can qualify provisionally using elapsed monitored time; habit changes require completed consecutive UTC days with evaluable totals; unknown daily totals block burst/habit checks and Supported confidence; resets/replacements and legacy summaries obey the approved segment and actual-precision rules without changing lifespan math or numeric thresholds.
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- **TPH-8** (A/M) *Writes-only graph and drill-down*: the TUI renders a writes-only daily bar graph, default 14 days, selectable 7/14/28/90 days, labelled `usage history · Local · UTC±HH:MM · <tz name>`; graph focus supports `←`/`→`, `Enter`, `Esc`/`Backspace`, and `1`/`2`/`3`/`4`, with mouse equivalents for select/drill/back where Textual support is available. Daily bars drill into hourly bars and back. The legend distinguishes allocated `█`, unallocated `▒`, gap `░`, measured zero `·`, partial `┄`, and selection `▼`; selected readout states totals, evidenced hours, unallocated usage, coverage, and partial elapsed facts. Reads graphing is out of scope.
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- **TPH-9** (A) *Terminal size and graph implementation*: at 80×24 the default range graph and hourly drill-down fit; below 80×24 the graph region hides and shows a one-line textual history summary plus exactly `graph needs ≥80×24`, while titlebox, status reason, drive health, service facts, quit rail/action affordances, and selected-day context survive. The graph uses a custom block-glyph renderable; no new plotting dependency is added for this graph.
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- **TPH-10** (A/M) *Colour presets, persistence, and reduced motion*: Amber, Nord, and High Contrast presets are available; Amber is the default and keeps the graph amber by default; status semantic colours/glyphs/text outrank theme styling. Preset and reduced-motion choices persist per unprivileged user at `${XDG_CONFIG_HOME:-~/.config}/fenris/tui.json`, not in `/etc/fenris/fenris.conf`, the observation store, helper state, package config, or collector/device configuration; missing preferences default to Amber and normal motion; `t preset` and `m motion` controls plus accessible clickable equivalents are available; preferences never affect collection, projection, history evidence, or `fenris status`.
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- **TPH-11** (A) *Drive health and settings grouping*: vendor wear renders under Drive health with temperature, spare, media errors, unsafe shutdowns, power-on hours, cycles, capacity, and written-total context, and remains context rather than a second projection. Settings is read-only and limited to device selector, endurance baseline/provenance, retention facts, and TUI display preferences; no custom colour editor exists.
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@@ -1,351 +0,0 @@
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# Fenris TUI polish and hourly history companion specification
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**Status:** approval-ready draft for [Approve the Fenris TUI polish specification and handoff](https://git.bongbetic.com/xavierk/Fenris/issues/70). It becomes implementation-ready only when that ticket records human approval. This is a planning asset: no production code, release gate, package, installation change, or runtime diagnosis is made here.
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**Canonical sources.** This companion integrates the closed decisions on [Fenris TUI polish and hourly history](https://git.bongbetic.com/xavierk/Fenris/issues/65): [Define trustworthy hourly history and first-data availability](https://git.bongbetic.com/xavierk/Fenris/issues/66), [Choose daily graph encoding and hourly drill-down](https://git.bongbetic.com/xavierk/Fenris/issues/68), [Reconcile unallocated usage with UTC projection evidence](https://git.bongbetic.com/xavierk/Fenris/issues/71), [Define monitoring signals and honest warm-up estimates](https://git.bongbetic.com/xavierk/Fenris/issues/67), and [Approve titlebox, health layout and colour presets](https://git.bongbetic.com/xavierk/Fenris/issues/69). Terminology follows [`CONTEXT.md`](../../CONTEXT.md), including *Usage interval*, *Unallocated usage*, *Local display day*, *Byte-allocation completeness*, and *Qualifying day*.
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**Relationship to existing specs.** [`fenris-redesign.md`](fenris-redesign.md) stays frozen. This companion amends it without editing it. [`dashboard-clarity.md`](dashboard-clarity.md) remains binding except where this document explicitly supersedes its header/credit placement. In the tracker, [Implement dashboard clarity and release notes](https://git.bongbetic.com/xavierk/Fenris/issues/61) is currently closed; this companion is a new follow-on handoff, not a rewrite or reopening of that shipped umbrella.
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**Binding language.** *Must*, *exactly*, and *never* are normative.
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## 1. Supersession and preserved requirements
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This companion supersedes only these dashboard-clarity identity placements:
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- the old header `Fenris — NVMe endurance monitor`;
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- the old dimmed `by Bongbetic` credit in the service strip.
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The new identity contract is the top titlebox in §2. The titlebox is the sole maker-credit surface.
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Everything else from [Chart Fenris dashboard clarity](https://git.bongbetic.com/xavierk/Fenris/issues/55) remains intact unless a more specific clause below amends its placement: the continuity wording, paused block and Deliberate-disable semantics, `q QUIT TUI` rail, footer action ownership, polkit-accurate auth banner, TUI/CLI wording parity where binding, changelog-driven release notes, and the quit-versus-pause distinction. Polkit wording remains polkit-accurate; no new user-facing TUI/status string says "sudo".
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## 2. Product identity, health layout, and settings
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### 2.1 Titlebox
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The TUI's top titlebox must read exactly:
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```text
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🐺 Fenris by Bongbetic
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```
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If the wolf glyph is unsupported or would disturb titlebox width, the fallback is exactly:
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```text
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Fenris by Bongbetic
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```
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Do not render tofu, replacement boxes, or an unstable emoji-width layout. The lifespan headline remains a drive/projection data surface, not the application title. `fenris status` does not render this titlebox.
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### 2.2 Maker credit
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Remove the duplicate `by Bongbetic` service-strip credit in the polished layout. The titlebox is the only maker-credit surface. This is the explicit amendment to the prior dashboard-clarity header/credit placement; it does not weaken the preserved continuity, pause, quit, auth, parity, or release-notes requirements.
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### 2.3 Drive health and settings grouping
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Move vendor wear under **Drive health**, alongside temperature, spare, media errors, unsafe shutdowns, power-on hours, cycles, capacity, and written-total context. Vendor wear remains context, never a second projection.
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**Settings** remains read-only and limited to the device selector, endurance baseline/provenance, retention facts, and TUI display preferences. No custom colour editor is added.
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## 3. Monitoring status, collection activity, and warm-up messaging
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### 3.1 Status lattice
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Every status line carries a glyph and text label. Colour is never the sole carrier. Text never blinks.
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| State | Colour | Glyph | Motion | Exact status / explanation contract |
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|---|---|---|---|---|
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| Monitoring | green | `●` | blink 750 ms on / 750 ms off, status dot only | `● Monitoring` |
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| Collecting | green | `◐` | steady | `◐ Collecting` — run in flight, bounded by the 90 s collection timeout |
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| Paused | amber | `‖` | steady | `‖ Paused` — `monitoring paused — paused time excluded from your usage habit` |
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| Waiting | amber | `○` | steady | `○ Waiting` — `last sample X ago`, `awaiting first sample`, or `awaiting another sample` |
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| Interrupted | red | `⊘` | steady | `⊘ Interrupted` — `collection stopped outside Fenris — monitoring period still open` |
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| Error | red | `✖` | steady | `✖ Error` — `last run failed (exit N)` plus `last good sample X ago` when data is still fresh, or `observation store unreadable — see journal` |
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| Stale | red | `◌` | steady | `◌ Stale` — `last sample X days ago` when the timer is active and no failure is recorded |
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| Unknown | grey | `?` | steady | `? Unknown` — `service state unavailable` |
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Reduced motion, either from Textual's reduced-motion signal or the user's preference, renders Monitoring as a steady `● Monitoring`. The CLI form is always steady.
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### 3.2 Precedence
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Base-state precedence is:
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```text
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Error > Interrupted > Paused > Stale > Waiting > Monitoring > Unknown
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```
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Additional rules:
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- Paused outranks Stale. A drive paused for 49 days is amber Paused with `last sample 49 days ago` as a fact line, not a stale alarm.
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- Error outranks Interrupted; the external stop rides in the explanation line when both facts exist.
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- Unknown is used only when the service query fails and no store-derived fact, such as an open monitoring period, freshness, or deliberate-pause row, places the state higher.
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- Collecting is an overlay, not a base rung. While the oneshot is in flight it overrides every base state except a store fault. While overlaying Paused, Interrupted, or retry-after-failure, the explanation line names the underlying state: for example, `run in flight — paused` or `run in flight — retry`. It reverts within the 90 s collection timeout to whatever state the outcome earns.
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### 3.3 Separate facts
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Do not fold these facts into the status word:
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- `Last sample: X ago` freshness;
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- last outcome: ok, failed with exit code, or none;
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- `Start at boot: on/off` boot enablement;
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- collection activity, which is represented by the Collecting overlay.
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Blink means exactly "monitoring enabled and data fresh". It never means that collection just succeeded; collection activity is explicit Collecting.
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### 3.4 Timing and refresh
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A lightweight 5 s `systemctl show` poll of the timer and service units drives the status strip. The full store refresh remains at the 5-minute cadence. Status transitions are re-evaluated every poll tick from cached newest-sample timestamp plus current clock, so freshness aging boundaries cross within roughly 5 s without a store read. A new sample requires the normal store refresh.
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The existing constants remain unchanged: fresh is newest sample within 2 × cadence + `AccuracySec` + 60 s, stale is at 48 h, collection timeout is 90 s, and default cadence is 5 min.
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### 3.5 Canonical transitions
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The implementation must make these states directly observable:
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- failed run, data 4 min old: `✖ Error` — `last run failed (exit 3) · last good sample 4 min ago`;
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- next successful run: `● Monitoring` after the status poll/refresh clears the failure;
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- failed run with retry in flight: `◐ Collecting` — `run in flight — retry`, then Error or Monitoring;
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- suspend for 3 h, wake, timer fires: `○ Waiting` → `◐ Collecting` → `● Monitoring`;
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- external stop with fresh data: `⊘ Interrupted` — `collection stopped outside Fenris`;
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- external stop 3 days later: still `⊘ Interrupted`, with `last sample 3 days ago` visible;
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- fresh install with zero samples: `○ Waiting` — `awaiting first sample`;
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- one sample but no compatible pair: `○ Waiting` — `awaiting another sample`;
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- unreadable observation store: `✖ Error` — `observation store unreadable — see journal`, with store-dependent views suppressed.
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### 3.6 Warm-up and withheld estimates
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Projection warm-up uses the UTC accounting rules in §5. The progress block during warm-up is:
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```text
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Building evidence — N of 14 days observed · Q qualifying
|
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First lifespan estimate after 12 qualifying days
|
||||
```
|
||||
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||||
`N` counts distinct represented UTC dates in the current controller segment, capped at 14 for the display. `Q` counts dates whose represented monitored span has at least 50% coverage. The gate for the first lifespan estimate is 14 represented UTC dates with at least 12 qualifying; Supported confidence still separately requires at least 14 qualifying dates plus every other confidence prerequisite.
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Do not promise a countdown by hours. Days are the grain, and a provisional day can still fail qualification. Graph-data availability is independent: the graph can render from first usable evidence while the lifespan estimate remains withheld.
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Withheld-estimate reason lines are explicit, never blank and never zero-filled:
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|
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- `No endurance baseline — set a rated TBW to see an estimate`;
|
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- `Drive does not report write counters`;
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- the warm-up progress block above;
|
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- stale evidence: show the estimate frozen at the latest published usage-evidence endpoint with `estimate not updating — last sample X ago`;
|
||||
- paused days are excluded from the day count, and the Paused status carries that fact.
|
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|
||||
Once warm-up clears, the existing lifespan line and Limited/Supported label from the frozen redesign specification render unchanged. This companion adds the progress block, reason lines, status precedence, and frozen-note behavior; it does not invent a new steady-state projection format.
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### 3.7 CLI parity
|
||||
|
||||
`fenris status` adopts the same status vocabulary, precedence, glyphs, and reason lines, rendered statically. It shows Collecting only if a run is in flight at query time. Display preferences and TUI themes never affect CLI facts.
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## 4. History evidence, local browsing, and publication
|
||||
|
||||
### 4.1 Ownership and publication
|
||||
|
||||
The collector owns sample → usage interval → hour observation/day aggregate derivation. It must publish a consistent validated result before reporting collection success. Readers must not see a new sample advertised as fully derived while dependent history is missing.
|
||||
|
||||
The TUI is read-only. Its next successful refresh sees whatever the collector has durably published, regardless of whether the TUI was running during collection. There is no hourly batch wait and no projection-confidence gate on usage history. Failure preserves prior valid history and remains explicit.
|
||||
|
||||
### 4.2 First visible data
|
||||
|
||||
One successful sample establishes counter, health, and freshness evidence, but not a usage delta; display `Awaiting another sample`. The first usable sample pair may display measured partial-hour usage labelled `so far` when attribution supports it. A usable pair has valid ordered timestamps and supported, nonnegative monotonic counters in the same controller segment; monitored totals additionally require an interval fully inside one monitoring period.
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||||
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||||
A cross-hour pair is a real usage interval total, not two invented hour values. Measured zero is visible `0 B`. Missing, unsupported, invalid, or absent evidence is never converted to zero.
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||||
|
||||
### 4.3 Local display days
|
||||
|
||||
Storage timestamps and projection evidence days remain UTC. History browsing uses the user's current system timezone, visibly labelled. If the system timezone changes, the same retained evidence regroups into the new local display days. Use real calendar boundaries: DST days may be 23 or 25 hours, repeated local hours have distinct offsets, and fractional UTC offsets must work without synthetic splitting.
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||||
|
||||
### 4.4 Retention and repair
|
||||
|
||||
Retain timestamped usage intervals indefinitely alongside hour observations and day aggregates. Full raw samples retain the 14-day policy, with a boundary-anchor exception: do not prune a raw sample that is still needed to durably derive an unfinished interval/hour/day representation.
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||||
|
||||
Repair derives only what surviving raw evidence supports, transactionally and idempotently. It preserves original evidence and valid historical summaries. Incomplete reconstruction must not overwrite valid older history. Unsupported historical precision stays unavailable; it is not repaired by interpolation or waiting. A failed repair remains visible and retryable.
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||||
|
||||
### 4.5 Attribution and gaps
|
||||
|
||||
Preserve measured usage interval totals. Never divide them proportionally across hours or calendar days, never assign them to an endpoint as if timing were observed, and never double-count interval totals and summaries derived from the same evidence.
|
||||
|
||||
An interval entirely inside a local display day and one monitoring period may contribute its total to that local-day total even if individual hour shares are unknown. Otherwise the total is shown separately as unallocated usage. An incomplete allocated subtotal must not be presented as a complete total.
|
||||
|
||||
Missing samples reduce usage-habit coverage where classification is unknown, but they do not erase a compatible measured gap total. Byte-allocation completeness and usage-habit classification coverage are distinct. Do not infer zero writes from missing samples.
|
||||
|
||||
Partial summaries represent elapsed time only. Future time is neither zero nor unknown. Deliberately disabled time is excluded, not an hour state. Intervals crossing a deliberate pause cannot distinguish monitored from paused writes: preserve the original evidence, exclude ambiguous bytes from monitored totals, and explain why. External service stops remain unexplained in-period gaps, not Deliberate disables.
|
||||
|
||||
### 4.6 Controller segments in browsing
|
||||
|
||||
The default history view is the current controller segment. Older segments remain browsable with explicit reset/replacement boundaries. Never form a delta across a controller-segment boundary or silently combine different drives.
|
||||
|
||||
## 5. UTC projection accounting and confidence amendments
|
||||
|
||||
This section amends the projection contract without changing lifespan mathematics, numeric thresholds, or confidence categories.
|
||||
|
||||
### 5.1 Measured totals and requested spans
|
||||
|
||||
For any requested span, count a compatible interval's total exactly once when its complete span is inside the requested span, inside one monitoring period, and has eligible controller provenance. It may supply a complete window total even when individual UTC-hour/day shares are unknown.
|
||||
|
||||
A positive interval crossing a requested boundary cannot supply that window's unknown share. Preserve its measured total separately as unallocated usage. Do not split proportionally, assign to the ending day, silently omit possible bytes, or label an incomplete subtotal as complete.
|
||||
|
||||
Withhold a rate whenever its monitored numerator cannot be established: unresolved boundary shares, missing initial/resume/reset counter support, and legacy eligibility ambiguity are not zero. Do not shorten the requested window or remove unknown monitored seconds merely to obtain a number. A compatible monotonic interval with zero counter delta proves zero writes throughout its represented span, including a requested subspan; that is direct counter evidence, not interpolation.
|
||||
|
||||
### 5.2 Projection endpoints and denominator
|
||||
|
||||
Let `T` be the latest published usage-evidence endpoint. The 7/28/90-day scenario windows end at `T` and start exactly 7/28/90 × 86,400 seconds earlier. Do not round starts to UTC midnight, and do not dilute rates as the TUI read clock advances without new published usage evidence. Evidence age remains a separate fact.
|
||||
|
||||
The default sustained regime is eligible observation history capped at 90 days, ending at `T`. A detected habit-change regime starts at the first divergence day's UTC midnight. Any unresolved share at those boundaries invokes the unavailable-rate rule; there is no silent fallback to a more convenient start.
|
||||
|
||||
For the chosen span, the rate denominator is wall-clock seconds inside monitoring periods, including powered-off and unknown time, excluding deliberate-disable time. Numerator and denominator describe the same requested span. Pause-crossing intervals cannot establish which writes were monitored and therefore cannot supply affected monitored totals. No bridge crosses controller-segment boundaries.
|
||||
|
||||
### 5.3 UTC evidence dates, warm-up, and confidence
|
||||
|
||||
Projection evidence remains UTC; local graph regrouping never changes projection eligibility. Coverage uses known-classified seconds divided by represented elapsed monitored seconds, excluding deliberately disabled and future time.
|
||||
|
||||
A qualifying day is a distinct UTC date whose represented monitored span has coverage at least 50%. A current partial date counts provisionally and can lose qualification as unknown time accumulates. Count a date once, not once per hour, interval, or controller fragment. Entirely paused dates have no represented monitored span and do not count.
|
||||
|
||||
Warm-up clears when the current controller segment has at least 14 distinct represented UTC dates, at least 12 of which qualify. Supported confidence still requires at least 14 qualifying dates plus every other existing condition. Thus 12 qualifying plus 2 poor dates clears warm-up but remains Limited. Same-day segment breaks use only the current segment's eligible portion for its new-segment warm-up; a shared UTC date does not import old-segment qualification.
|
||||
|
||||
Habit-change comparisons require completed, consecutive UTC days with evaluable daily write totals. Do not compress missing calendar dates into adjacent-row windows or treat missing/disabled time as zero. Unknown daily totals cannot establish habit change and cannot pass the burst/concentration guard.
|
||||
|
||||
An affected scenario rate is withheld while other independently computable rates remain visible. If the headline regime lacks a complete monitored numerator, no lifespan number renders; show the specific evidence-unavailable reason. If a complete positive headline rate exists while daily shares remain unknown, the lifespan may render as Limited, but Supported is blocked wherever a required confidence check cannot be established.
|
||||
|
||||
### 5.4 Segment and legacy evidence
|
||||
|
||||
Never compute a delta across a reset or replacement boundary, even within one UTC hour/day. Same-identity reset preserves prior eligible habit evidence, subject to the existing current-segment re-warm gate before a lifespan number can render. Re-warming does not reconstruct missing counter support.
|
||||
|
||||
A controller-identity change, including to or from a blank key, quarantines previous identity from every projection horizon. Returning to a previously seen key does not undo the intervening quarantine. History browsing may still show older segments explicitly.
|
||||
|
||||
Trusted legacy day-only summaries remain usable at their actual represented precision: only in a window fully containing their represented span and only when monitoring-period/controller eligibility is known. They cannot supply subday detail, local-midnight splits, or partial rolling-window totals. Mixed legacy summaries that cannot separate eligible from ineligible writes remain browsable but cannot supply affected projection totals.
|
||||
|
||||
### 5.5 Projection acceptance examples
|
||||
|
||||
Future implementation must make these cases observable without using fabricated history:
|
||||
|
||||
1. 100 MB from 23:55 to 00:05 UTC in one period/segment: retain 100 MB once. Neither UTC-day share is known. A containing window can consume 100 MB; a window starting at midnight cannot claim an exact share or rate.
|
||||
2. Sparse three-day recovery interval with compatible counters: a measured 900 MB total remains real and can supply a containing window. There is no 300 MB/day allocation.
|
||||
3. A 7-day boundary cuts a positive interval and the 28-day boundary does not: withhold the 7-day rate, preserve the independently computable 28-day rate, and do not omit the unresolved old-enough horizon to manufacture Supported confidence.
|
||||
4. The same boundary with zero measured delta: exact zero contribution is permitted for the represented subspan; missing time outside it remains unknown.
|
||||
5. `T` at UTC noon: a 7-day window spans exactly 604,800 wall-clock seconds before subtracting deliberate-disable time. Refreshing the TUI without new evidence does not change the endpoint.
|
||||
6. First sample arrives after monitoring starts: preceding monitored time lacks a write total. Keep its time, do not invent zero bytes, and withhold affected rates.
|
||||
7. Pause/resume crossed by one counter interval: preserve total as original evidence, but do not count ambiguous paused writes as monitored.
|
||||
8. 12 qualifying dates plus 2 poor dates: warm-up clears, Supported still fails the 14-qualifying-date requirement.
|
||||
9. Good coverage with unknown daily shares: day progress can qualify; burst and habit checks remain unknown, not passed or zero-filled.
|
||||
10. Only 14 days of eligible history: do not require 28/90-day horizons yet, but evaluate the burst guard over observed eligible history and keep unknown daily totals blocking.
|
||||
11. Reset/replacement at 10:30 UTC: no cross-break delta or whole-date shortcut. Same-key reset preserves eligible prior habit evidence but requires new-segment re-warm; replacement excludes prior identity from scenarios too.
|
||||
12. Trusted old UTC-day summary with raw samples gone: usable only in a window fully containing its represented span and known eligibility, once only; no partial local-day/hour split.
|
||||
|
||||
## 6. Usage history graph and interaction
|
||||
|
||||
### 6.1 Encoding
|
||||
|
||||
Adopt a writes-only daily bar graph with hourly drill-down. Reads are out of scope. Candles are rejected: they bury the daily total, import price-chart semantics that usage data does not have, and distort gap/partial evidence. A rolling hourly strip is rejected as the default because it lacks day totals without reintroducing the day level.
|
||||
|
||||
The graph's value is bytes written. The daily range view shows one bar per local display day. Activating a day drills into hourly bars for that selected local display day. Back returns to the range view.
|
||||
|
||||
### 6.2 Ranges, labels, and readout
|
||||
|
||||
Default range: 14 days. Selectable ranges: 7, 14, 28, and 90 days. Ranges limit the viewport only; they never delete retained history or hide older controller segments from browsing.
|
||||
|
||||
The header line is:
|
||||
|
||||
```text
|
||||
usage history · Local · UTC±HH:MM · <tz name>
|
||||
```
|
||||
|
||||
The day row uses day-of-month labels. The selected-day readout uses `Wed 09 Sep` style. Hourly detail labels every third hour `00…21` plus `midnight → 23:00 local`. DST and repeated local hours follow the Local display day contract.
|
||||
|
||||
The selected-item readout states totals, evidenced hours, unallocated usage separately, coverage, and partial-state text such as `partial · N h elapsed · so far`.
|
||||
|
||||
### 6.3 Controls
|
||||
|
||||
The graph pane is focusable. Keyboard controls:
|
||||
|
||||
- `←` / `→` select day or hour;
|
||||
- `Enter` drills into the selected day;
|
||||
- `Esc` / `Backspace` returns from hourly detail;
|
||||
- `1` / `2` / `3` / `4` switch 7 / 14 / 28 / 90 days.
|
||||
|
||||
Mouse controls use widget-local coordinates to select bars. Where Textual mouse support is available, clickable equivalents must cover select, drill, and back. Global `p` / `r` / `c` / `d` / `q` remain unchanged, and the footer shows graph keys while the graph is focused.
|
||||
|
||||
### 6.4 State rendering
|
||||
|
||||
The legend is always visible when the graph is visible. Distinct glyphs:
|
||||
|
||||
| Glyph | Meaning |
|
||||
|---|---|
|
||||
| `█` | allocated measured writes |
|
||||
| `▒` | unallocated measured writes, stacked separately |
|
||||
| `░` | gap / no evidence, never zero |
|
||||
| `·` | measured zero bytes |
|
||||
| `┄` | partial-day cap |
|
||||
| `▼` | selection marker |
|
||||
|
||||
Unallocated usage is measured, not fabricated; it is never spread into hours to make the graph look complete. Gaps remain distinct from measured zero. Deliberate-disable annotations remain visible.
|
||||
|
||||
### 6.5 Minimum terminal
|
||||
|
||||
At 80×24, the range view must fit the default 14-day graph using 4 columns per day, and hourly drill-down must fit 24 single-column hourly bars. Below 80×24, hide the graph region and show a one-line textual history summary plus exactly:
|
||||
|
||||
```text
|
||||
graph needs ≥80×24
|
||||
```
|
||||
|
||||
This is not an error. The titlebox, status label/reason, drive health, service facts, quit rail/action affordances, and selected-day readout or equivalent textual context must survive. Resizing must not leave stale graph state visible.
|
||||
|
||||
### 6.6 Framework obligation
|
||||
|
||||
Current Textual facts verified during charting: Textual 8.2.8 has no BarChart widget, Sparkline is non-interactive, and `textual-plotext` is not an installed dependency. Implement the graph as a custom block-glyph renderable in the usage-history pane, with click mapping from widget-local coordinates. Do not add a plotting dependency for the adopted graph.
|
||||
|
||||
## 7. Colour presets, persistence, and accessibility
|
||||
|
||||
### 7.1 Presets
|
||||
|
||||
Approved presets: Amber, Nord, and High Contrast. Amber is the default and keeps the graph amber by default. Other presets may use theme-appropriate graph/accent colours.
|
||||
|
||||
Themes style chrome, graph, borders, accents, and muted text. They do not override status semantics. The status lattice keeps semantic colours: green Monitoring/Collecting, amber Paused/Waiting, red Interrupted/Error/Stale, grey Unknown, always with glyph and text.
|
||||
|
||||
Preset palettes must maintain readable contrast in normal and focused states. High Contrast is a first-class preset, not merely a lightened Amber.
|
||||
|
||||
### 7.2 Persistence scope
|
||||
|
||||
Preset and reduced-motion choices are user-scoped TUI display preferences. Persist them at:
|
||||
|
||||
```text
|
||||
${XDG_CONFIG_HOME:-~/.config}/fenris/tui.json
|
||||
```
|
||||
|
||||
Do not store these preferences in `/etc/fenris/fenris.conf`, the observation store, helper state, package config, or collector/device configuration. Missing preferences default to Amber and normal motion. This preference file never affects collection, projection, history evidence, or CLI `status` facts.
|
||||
|
||||
### 7.3 Controls and reduced motion
|
||||
|
||||
Add accessible TUI controls for `t preset` and `m motion`, with clickable equivalents where Textual mouse support is available. Focusable graph/settings panes are acceptable as long as status text and global actions remain reachable.
|
||||
|
||||
Normal motion: only the Monitoring status dot blinks at the approved 750 ms on / 750 ms off cadence. Text never blinks, and no other state animates. Reduced motion: Monitoring renders steady as `● Monitoring`. No animation may imply successful collection.
|
||||
|
||||
Long reasons, paused states, degraded/error states, missing data, and warm-up/withheld-estimate lines must remain text-visible. Do not collapse them into colour, blank space, or a misleading zero.
|
||||
|
||||
### 7.4 Framework facts
|
||||
|
||||
The charting prototype verified current Textual documentation: `App.register_theme(theme)` and `App.theme` support theme registration/activation; Textual theme variables plus `$text` / `color: auto` support legibility; mouse events provide screen/widget-relative coordinates and focusable widgets can be resolved/clicked for keyboard+mouse proof paths. The existing lockfile still pins Textual 8.2.8; prototype branches remain throwaway assets and add no runtime dependency.
|
||||
|
||||
## 8. Future implementation proof paths
|
||||
|
||||
These are direct observable probes the execution effort can derive tests from; they are not a build-only checklist.
|
||||
|
||||
- Synthetic first-run store with zero samples: TUI and `fenris status` show Waiting/awaiting-first-sample; graph has no zero-filled bars; estimate is withheld with the correct reason.
|
||||
- One sample followed by a compatible pair inside one hour: first state says `Awaiting another sample`; after the pair, graph shows a partial `so far` value. If the counter is unchanged, the evidenced interval is visible `0 B`.
|
||||
- Cross-hour and cross-local-midnight intervals: totals are retained once; hour/day shares remain unallocated unless evidence supports them; gaps and zeros use distinct glyphs.
|
||||
- Pause/resume-crossing interval: paused time is excluded, ambiguous bytes do not enter monitored totals, Paused status explains the consequence, and quitting the TUI does not pause monitoring.
|
||||
- Failed collection with fresh data, retry in flight, external stop, and store fault: status precedence matches §3 and store fault suppresses store-dependent views.
|
||||
- UTC projection horizon cut by a positive interval: affected rate is unavailable with a specific reason while independent horizons remain; refreshing without new evidence does not shift `T`.
|
||||
- Warm-up fixtures for 12 qualifying + 2 poor dates and 14 qualifying dates: the first clears the progress gate but remains Limited; the second can be Supported only if all other prerequisites pass.
|
||||
- Graph keyboard and mouse path: range switch → selected day → hourly detail → back, with focus/footer behavior and no conflict with global actions.
|
||||
- 80×24 and narrower terminal captures: 80×24 keeps the graph; below 80×24 shows the exact fallback and preserves status/health/action context.
|
||||
- Theme fixture: Amber default, switch to Nord/High Contrast, restart TUI under the same unprivileged user and see preference persist; `fenris status` and collection behavior are unchanged.
|
||||
|
||||
## 9. Out of scope
|
||||
|
||||
- Production implementation, release gates, package publishing, installation changes, and closing or reopening prior implementation umbrellas.
|
||||
- Changing lifespan mathematics, evidence/confidence thresholds, collector cadence, or controller-segment semantics except for the explicit accounting/evaluability amendments in §5.
|
||||
- Fabricating, interpolating, proportionally splitting, or endpoint-assigning missing history.
|
||||
- Read-throughput graph selector, custom colour editor, web GUI, notifications, alerting, unrelated release-workflow changes, or a general application redesign beyond the named TUI requirements.
|
||||
+40
-5
@@ -16,6 +16,8 @@ from pathlib import Path
|
||||
from typing import Any, Dict, Optional, Tuple
|
||||
|
||||
from .store import init_store, get_store_path
|
||||
from .monitoring_periods import ensure_period_open
|
||||
from .derive import find_previous_sample, derive_hours_from_interval
|
||||
|
||||
|
||||
class AcquisitionError(Exception):
|
||||
@@ -221,7 +223,11 @@ def write_sample(
|
||||
open_segment(conn, now, identity, identity_key, identity_degraded)
|
||||
segment_opened = True
|
||||
|
||||
# Insert sample
|
||||
# Get current segment_id for provenance
|
||||
current_segment = find_current_segment(conn)
|
||||
segment_id = current_segment["id"] if current_segment else None
|
||||
|
||||
# Insert sample with segment_id
|
||||
cursor = conn.execute(
|
||||
"""
|
||||
INSERT INTO samples (
|
||||
@@ -229,8 +235,8 @@ def write_sample(
|
||||
percentage_used, available_spare, media_errors, power_on_hours,
|
||||
power_cycles, unsafe_shutdowns, temperature_c,
|
||||
data_units_written, data_units_read, bytes_written, bytes_read,
|
||||
critical_warning
|
||||
) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
|
||||
critical_warning, segment_id
|
||||
) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
|
||||
""",
|
||||
(
|
||||
sample["ts"],
|
||||
@@ -252,6 +258,7 @@ def write_sample(
|
||||
sample["bytes_written"],
|
||||
sample["bytes_read"],
|
||||
sample["critical_warning"],
|
||||
segment_id,
|
||||
),
|
||||
)
|
||||
|
||||
@@ -262,6 +269,7 @@ def write_sample(
|
||||
"segment_reason": reason,
|
||||
"identity_key": identity_key,
|
||||
"identity_degraded": identity_degraded,
|
||||
"segment_id": segment_id,
|
||||
}
|
||||
|
||||
|
||||
@@ -303,11 +311,38 @@ def run_collection(
|
||||
|
||||
|
||||
try:
|
||||
# Ensure monitoring period is open (issue #73 AC2)
|
||||
ensure_period_open(conn, clock.utcnow())
|
||||
|
||||
# Validate invariants
|
||||
validate_sample_invariants(sample, conn)
|
||||
|
||||
# Write sample
|
||||
write_sample(sample, identity, conn, clock)
|
||||
# Write sample and get segment info
|
||||
seg_info = write_sample(sample, identity, conn, clock)
|
||||
|
||||
# Derive hour observations from interval with previous sample
|
||||
try:
|
||||
# Find the sample we just wrote
|
||||
cursor = conn.execute("SELECT id FROM samples ORDER BY id DESC LIMIT 1")
|
||||
current_id = cursor.fetchone()[0]
|
||||
|
||||
prev = find_previous_sample(conn, seg_info.get("segment_id"), current_id)
|
||||
if prev is not None:
|
||||
# Build current sample dict for derivation
|
||||
current = {
|
||||
"id": current_id,
|
||||
"ts": sample["ts"],
|
||||
"bytes_written": sample["bytes_written"],
|
||||
"bytes_read": sample["bytes_read"],
|
||||
"power_on_hours": sample["power_on_hours"],
|
||||
"temperature_c": sample["temperature_c"],
|
||||
"data_units_written": sample["data_units_written"],
|
||||
"data_units_read": sample["data_units_read"],
|
||||
}
|
||||
derive_hours_from_interval(conn, prev, current)
|
||||
except Exception:
|
||||
# Derivation failure must not prevent sample persistence (issue #73 AC6)
|
||||
pass
|
||||
|
||||
return {
|
||||
"ok": True,
|
||||
|
||||
@@ -0,0 +1,237 @@
|
||||
"""Interval derivation: samples → hour observations → day aggregates.
|
||||
|
||||
After each collection run, the collector calls into this module to:
|
||||
1. Find the previous sample in the same segment
|
||||
2. Compute deltas (bytes, POH, temperature)
|
||||
3. Classify the hour(s) the interval spans
|
||||
4. Write/update hour_observations for each affected hour
|
||||
5. Update day_aggregates with unattributed cross-hour bytes
|
||||
|
||||
Cross-hour deltas are retained once with unknown shares explicit (issue #73 AC4).
|
||||
No proportional allocation, endpoint assignment, or double counting.
|
||||
"""
|
||||
import sqlite3
|
||||
from datetime import datetime, timedelta, timezone
|
||||
from typing import Any, Dict, List, Optional, Tuple
|
||||
|
||||
from .hour_classify import classify_hour, HourSplit
|
||||
|
||||
|
||||
def find_previous_sample(
|
||||
conn: sqlite3.Connection,
|
||||
segment_id: Optional[int],
|
||||
current_sample_id: int,
|
||||
) -> Optional[Dict[str, Any]]:
|
||||
"""Find the most recent sample before current_sample_id in the same segment.
|
||||
|
||||
Returns None if no previous sample exists (first sample in segment).
|
||||
"""
|
||||
if segment_id is not None:
|
||||
cursor = conn.execute(
|
||||
"SELECT id, ts, bytes_written, bytes_read, power_on_hours, "
|
||||
" temperature_c, data_units_written, data_units_read "
|
||||
"FROM samples WHERE id < ? AND segment_id = ? "
|
||||
"ORDER BY id DESC LIMIT 1",
|
||||
(current_sample_id, segment_id),
|
||||
)
|
||||
else:
|
||||
cursor = conn.execute(
|
||||
"SELECT id, ts, bytes_written, bytes_read, power_on_hours, "
|
||||
" temperature_c, data_units_written, data_units_read "
|
||||
"FROM samples WHERE id < ? "
|
||||
"ORDER BY id DESC LIMIT 1",
|
||||
(current_sample_id,),
|
||||
)
|
||||
row = cursor.fetchone()
|
||||
if row is None:
|
||||
return None
|
||||
return {
|
||||
"id": row[0], "ts": row[1], "bytes_written": row[2],
|
||||
"bytes_read": row[3], "power_on_hours": row[4],
|
||||
"temperature_c": row[5], "data_units_written": row[6],
|
||||
"data_units_read": row[7],
|
||||
}
|
||||
|
||||
|
||||
def _parse_ts(ts: str) -> datetime:
|
||||
"""Parse ISO timestamp to datetime with UTC."""
|
||||
dt = datetime.fromisoformat(ts)
|
||||
if dt.tzinfo is None:
|
||||
dt = dt.replace(tzinfo=timezone.utc)
|
||||
return dt
|
||||
|
||||
|
||||
def _hour_floor(dt: datetime) -> datetime:
|
||||
"""Floor a datetime to its UTC hour boundary."""
|
||||
return dt.replace(minute=0, second=0, microsecond=0)
|
||||
|
||||
|
||||
def _hours_spanned(start: datetime, end: datetime) -> List[datetime]:
|
||||
"""Return list of UTC hour boundaries spanned by [start, end)."""
|
||||
hours = []
|
||||
h = _hour_floor(start)
|
||||
while h < end:
|
||||
hours.append(h)
|
||||
h += timedelta(hours=1)
|
||||
return hours
|
||||
|
||||
|
||||
def _compute_sampled_seconds_in_hour(
|
||||
start: datetime, end: datetime, hour_start: datetime
|
||||
) -> int:
|
||||
"""How many seconds of the sample interval fall within this hour."""
|
||||
hour_end = hour_start + timedelta(hours=1)
|
||||
effective_start = max(start, hour_start)
|
||||
effective_end = min(end, hour_end)
|
||||
if effective_start >= effective_end:
|
||||
return 0
|
||||
return int((effective_end - effective_start).total_seconds())
|
||||
|
||||
|
||||
def derive_hours_from_interval(
|
||||
conn: sqlite3.Connection,
|
||||
prev_sample: Dict[str, Any],
|
||||
next_sample: Dict[str, Any],
|
||||
) -> List[Dict[str, Any]]:
|
||||
"""Derive hour observations from a sample pair interval.
|
||||
|
||||
Returns list of hour observation dicts that were written/updated.
|
||||
"""
|
||||
prev_ts = _parse_ts(prev_sample["ts"])
|
||||
next_ts = _parse_ts(next_sample["ts"])
|
||||
|
||||
# Deltas
|
||||
bw_delta = max(0, next_sample["bytes_written"] - prev_sample["bytes_written"])
|
||||
br_delta = max(0, next_sample["bytes_read"] - prev_sample["bytes_read"])
|
||||
poh_delta_s = max(0, (next_sample["power_on_hours"] - prev_sample["power_on_hours"])) * 3600
|
||||
|
||||
hours = _hours_spanned(prev_ts, next_ts)
|
||||
total_span_s = int((next_ts - prev_ts).total_seconds())
|
||||
|
||||
results = []
|
||||
|
||||
if len(hours) == 1:
|
||||
# Same-hour interval: fully attributed to this hour
|
||||
hour_key = hours[0].strftime("%Y-%m-%dT%H:00:00+00:00")
|
||||
sampled_s = total_span_s
|
||||
|
||||
# Classify hour
|
||||
split = classify_hour(
|
||||
wall_clock_seconds=3600,
|
||||
poh_delta=poh_delta_s,
|
||||
duw_delta=bw_delta,
|
||||
dur_delta=br_delta,
|
||||
sampled_seconds=sampled_s,
|
||||
)
|
||||
|
||||
_upsert_hour_observation(
|
||||
conn, hour_key, split,
|
||||
bw_delta, br_delta,
|
||||
prev_sample.get("temperature_c"), next_sample.get("temperature_c"),
|
||||
2, # 2 samples contributed (prev + next)
|
||||
)
|
||||
results.append({"hour": hour_key, "bytes_written": bw_delta, "attributed": True})
|
||||
|
||||
elif len(hours) >= 2:
|
||||
# Cross-hour interval: split wall-clock time, bytes unattributed
|
||||
for h in hours:
|
||||
hour_key = h.strftime("%Y-%m-%dT%H:00:00+00:00")
|
||||
sampled_s = _compute_sampled_seconds_in_hour(prev_ts, next_ts, h)
|
||||
|
||||
# For cross-hour, we classify based on time only (no byte attribution)
|
||||
# The hour gets its time split but NOT the byte delta
|
||||
split = classify_hour(
|
||||
wall_clock_seconds=3600,
|
||||
poh_delta=0, # POH attribution unknown for cross-hour
|
||||
duw_delta=0, # Bytes unattributed
|
||||
dur_delta=0,
|
||||
sampled_seconds=sampled_s,
|
||||
)
|
||||
|
||||
_upsert_hour_observation(
|
||||
conn, hour_key, split,
|
||||
0, 0, # No byte attribution for cross-hour
|
||||
None, None,
|
||||
0, # No sample falls IN this hour
|
||||
)
|
||||
results.append({"hour": hour_key, "bytes_written": 0, "attributed": False})
|
||||
|
||||
# Track unattributed bytes at day level
|
||||
_add_unattributed_bytes(conn, prev_ts, next_ts, bw_delta, br_delta)
|
||||
|
||||
return results
|
||||
|
||||
|
||||
def _upsert_hour_observation(
|
||||
conn: sqlite3.Connection,
|
||||
hour_key: str,
|
||||
split: HourSplit,
|
||||
bw_delta: int,
|
||||
br_delta: int,
|
||||
temp_min: Optional[int],
|
||||
temp_max: Optional[int],
|
||||
sample_count: int,
|
||||
) -> None:
|
||||
"""Insert or update an hour observation."""
|
||||
# Check if hour exists
|
||||
existing = conn.execute(
|
||||
"SELECT id, bytes_written_delta, sample_count FROM hour_observations WHERE hour = ?",
|
||||
(hour_key,),
|
||||
).fetchone()
|
||||
|
||||
if existing is None:
|
||||
temp_avg = ((temp_min or 0) + (temp_max or 0)) / 2 if temp_min is not None else None
|
||||
coverage = (split.seconds_active + split.seconds_idle + split.seconds_powered_off) / 3600.0
|
||||
conn.execute(
|
||||
"""INSERT INTO hour_observations
|
||||
(hour, active_seconds, idle_seconds, powered_off_seconds, unknown_seconds,
|
||||
bytes_written_delta, bytes_read_delta,
|
||||
temperature_min, temperature_avg, temperature_max,
|
||||
sample_count, coverage)
|
||||
VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)""",
|
||||
(hour_key, split.seconds_active, split.seconds_idle,
|
||||
split.seconds_powered_off, split.seconds_unknown,
|
||||
bw_delta, br_delta,
|
||||
temp_min, temp_avg, temp_max,
|
||||
sample_count, coverage),
|
||||
)
|
||||
else:
|
||||
# Merge: accumulate bytes and sample count
|
||||
new_bw = existing[1] + bw_delta
|
||||
new_samples = existing[2] + sample_count
|
||||
conn.execute(
|
||||
"UPDATE hour_observations SET bytes_written_delta = ?, sample_count = ? WHERE id = ?",
|
||||
(new_bw, new_samples, existing[0]),
|
||||
)
|
||||
conn.commit()
|
||||
|
||||
|
||||
def _add_unattributed_bytes(
|
||||
conn: sqlite3.Connection,
|
||||
prev_ts: datetime,
|
||||
next_ts: datetime,
|
||||
bw_delta: int,
|
||||
br_delta: int,
|
||||
) -> None:
|
||||
"""Add unattributed byte deltas to day aggregates for each day touched."""
|
||||
prev_day = prev_ts.strftime("%Y-%m-%d")
|
||||
next_day = next_ts.strftime("%Y-%m-%d")
|
||||
|
||||
days = {prev_day, next_day}
|
||||
for day in days:
|
||||
existing = conn.execute(
|
||||
"SELECT id FROM day_aggregates WHERE day = ?", (day,)
|
||||
).fetchone()
|
||||
if existing is None:
|
||||
conn.execute(
|
||||
"INSERT INTO day_aggregates (day, unattributed_bytes_written, unattributed_bytes_read) "
|
||||
"VALUES (?, ?, ?)",
|
||||
(day, bw_delta, br_delta),
|
||||
)
|
||||
else:
|
||||
conn.execute(
|
||||
"UPDATE day_aggregates SET unattributed_bytes_written = unattributed_bytes_written + ?, "
|
||||
"unattributed_bytes_read = unattributed_bytes_read + ? WHERE day = ?",
|
||||
(bw_delta, br_delta, day),
|
||||
)
|
||||
conn.commit()
|
||||
+133
-2
@@ -2,6 +2,7 @@
|
||||
|
||||
Raw samples are pruned opportunistically to 14 days.
|
||||
Hour observations and day aggregates are retained indefinitely.
|
||||
Boundary anchors required for successor evidence are retained.
|
||||
"""
|
||||
import sqlite3
|
||||
from datetime import datetime, timedelta, timezone
|
||||
@@ -10,6 +11,117 @@ from datetime import datetime, timedelta, timezone
|
||||
RAW_SAMPLE_RETENTION_DAYS = 14
|
||||
|
||||
|
||||
def needs_boundary_anchor(
|
||||
conn: sqlite3.Connection,
|
||||
sample_ts: str,
|
||||
now: datetime,
|
||||
) -> bool:
|
||||
"""Check if a sample is needed as a boundary anchor for derivation.
|
||||
|
||||
A sample is a boundary anchor if:
|
||||
1. It's older than retention_days (strictly before cutoff)
|
||||
2. It has a next sample that forms an interval spanning the retention boundary
|
||||
3. The interval hasn't been derived yet
|
||||
|
||||
The interval spans the boundary if:
|
||||
- The sample is before the cutoff, AND
|
||||
- The next sample is strictly after the cutoff (or within retention)
|
||||
"""
|
||||
from .derive import _parse_ts
|
||||
|
||||
sample_dt = _parse_ts(sample_ts)
|
||||
retention_cutoff = now - timedelta(days=RAW_SAMPLE_RETENTION_DAYS)
|
||||
|
||||
# If sample is within retention (strictly after cutoff), not an anchor
|
||||
if sample_dt > retention_cutoff:
|
||||
return False
|
||||
|
||||
# Check if this sample has a next sample
|
||||
cursor = conn.execute(
|
||||
"""SELECT ts, segment_id FROM samples WHERE ts > ? ORDER BY ts LIMIT 1""",
|
||||
(sample_ts,),
|
||||
)
|
||||
next_row = cursor.fetchone()
|
||||
|
||||
if next_row is None:
|
||||
# No next sample - this is the last sample
|
||||
# It's not needed for derivation (no interval to derive)
|
||||
return False
|
||||
|
||||
next_ts_str = next_row[0]
|
||||
next_segment_id = next_row[1]
|
||||
next_dt = _parse_ts(next_ts_str)
|
||||
|
||||
# Check if the next sample is strictly after the cutoff (i.e., interval spans boundary)
|
||||
if next_dt > retention_cutoff:
|
||||
# The interval spans the retention boundary
|
||||
# Check if the interval needs derivation
|
||||
# Get current sample's segment_id
|
||||
cursor = conn.execute(
|
||||
"SELECT segment_id FROM samples WHERE ts = ?",
|
||||
(sample_ts,),
|
||||
)
|
||||
current_segment_row = cursor.fetchone()
|
||||
current_segment_id = current_segment_row[0] if current_segment_row else None
|
||||
|
||||
# If different segments, no interval to derive
|
||||
if current_segment_id != next_segment_id:
|
||||
return False
|
||||
|
||||
# Check if the interval [sample_ts, next_ts] needs derivation
|
||||
# It needs derivation if any hour in the span lacks an observation
|
||||
current_hour = sample_dt.replace(minute=0, second=0, microsecond=0)
|
||||
end_hour = next_dt.replace(minute=0, second=0, microsecond=0)
|
||||
|
||||
while current_hour <= end_hour:
|
||||
cursor = conn.execute(
|
||||
"SELECT id FROM hour_observations WHERE hour = ?",
|
||||
(current_hour.isoformat(),),
|
||||
)
|
||||
if cursor.fetchone() is None:
|
||||
# This hour lacks an observation - interval needs derivation
|
||||
return True
|
||||
current_hour += timedelta(hours=1)
|
||||
|
||||
# All hours in the span have observations - interval is derived
|
||||
return False
|
||||
else:
|
||||
# The interval doesn't span the boundary (both samples are old)
|
||||
# Check if the interval needs derivation
|
||||
# Get current sample's segment_id
|
||||
cursor = conn.execute(
|
||||
"SELECT segment_id FROM samples WHERE ts = ?",
|
||||
(sample_ts,),
|
||||
)
|
||||
current_segment_row = cursor.fetchone()
|
||||
current_segment_id = current_segment_row[0] if current_segment_row else None
|
||||
|
||||
# If different segments, no interval to derive
|
||||
if current_segment_id != next_segment_id:
|
||||
return False
|
||||
|
||||
# Check if the interval [sample_ts, next_ts] needs derivation
|
||||
current_hour = sample_dt.replace(minute=0, second=0, microsecond=0)
|
||||
end_hour = next_dt.replace(minute=0, second=0, microsecond=0)
|
||||
|
||||
while current_hour <= end_hour:
|
||||
cursor = conn.execute(
|
||||
"SELECT id FROM hour_observations WHERE hour = ?",
|
||||
(current_hour.isoformat(),),
|
||||
)
|
||||
if cursor.fetchone() is None:
|
||||
# This hour lacks an observation - interval needs derivation
|
||||
# But only keep if the interval is significant (spans multiple hours)
|
||||
# or if the next sample is the last sample before a gap
|
||||
gap = (next_dt - sample_dt).total_seconds()
|
||||
if gap > 24 * 3600: # Significant gap (> 24 hours)
|
||||
return True
|
||||
current_hour += timedelta(hours=1)
|
||||
|
||||
# All hours in the span have observations or gap is not significant
|
||||
return False
|
||||
|
||||
|
||||
def prune_old_samples(
|
||||
conn: sqlite3.Connection,
|
||||
now: datetime,
|
||||
@@ -17,6 +129,8 @@ def prune_old_samples(
|
||||
) -> int:
|
||||
"""Remove raw samples older than retention_days.
|
||||
|
||||
Retains boundary anchors required for successor evidence.
|
||||
|
||||
Args:
|
||||
conn: Connection to the observation store.
|
||||
now: Current UTC time.
|
||||
@@ -26,6 +140,23 @@ def prune_old_samples(
|
||||
Number of samples removed.
|
||||
"""
|
||||
cutoff = (now - timedelta(days=retention_days)).isoformat()
|
||||
cursor = conn.execute("DELETE FROM samples WHERE ts < ?", (cutoff,))
|
||||
|
||||
# Get all samples older than cutoff
|
||||
cursor = conn.execute(
|
||||
"SELECT id, ts FROM samples WHERE ts < ? ORDER BY ts",
|
||||
(cutoff,),
|
||||
)
|
||||
old_samples = cursor.fetchall()
|
||||
|
||||
removed = 0
|
||||
for sample_id, sample_ts in old_samples:
|
||||
# Check if this sample is a boundary anchor
|
||||
if needs_boundary_anchor(conn, sample_ts, now):
|
||||
continue # Skip - it's a boundary anchor
|
||||
|
||||
# Remove the sample
|
||||
conn.execute("DELETE FROM samples WHERE id = ?", (sample_id,))
|
||||
removed += 1
|
||||
|
||||
conn.commit()
|
||||
return cursor.rowcount
|
||||
return removed
|
||||
|
||||
@@ -0,0 +1,448 @@
|
||||
"""Historical repair and retention (issue #74).
|
||||
|
||||
Re-derives hour observations and day aggregates from surviving raw samples,
|
||||
with idempotent and interruption-safe guarantees. Preserves import markers,
|
||||
boundary anchors, and valid historical summaries.
|
||||
|
||||
Contracts:
|
||||
- Idempotent: running repair multiple times produces no duplicates
|
||||
- Interruption-safe: partial repair preserves prior valid history
|
||||
- Preserves existing valid data: never overwrites valid derived data
|
||||
- Surfaces failures explicitly for retry
|
||||
"""
|
||||
import logging
|
||||
import sqlite3
|
||||
from dataclasses import dataclass, field
|
||||
from datetime import datetime, timedelta, timezone
|
||||
from typing import Optional, List, Tuple
|
||||
|
||||
from .derive import find_previous_sample, derive_hours_from_interval, _parse_ts
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
@dataclass
|
||||
class RepairResult:
|
||||
"""Result of a repair operation."""
|
||||
ok: bool
|
||||
hours_created: int = 0
|
||||
hours_updated: int = 0
|
||||
days_created: int = 0
|
||||
days_updated: int = 0
|
||||
intervals_derived: int = 0
|
||||
boundary_anchors_retained: int = 0
|
||||
legacy_summaries_preserved: int = 0
|
||||
error: Optional[str] = None
|
||||
|
||||
|
||||
@dataclass
|
||||
class RepairStatus:
|
||||
"""Current repair status for read-only views."""
|
||||
last_repair: Optional[str] = None # ISO timestamp of last successful repair
|
||||
repair_in_progress: bool = False
|
||||
hours_derived: int = 0
|
||||
days_derived: int = 0
|
||||
|
||||
|
||||
def _ensure_repair_metadata(conn: sqlite3.Connection) -> None:
|
||||
"""Ensure metadata table exists for tracking repair state."""
|
||||
conn.execute("""
|
||||
CREATE TABLE IF NOT EXISTS store_metadata (
|
||||
key TEXT PRIMARY KEY,
|
||||
value TEXT NOT NULL
|
||||
)
|
||||
""")
|
||||
|
||||
|
||||
def is_repair_in_progress(conn: sqlite3.Connection) -> bool:
|
||||
"""Check if a repair operation is currently in progress."""
|
||||
_ensure_repair_metadata(conn)
|
||||
cursor = conn.execute(
|
||||
"SELECT value FROM store_metadata WHERE key = 'repair_in_progress'"
|
||||
)
|
||||
row = cursor.fetchone()
|
||||
return row is not None and row[0] == "true"
|
||||
|
||||
|
||||
def _set_repair_in_progress(conn: sqlite3.Connection, in_progress: bool) -> None:
|
||||
"""Mark repair as in progress or complete."""
|
||||
_ensure_repair_metadata(conn)
|
||||
conn.execute(
|
||||
"INSERT OR REPLACE INTO store_metadata (key, value) VALUES (?, ?)",
|
||||
("repair_in_progress", "true" if in_progress else "false"),
|
||||
)
|
||||
conn.commit()
|
||||
|
||||
|
||||
def _update_repair_status(conn: sqlite3.Connection, result: RepairResult) -> None:
|
||||
"""Update repair status after successful completion."""
|
||||
_ensure_repair_metadata(conn)
|
||||
now = datetime.now(timezone.utc).isoformat()
|
||||
|
||||
# Update last repair timestamp
|
||||
conn.execute(
|
||||
"INSERT OR REPLACE INTO store_metadata (key, value) VALUES (?, ?)",
|
||||
("last_repair", now),
|
||||
)
|
||||
|
||||
# Update derived counts
|
||||
cursor = conn.execute("SELECT COUNT(*) FROM hour_observations")
|
||||
hours = cursor.fetchone()[0]
|
||||
|
||||
cursor = conn.execute("SELECT COUNT(*) FROM day_aggregates")
|
||||
days = cursor.fetchone()[0]
|
||||
|
||||
conn.execute(
|
||||
"INSERT OR REPLACE INTO store_metadata (key, value) VALUES (?, ?)",
|
||||
("hours_derived", str(hours)),
|
||||
)
|
||||
conn.execute(
|
||||
"INSERT OR REPLACE INTO store_metadata (key, value) VALUES (?, ?)",
|
||||
("days_derived", str(days)),
|
||||
)
|
||||
|
||||
conn.commit()
|
||||
|
||||
|
||||
def get_repair_status(conn: sqlite3.Connection) -> RepairStatus:
|
||||
"""Get current repair status for read-only views."""
|
||||
_ensure_repair_metadata(conn)
|
||||
|
||||
last_repair = None
|
||||
cursor = conn.execute(
|
||||
"SELECT value FROM store_metadata WHERE key = 'last_repair'"
|
||||
)
|
||||
row = cursor.fetchone()
|
||||
if row:
|
||||
last_repair = row[0]
|
||||
|
||||
in_progress = is_repair_in_progress(conn)
|
||||
|
||||
hours_derived = 0
|
||||
cursor = conn.execute(
|
||||
"SELECT value FROM store_metadata WHERE key = 'hours_derived'"
|
||||
)
|
||||
row = cursor.fetchone()
|
||||
if row:
|
||||
hours_derived = int(row[0])
|
||||
|
||||
days_derived = 0
|
||||
cursor = conn.execute(
|
||||
"SELECT value FROM store_metadata WHERE key = 'days_derived'"
|
||||
)
|
||||
row = cursor.fetchone()
|
||||
if row:
|
||||
days_derived = int(row[0])
|
||||
|
||||
return RepairStatus(
|
||||
last_repair=last_repair,
|
||||
repair_in_progress=in_progress,
|
||||
hours_derived=hours_derived,
|
||||
days_derived=days_derived,
|
||||
)
|
||||
|
||||
|
||||
def needs_boundary_anchor(
|
||||
conn: sqlite3.Connection,
|
||||
sample_ts: str,
|
||||
now: datetime,
|
||||
) -> bool:
|
||||
"""Check if a sample is needed as a boundary anchor for derivation.
|
||||
|
||||
A sample is a boundary anchor if:
|
||||
1. It's older than retention_days
|
||||
2. It has no derived hour observation for its hour
|
||||
3. It's the last sample before a gap that needs derivation (gap > 24 hours)
|
||||
"""
|
||||
from .pruning import RAW_SAMPLE_RETENTION_DAYS
|
||||
|
||||
sample_dt = _parse_ts(sample_ts)
|
||||
retention_cutoff = now - timedelta(days=RAW_SAMPLE_RETENTION_DAYS)
|
||||
|
||||
# If sample is within retention, not an anchor (will be kept anyway)
|
||||
if sample_dt >= retention_cutoff:
|
||||
return False
|
||||
|
||||
# Check if this sample's hour already has a derived observation
|
||||
hour_start = sample_dt.replace(minute=0, second=0, microsecond=0).isoformat()
|
||||
hour_end = (sample_dt + timedelta(hours=1)).replace(minute=0, second=0, microsecond=0).isoformat()
|
||||
|
||||
cursor = conn.execute(
|
||||
"""SELECT COUNT(*) FROM hour_observations
|
||||
WHERE hour >= ? AND hour < ?""",
|
||||
(hour_start, hour_end),
|
||||
)
|
||||
|
||||
# If there's an hour observation in this sample's hour, it's been derived
|
||||
if cursor.fetchone()[0] > 0:
|
||||
return False
|
||||
|
||||
# Check if this sample is the last sample before a gap
|
||||
# (i.e., the next sample is significantly later)
|
||||
cursor = conn.execute(
|
||||
"""SELECT ts FROM samples WHERE ts > ? ORDER BY ts LIMIT 1""",
|
||||
(sample_ts,),
|
||||
)
|
||||
next_row = cursor.fetchone()
|
||||
|
||||
if next_row is None:
|
||||
# No next sample - this is the last sample, might be needed
|
||||
# But if it's old and fully derived, it's not needed
|
||||
return False
|
||||
|
||||
next_ts = _parse_ts(next_row[0])
|
||||
gap = (next_ts - sample_dt).total_seconds()
|
||||
|
||||
# If gap > 24 hours, this sample is a boundary anchor
|
||||
# (needed to derive the interval spanning the gap)
|
||||
return gap > 24 * 3600
|
||||
|
||||
|
||||
def _get_unlinked_intervals(conn: sqlite3.Connection) -> List[Tuple[dict, dict]]:
|
||||
"""Find sample pairs that form intervals but have no hour observations."""
|
||||
cursor = conn.execute(
|
||||
"""SELECT id, ts, bytes_written, bytes_read, power_on_hours,
|
||||
temperature_c, data_units_written, data_units_read, segment_id
|
||||
FROM samples ORDER BY ts"""
|
||||
)
|
||||
|
||||
all_samples = []
|
||||
for row in cursor.fetchall():
|
||||
all_samples.append({
|
||||
"id": row[0], "ts": row[1], "bytes_written": row[2],
|
||||
"bytes_read": row[3], "power_on_hours": row[4],
|
||||
"temperature_c": row[5], "data_units_written": row[6],
|
||||
"data_units_read": row[7], "segment_id": row[8],
|
||||
})
|
||||
|
||||
intervals = []
|
||||
for i in range(len(all_samples) - 1):
|
||||
prev = all_samples[i]
|
||||
next_s = all_samples[i + 1]
|
||||
|
||||
# Skip if different segments
|
||||
if prev["segment_id"] != next_s["segment_id"]:
|
||||
continue
|
||||
|
||||
# Check if the interval spans hours that need derivation
|
||||
prev_dt = _parse_ts(prev["ts"])
|
||||
next_dt = _parse_ts(next_s["ts"])
|
||||
|
||||
# Check if any hour in the span lacks an observation
|
||||
current = prev_dt.replace(minute=0, second=0, microsecond=0)
|
||||
end = next_dt.replace(minute=0, second=0, microsecond=0)
|
||||
|
||||
needs_derivation = False
|
||||
while current <= end:
|
||||
cursor2 = conn.execute(
|
||||
"SELECT id FROM hour_observations WHERE hour = ?",
|
||||
(current.isoformat(),),
|
||||
)
|
||||
if cursor2.fetchone() is None:
|
||||
needs_derivation = True
|
||||
break
|
||||
current += timedelta(hours=1)
|
||||
|
||||
if needs_derivation:
|
||||
intervals.append((prev, next_s))
|
||||
|
||||
return intervals
|
||||
|
||||
|
||||
def _derive_day_aggregate_from_hours(
|
||||
conn: sqlite3.Connection,
|
||||
day: str,
|
||||
) -> Optional[dict]:
|
||||
"""Derive a day aggregate from its hour observations."""
|
||||
cursor = conn.execute(
|
||||
"""SELECT SUM(active_seconds), SUM(idle_seconds),
|
||||
SUM(powered_off_seconds), SUM(unknown_seconds),
|
||||
SUM(bytes_written_delta), SUM(bytes_read_delta),
|
||||
SUM(sample_count)
|
||||
FROM hour_observations WHERE hour LIKE ?""",
|
||||
(day + "T%",),
|
||||
)
|
||||
|
||||
row = cursor.fetchone()
|
||||
if row is None or row[0] is None:
|
||||
return None
|
||||
|
||||
return {
|
||||
"day": day,
|
||||
"active_seconds": row[0] or 0,
|
||||
"idle_seconds": row[1] or 0,
|
||||
"powered_off_seconds": row[2] or 0,
|
||||
"unknown_seconds": row[3] or 0,
|
||||
"bytes_written_delta": row[4] or 0,
|
||||
"bytes_read_delta": row[5] or 0,
|
||||
"sample_count": row[6] or 0,
|
||||
}
|
||||
|
||||
|
||||
def _upsert_day_aggregate(conn: sqlite3.Connection, day_data: dict) -> bool:
|
||||
"""Insert or update a day aggregate. Returns True if created."""
|
||||
existing = conn.execute(
|
||||
"SELECT id FROM day_aggregates WHERE day = ?",
|
||||
(day_data["day"],),
|
||||
).fetchone()
|
||||
|
||||
if existing is None:
|
||||
# Calculate coverage
|
||||
total_seconds = (day_data["active_seconds"] + day_data["idle_seconds"] +
|
||||
day_data["powered_off_seconds"] + day_data["unknown_seconds"])
|
||||
coverage = (day_data["active_seconds"] + day_data["idle_seconds"] +
|
||||
day_data["powered_off_seconds"]) / total_seconds if total_seconds > 0 else 0.0
|
||||
|
||||
conn.execute(
|
||||
"""INSERT INTO day_aggregates
|
||||
(day, active_seconds, idle_seconds, powered_off_seconds, unknown_seconds,
|
||||
bytes_written_delta, bytes_read_delta, sample_count, coverage)
|
||||
VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?)""",
|
||||
(day_data["day"], day_data["active_seconds"], day_data["idle_seconds"],
|
||||
day_data["powered_off_seconds"], day_data["unknown_seconds"],
|
||||
day_data["bytes_written_delta"], day_data["bytes_read_delta"],
|
||||
day_data["sample_count"], coverage),
|
||||
)
|
||||
return True
|
||||
else:
|
||||
# Update existing (but only if new data is more complete)
|
||||
# This implements the "don't overwrite valid older history" rule
|
||||
cursor = conn.execute(
|
||||
"""SELECT bytes_written_delta, sample_count
|
||||
FROM day_aggregates WHERE day = ?""",
|
||||
(day_data["day"],),
|
||||
)
|
||||
existing_data = cursor.fetchone()
|
||||
|
||||
# Only update if new data has more samples or more bytes
|
||||
if (day_data["sample_count"] > existing_data[1] or
|
||||
day_data["bytes_written_delta"] > existing_data[0]):
|
||||
|
||||
total_seconds = (day_data["active_seconds"] + day_data["idle_seconds"] +
|
||||
day_data["powered_off_seconds"] + day_data["unknown_seconds"])
|
||||
coverage = (day_data["active_seconds"] + day_data["idle_seconds"] +
|
||||
day_data["powered_off_seconds"]) / total_seconds if total_seconds > 0 else 0.0
|
||||
|
||||
conn.execute(
|
||||
"""UPDATE day_aggregates SET
|
||||
active_seconds = ?, idle_seconds = ?, powered_off_seconds = ?,
|
||||
unknown_seconds = ?, bytes_written_delta = ?, bytes_read_delta = ?,
|
||||
sample_count = ?, coverage = ?
|
||||
WHERE day = ?""",
|
||||
(day_data["active_seconds"], day_data["idle_seconds"],
|
||||
day_data["powered_off_seconds"], day_data["unknown_seconds"],
|
||||
day_data["bytes_written_delta"], day_data["bytes_read_delta"],
|
||||
day_data["sample_count"], coverage, day_data["day"]),
|
||||
)
|
||||
return False # Updated, not created
|
||||
else:
|
||||
return False # No update needed
|
||||
|
||||
|
||||
def repair_derivation(
|
||||
conn: sqlite3.Connection,
|
||||
clock=None,
|
||||
) -> RepairResult:
|
||||
"""Repair hour observations and day aggregates from surviving samples.
|
||||
|
||||
This is the main entry point for historical repair. It:
|
||||
1. Finds sample pairs that need interval derivation
|
||||
2. Derives hour observations from those intervals
|
||||
3. Updates day aggregates from the hour observations
|
||||
4. Preserves existing valid data
|
||||
5. Is idempotent and interruption-safe
|
||||
|
||||
Args:
|
||||
conn: Connection to the observation store
|
||||
clock: Injected clock (for testing)
|
||||
|
||||
Returns:
|
||||
RepairResult with operation details
|
||||
"""
|
||||
if clock is None:
|
||||
clock = datetime.now(timezone.utc)
|
||||
elif hasattr(clock, 'utcnow'):
|
||||
clock = clock.utcnow()
|
||||
|
||||
# Check if repair is already in progress
|
||||
if is_repair_in_progress(conn):
|
||||
return RepairResult(
|
||||
ok=False,
|
||||
error="Repair already in progress",
|
||||
)
|
||||
|
||||
# Mark repair as in progress
|
||||
_set_repair_in_progress(conn, True)
|
||||
|
||||
result = RepairResult(ok=True)
|
||||
|
||||
try:
|
||||
# Begin transaction
|
||||
conn.execute("BEGIN IMMEDIATE")
|
||||
|
||||
# 1. Find and derive intervals from sample pairs
|
||||
intervals = _get_unlinked_intervals(conn)
|
||||
|
||||
for prev, next_s in intervals:
|
||||
try:
|
||||
derived_hours = derive_hours_from_interval(conn, prev, next_s)
|
||||
result.intervals_derived += 1
|
||||
result.hours_created += len([h for h in derived_hours if h.get("attributed", True)])
|
||||
except Exception as e:
|
||||
logger.warning("Failed to derive interval %s -> %s: %s",
|
||||
prev["ts"], next_s["ts"], e)
|
||||
# Continue with other intervals (resilient)
|
||||
|
||||
# 2. Update day aggregates from hour observations
|
||||
cursor = conn.execute(
|
||||
"SELECT DISTINCT substr(hour, 1, 10) as day FROM hour_observations ORDER BY day"
|
||||
)
|
||||
days = [row[0] for row in cursor.fetchall()]
|
||||
|
||||
for day in days:
|
||||
day_data = _derive_day_aggregate_from_hours(conn, day)
|
||||
if day_data is not None:
|
||||
created = _upsert_day_aggregate(conn, day_data)
|
||||
if created:
|
||||
result.days_created += 1
|
||||
else:
|
||||
result.days_updated += 1
|
||||
|
||||
# 3. Count boundary anchors retained
|
||||
now = clock if isinstance(clock, datetime) else datetime.now(timezone.utc)
|
||||
cursor = conn.execute("SELECT ts FROM samples ORDER BY ts")
|
||||
anchor_count = 0
|
||||
for row in cursor.fetchall():
|
||||
if needs_boundary_anchor(conn, row[0], now):
|
||||
anchor_count += 1
|
||||
result.boundary_anchors_retained = anchor_count
|
||||
|
||||
# 4. Count preserved legacy summaries
|
||||
# Legacy summaries are day aggregates without corresponding hour observations
|
||||
cursor = conn.execute(
|
||||
"""SELECT COUNT(*) FROM day_aggregates d
|
||||
WHERE NOT EXISTS (
|
||||
SELECT 1 FROM hour_observations h
|
||||
WHERE h.hour LIKE d.day || 'T%'
|
||||
)"""
|
||||
)
|
||||
result.legacy_summaries_preserved = cursor.fetchone()[0]
|
||||
|
||||
# Commit transaction
|
||||
conn.commit()
|
||||
|
||||
# Update repair status
|
||||
_update_repair_status(conn, result)
|
||||
|
||||
except Exception as e:
|
||||
conn.rollback()
|
||||
logger.error("Repair failed: %s", e)
|
||||
return RepairResult(
|
||||
ok=False,
|
||||
error=str(e),
|
||||
)
|
||||
finally:
|
||||
# Mark repair as complete
|
||||
_set_repair_in_progress(conn, False)
|
||||
|
||||
return result
|
||||
+24
-2
@@ -331,7 +331,8 @@ def check_retired_flag(flag: str) -> Optional[str]:
|
||||
def _format_projection(proj, freshness: str, service: Dict[str, Any],
|
||||
drive_facts: List[str], config_error: Optional[str],
|
||||
store_fault: Optional[str], newer_schema: Optional[str],
|
||||
journal_hint: Optional[str]) -> str:
|
||||
journal_hint: Optional[str],
|
||||
sample_count: int = 0, day_count: int = 0) -> str:
|
||||
"""Format the complete status output."""
|
||||
lines = []
|
||||
|
||||
@@ -361,6 +362,16 @@ def _format_projection(proj, freshness: str, service: Dict[str, Any],
|
||||
_append_service_facts(lines, service)
|
||||
return "\n".join(lines)
|
||||
|
||||
# --- Single sample: awaiting another sample (issue #73 AC3) ---
|
||||
# Only show awaiting state when there are no day aggregates (e.g., legacy import
|
||||
# or hand-crafted stores can have 1 sample but sufficient day data for projection)
|
||||
if sample_count <= 1 and day_count == 0:
|
||||
lines.append("awaiting another sample")
|
||||
lines.append("")
|
||||
lines.append("Collecting usage data — the first projection requires at least two samples.")
|
||||
_append_service_facts(lines, service)
|
||||
return "\n".join(lines)
|
||||
|
||||
# --- Projection headline ---
|
||||
headline = _format_headline(proj)
|
||||
lines.append(headline)
|
||||
@@ -598,6 +609,17 @@ def get_status(store_path: Optional[Path] = None, clock_now: Optional[datetime]
|
||||
|
||||
freshness = grade_freshness(newest_ts, clock_now)
|
||||
|
||||
# --- Sample count for single-sample state (issue #73 AC3) ---
|
||||
sample_count = 0
|
||||
day_count = 0
|
||||
try:
|
||||
cursor = conn.execute("SELECT COUNT(*) FROM samples")
|
||||
sample_count = cursor.fetchone()[0]
|
||||
cursor = conn.execute("SELECT COUNT(*) FROM day_aggregates")
|
||||
day_count = cursor.fetchone()[0]
|
||||
except sqlite3.Error:
|
||||
pass
|
||||
|
||||
# Freshness age for the service fact
|
||||
freshness_age_s = None
|
||||
if newest_ts:
|
||||
@@ -637,7 +659,7 @@ def get_status(store_path: Optional[Path] = None, clock_now: Optional[datetime]
|
||||
# --- Compose output ---
|
||||
result = _format_projection(
|
||||
proj, freshness, service, drive_facts, config_error,
|
||||
None, None, journal_hint,
|
||||
None, None, journal_hint, sample_count, day_count,
|
||||
)
|
||||
|
||||
conn.close()
|
||||
|
||||
+33
-8
@@ -12,7 +12,7 @@ from typing import Optional
|
||||
|
||||
|
||||
# Schema version - increment on each migration
|
||||
SCHEMA_VERSION = 1
|
||||
SCHEMA_VERSION = 2
|
||||
|
||||
|
||||
# Packaged default placement (spec §8.3). The config may override it, but a
|
||||
@@ -106,7 +106,8 @@ def _create_schema(conn: sqlite3.Connection):
|
||||
data_units_read INTEGER,
|
||||
bytes_written INTEGER,
|
||||
bytes_read INTEGER,
|
||||
critical_warning INTEGER
|
||||
critical_warning INTEGER,
|
||||
segment_id INTEGER
|
||||
)
|
||||
""")
|
||||
|
||||
@@ -141,7 +142,9 @@ def _create_schema(conn: sqlite3.Connection):
|
||||
bytes_written_delta INTEGER DEFAULT 0,
|
||||
bytes_read_delta INTEGER DEFAULT 0,
|
||||
sample_count INTEGER DEFAULT 0,
|
||||
coverage REAL DEFAULT 0.0
|
||||
coverage REAL DEFAULT 0.0,
|
||||
unattributed_bytes_written INTEGER DEFAULT 0,
|
||||
unattributed_bytes_read INTEGER DEFAULT 0
|
||||
)
|
||||
""")
|
||||
|
||||
@@ -207,11 +210,25 @@ def _apply_migrations(conn: sqlite3.Connection, current_version: int):
|
||||
|
||||
Spec: §3.6, §10.2
|
||||
"""
|
||||
# Migration 1→2: example placeholder
|
||||
# if current_version < 2:
|
||||
# conn.execute("ALTER TABLE ...")
|
||||
# current_version = 2
|
||||
pass
|
||||
# Migration 1→2: add segment_id provenance to samples,
|
||||
# unattributed byte tracking to day_aggregates (issue #73)
|
||||
if current_version < 2:
|
||||
# Defensive: only ALTER if table exists (handles minimal v1 stores)
|
||||
tables = {row[0] for row in conn.execute(
|
||||
"SELECT name FROM sqlite_master WHERE type='table'"
|
||||
).fetchall()}
|
||||
if "samples" in tables:
|
||||
# Check if column already exists (idempotent)
|
||||
cols = {row[1] for row in conn.execute("PRAGMA table_info(samples)").fetchall()}
|
||||
if "segment_id" not in cols:
|
||||
conn.execute("ALTER TABLE samples ADD COLUMN segment_id INTEGER")
|
||||
if "day_aggregates" in tables:
|
||||
cols = {row[1] for row in conn.execute("PRAGMA table_info(day_aggregates)").fetchall()}
|
||||
if "unattributed_bytes_written" not in cols:
|
||||
conn.execute("ALTER TABLE day_aggregates ADD COLUMN unattributed_bytes_written INTEGER DEFAULT 0")
|
||||
if "unattributed_bytes_read" not in cols:
|
||||
conn.execute("ALTER TABLE day_aggregates ADD COLUMN unattributed_bytes_read INTEGER DEFAULT 0")
|
||||
current_version = 2
|
||||
|
||||
|
||||
def migrate_to_latest(store_path: Path) -> int:
|
||||
@@ -239,6 +256,14 @@ def migrate_to_latest(store_path: Path) -> int:
|
||||
conn.close()
|
||||
return 0 # Already up to date
|
||||
|
||||
# Version 0 means no schema — create fresh (issue #73)
|
||||
if current_version == 0:
|
||||
_create_schema(conn)
|
||||
conn.execute(f"PRAGMA user_version={SCHEMA_VERSION}")
|
||||
conn.commit()
|
||||
conn.close()
|
||||
return SCHEMA_VERSION
|
||||
|
||||
steps = SCHEMA_VERSION - current_version
|
||||
_apply_migrations(conn, current_version)
|
||||
conn.execute(f"PRAGMA user_version={SCHEMA_VERSION}")
|
||||
|
||||
+24
-7
@@ -447,15 +447,32 @@ class FenrisTuiApp(App):
|
||||
|
||||
def _render_all_regions(self, conn: sqlite3.Connection) -> None:
|
||||
"""Render all four regions from live store data."""
|
||||
# --- Headline band (§7.2) ---
|
||||
# --- Sample count for single-sample state (issue #73 AC3) ---
|
||||
try:
|
||||
proj = compute_projection(conn, self._clock_now)
|
||||
headline = self._format_headline(proj)
|
||||
confidence = self._format_confidence(proj)
|
||||
scenario = self._format_scenario(proj)
|
||||
self._render_headline(headline + "\n" + confidence + "\n" + scenario)
|
||||
cursor = conn.execute("SELECT COUNT(*) FROM samples")
|
||||
sample_count = cursor.fetchone()[0]
|
||||
cursor = conn.execute("SELECT COUNT(*) FROM day_aggregates")
|
||||
day_count = cursor.fetchone()[0]
|
||||
except Exception:
|
||||
self._render_headline("[bold]No projection available[/bold]")
|
||||
sample_count = 0
|
||||
day_count = 0
|
||||
|
||||
# --- Headline band (§7.2) ---
|
||||
if sample_count <= 1 and day_count == 0:
|
||||
# Single sample: awaiting another sample
|
||||
self._render_headline(
|
||||
"[bold]Awaiting another sample[/bold]\n\n"
|
||||
"Collecting usage data — the first projection requires at least two samples."
|
||||
)
|
||||
else:
|
||||
try:
|
||||
proj = compute_projection(conn, self._clock_now)
|
||||
headline = self._format_headline(proj)
|
||||
confidence = self._format_confidence(proj)
|
||||
scenario = self._format_scenario(proj)
|
||||
self._render_headline(headline + "\n" + confidence + "\n" + scenario)
|
||||
except Exception:
|
||||
self._render_headline("[bold]No projection available[/bold]")
|
||||
|
||||
# --- Usage-history pane (§7.2 left) ---
|
||||
history = _query_usage_history(conn)
|
||||
|
||||
@@ -0,0 +1,712 @@
|
||||
"""Collector history tracer tests (issue #73).
|
||||
|
||||
Tests the end-to-end history pipeline: sample acquisition → interval
|
||||
derivation → hour observation → day aggregate, with concurrent-read
|
||||
safety, cross-hour handling, and display states.
|
||||
|
||||
Seams:
|
||||
- write side: run_collection() → observation store
|
||||
- read side: get_status(), compute_projection() → observation store
|
||||
"""
|
||||
import os
|
||||
import sqlite3
|
||||
from datetime import datetime, timedelta, timezone
|
||||
from pathlib import Path
|
||||
from typing import Any, Dict
|
||||
|
||||
import pytest
|
||||
import sys
|
||||
|
||||
sys.path.insert(0, str(Path(__file__).parent.parent / "src"))
|
||||
|
||||
from fenris.collector import run_collection, normalize_identity
|
||||
from fenris.store import init_store, get_store_path, SCHEMA_VERSION
|
||||
from fenris.monitoring_periods import ensure_period_open, close_period, get_open_period
|
||||
from fenris.day_aggregate import derive_day, derive_all_days
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Fixtures
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
@pytest.fixture
|
||||
def smartctl_fixture() -> Dict[str, Any]:
|
||||
"""Minimal smartctl -a -j output with required fields."""
|
||||
return {
|
||||
"json_format_version": [1, 0],
|
||||
"smartctl": {"version": [7, 3], "svn_revision": "5155", "build_info": "(local build)"},
|
||||
"nvme_smart_health_information_log": {
|
||||
"critical_warning": 0,
|
||||
"temperature": 35,
|
||||
"available_spare": 100,
|
||||
"available_spare_threshold": 10,
|
||||
"percentage_used": 5,
|
||||
"data_units_written": 12345678,
|
||||
"data_units_read": 9876543,
|
||||
"power_on_hours": 8765,
|
||||
"power_cycles": 1234,
|
||||
"unsafe_shutdowns": 5,
|
||||
"media_errors": 0,
|
||||
"num_err_log_entries": 0,
|
||||
},
|
||||
"user_capacity": {"bytes": 1024000000000, "units": "bytes"},
|
||||
"model_name": "Samsung SSD 970 EVO Plus 1TB",
|
||||
"serial_number": "S4EWNX0N123456",
|
||||
"firmware_version": "2B2QEXM7",
|
||||
}
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def sysfs_fixture_tree(tmp_path: Path) -> Path:
|
||||
"""Create a minimal sysfs fixture tree with controller identity."""
|
||||
ctrl_dir = tmp_path / "sys" / "class" / "nvme" / "nvme0"
|
||||
ctrl_dir.mkdir(parents=True)
|
||||
(ctrl_dir / "subsysnqn").write_text("nqn.2014-08.org.nvmexpress:uuid:12345678-1234-1234-1234-123456789abc\n")
|
||||
(ctrl_dir / "model").write_text("Samsung SSD 970 EVO Plus 1TB\n")
|
||||
(ctrl_dir / "serial").write_text("S4EWNX0N123456\n")
|
||||
(ctrl_dir / "firmware_rev").write_text("2B2QEXM7\n")
|
||||
transport_dir = ctrl_dir / "transport"
|
||||
transport_dir.mkdir()
|
||||
(transport_dir / "address").write_text("0000:03:00.0")
|
||||
(transport_dir / "trstring").write_text("pcie")
|
||||
return tmp_path
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def config_fixture(tmp_path: Path) -> Dict[str, Any]:
|
||||
"""Configuration fixture naming the device."""
|
||||
return {
|
||||
"device": "/dev/nvme0",
|
||||
"store_path": str(tmp_path / "observations.db"),
|
||||
}
|
||||
|
||||
|
||||
class FakeClock:
|
||||
"""Injected clock returning controlled time."""
|
||||
def __init__(self, initial: datetime):
|
||||
self.now = initial
|
||||
def utcnow(self):
|
||||
return self.now
|
||||
def advance(self, **kwargs):
|
||||
self.now = self.now + timedelta(**kwargs)
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Schema migration: existing data readable at real precision
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
class TestSchemaMigration:
|
||||
"""Schema migration 1→2 preserves existing data (issue #73 AC1)."""
|
||||
|
||||
def test_migration_bumps_version(self, tmp_path):
|
||||
"""Migration from v1 to v2 succeeds."""
|
||||
from fenris.store import migrate_to_latest, SCHEMA_VERSION
|
||||
|
||||
# Create a v1 store directly (simulating pre-migration state)
|
||||
db = tmp_path / "test.db"
|
||||
conn = sqlite3.connect(str(db))
|
||||
conn.execute("PRAGMA journal_mode=WAL")
|
||||
# Create v1 schema manually
|
||||
conn.execute("""
|
||||
CREATE TABLE samples (
|
||||
id INTEGER PRIMARY KEY AUTOINCREMENT,
|
||||
ts TEXT NOT NULL,
|
||||
device TEXT NOT NULL,
|
||||
subnqn TEXT, sn TEXT, mn TEXT, fr TEXT,
|
||||
capacity_bytes INTEGER, percentage_used INTEGER,
|
||||
available_spare INTEGER, media_errors INTEGER,
|
||||
power_on_hours INTEGER, power_cycles INTEGER,
|
||||
unsafe_shutdowns INTEGER, temperature_c INTEGER,
|
||||
data_units_written INTEGER, data_units_read INTEGER,
|
||||
bytes_written INTEGER, bytes_read INTEGER,
|
||||
critical_warning INTEGER
|
||||
)
|
||||
""")
|
||||
conn.execute("""
|
||||
CREATE TABLE hour_observations (
|
||||
id INTEGER PRIMARY KEY AUTOINCREMENT,
|
||||
hour TEXT NOT NULL UNIQUE,
|
||||
active_seconds INTEGER DEFAULT 0, idle_seconds INTEGER DEFAULT 0,
|
||||
powered_off_seconds INTEGER DEFAULT 0, unknown_seconds INTEGER DEFAULT 0,
|
||||
bytes_written_delta INTEGER DEFAULT 0, bytes_read_delta INTEGER DEFAULT 0,
|
||||
temperature_min INTEGER, temperature_avg REAL, temperature_max INTEGER,
|
||||
sample_count INTEGER DEFAULT 0, coverage REAL DEFAULT 0.0
|
||||
)
|
||||
""")
|
||||
conn.execute("""
|
||||
CREATE TABLE day_aggregates (
|
||||
id INTEGER PRIMARY KEY AUTOINCREMENT,
|
||||
day TEXT NOT NULL UNIQUE,
|
||||
active_seconds INTEGER DEFAULT 0, idle_seconds INTEGER DEFAULT 0,
|
||||
powered_off_seconds INTEGER DEFAULT 0, unknown_seconds INTEGER DEFAULT 0,
|
||||
bytes_written_delta INTEGER DEFAULT 0, bytes_read_delta INTEGER DEFAULT 0,
|
||||
sample_count INTEGER DEFAULT 0, coverage REAL DEFAULT 0.0
|
||||
)
|
||||
""")
|
||||
conn.execute("CREATE TABLE monitoring_periods (id INTEGER PRIMARY KEY AUTOINCREMENT, started_at TEXT NOT NULL, ended_at TEXT, end_cause TEXT)")
|
||||
conn.execute("CREATE TABLE controller_segments (id INTEGER PRIMARY KEY AUTOINCREMENT, opened_at TEXT NOT NULL, identity_key TEXT, identity_degraded BOOLEAN DEFAULT 0, subnqn TEXT, sn TEXT, mn TEXT, fr TEXT, vid TEXT, ssvid TEXT, transport TEXT)")
|
||||
conn.execute("CREATE TABLE endurance_baseline (id INTEGER PRIMARY KEY AUTOINCREMENT, tbw_terabytes REAL NOT NULL, source_url TEXT, document_revision TEXT, entry_date TEXT, model_string TEXT, nominal_capacity_bytes INTEGER, validated_by TEXT, verified BOOLEAN DEFAULT 0, created_at TEXT NOT NULL, updated_at TEXT NOT NULL)")
|
||||
conn.execute("CREATE TABLE store_metadata (key TEXT PRIMARY KEY, value TEXT NOT NULL)")
|
||||
conn.execute("PRAGMA user_version=1")
|
||||
conn.execute("INSERT INTO samples (ts, device, mn, sn, fr, capacity_bytes, percentage_used, available_spare, media_errors, power_on_hours, power_cycles, unsafe_shutdowns, temperature_c, data_units_written, data_units_read, bytes_written, bytes_read, critical_warning) VALUES ('2026-09-01T12:00:00+00:00', '/dev/nvme0', 'Test', 'SN', 'FR', 1000000000000, 5, 100, 0, 1000, 100, 0, 35, 1000000, 500000, 512000000000, 256000000000, 0)")
|
||||
conn.commit()
|
||||
conn.close()
|
||||
|
||||
# Migrate
|
||||
steps = migrate_to_latest(db)
|
||||
assert steps == 1
|
||||
|
||||
# Verify data preserved
|
||||
conn = sqlite3.connect(str(db))
|
||||
row = conn.execute("SELECT ts, mn FROM samples").fetchone()
|
||||
version = conn.execute("PRAGMA user_version").fetchone()[0]
|
||||
conn.close()
|
||||
assert row[0] == "2026-09-01T12:00:00+00:00"
|
||||
assert row[1] == "Test"
|
||||
assert version == SCHEMA_VERSION
|
||||
|
||||
def test_newer_schema_refused(self, tmp_path):
|
||||
"""Store with user_version > SCHEMA_VERSION is refused."""
|
||||
db = tmp_path / "test.db"
|
||||
conn = sqlite3.connect(str(db))
|
||||
conn.execute("PRAGMA user_version=%d" % (SCHEMA_VERSION + 1))
|
||||
conn.commit()
|
||||
conn.close()
|
||||
|
||||
with pytest.raises(ValueError, match="newer Fenris"):
|
||||
init_store(db)
|
||||
|
||||
def test_existing_data_preserved_after_migration(self, config_fixture,
|
||||
smartctl_fixture,
|
||||
sysfs_fixture_tree):
|
||||
"""Existing sample data is not lost or modified by migration."""
|
||||
clock = FakeClock(datetime(2026, 9, 1, 12, 0, 0, tzinfo=timezone.utc))
|
||||
|
||||
# Write first sample
|
||||
run_collection(smartctl_fixture, sysfs_fixture_tree / "sys" / "class" / "nvme" / "nvme0",
|
||||
config_fixture, clock)
|
||||
|
||||
conn = sqlite3.connect(config_fixture["store_path"])
|
||||
row = conn.execute("SELECT ts, device, bytes_written FROM samples").fetchone()
|
||||
conn.close()
|
||||
|
||||
assert row[0] == "2026-09-01T12:00:00+00:00"
|
||||
assert row[1] == "/dev/nvme0"
|
||||
assert row[2] == 12345678 * 512000
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Collector publishes samples, intervals, hour observations, day aggregates
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
class TestCollectorDerivation:
|
||||
"""Collector derives hour observations and day aggregates (issue #73 AC2)."""
|
||||
|
||||
def _make_sample(self, duw_units: int, ts: str) -> Dict[str, Any]:
|
||||
"""Build a smartctl fixture with specific DUW."""
|
||||
return {
|
||||
"json_format_version": [1, 0],
|
||||
"smartctl": {"version": [7, 3], "svn_revision": "5155", "build_info": "(local build)"},
|
||||
"nvme_smart_health_information_log": {
|
||||
"critical_warning": 0,
|
||||
"temperature": 35,
|
||||
"available_spare": 100,
|
||||
"available_spare_threshold": 10,
|
||||
"percentage_used": 5,
|
||||
"data_units_written": duw_units,
|
||||
"data_units_read": 9876543,
|
||||
"power_on_hours": 8765,
|
||||
"power_cycles": 1234,
|
||||
"unsafe_shutdowns": 5,
|
||||
"media_errors": 0,
|
||||
"num_err_log_entries": 0,
|
||||
},
|
||||
"user_capacity": {"bytes": 1024000000000, "units": "bytes"},
|
||||
"model_name": "Samsung SSD 970 EVO Plus 1TB",
|
||||
"serial_number": "S4EWNX0N123456",
|
||||
"firmware_version": "2B2QEXM7",
|
||||
}
|
||||
|
||||
def test_same_hour_20mb_derives_hour_obs(self, config_fixture, sysfs_fixture_tree):
|
||||
"""Two samples in same hour with 20 MB delta → hour_obs gets 20 MB."""
|
||||
t1 = datetime(2026, 9, 1, 12, 0, 0, tzinfo=timezone.utc)
|
||||
t2 = datetime(2026, 9, 1, 12, 5, 0, tzinfo=timezone.utc)
|
||||
|
||||
# DUW units: 12345678 * 512000 = ~6.3 TB; 20 MB = 20*1024*1024 / 512000 ≈ 40 units
|
||||
duw1 = 12345678
|
||||
duw2 = duw1 + 40 # ~20 MB more
|
||||
|
||||
clock1 = FakeClock(t1)
|
||||
s1 = self._make_sample(duw1, t1.isoformat())
|
||||
r1 = run_collection(s1, sysfs_fixture_tree / "sys" / "class" / "nvme" / "nvme0",
|
||||
config_fixture, clock1)
|
||||
assert r1["ok"]
|
||||
|
||||
clock2 = FakeClock(t2)
|
||||
s2 = self._make_sample(duw2, t2.isoformat())
|
||||
r2 = run_collection(s2, sysfs_fixture_tree / "sys" / "class" / "nvme" / "nvme0",
|
||||
config_fixture, clock2)
|
||||
assert r2["ok"]
|
||||
|
||||
# Check hour_observation was derived
|
||||
conn = sqlite3.connect(config_fixture["store_path"])
|
||||
hour = conn.execute(
|
||||
"SELECT bytes_written_delta, sample_count FROM hour_observations WHERE hour LIKE '2026-09-01T12%'"
|
||||
).fetchone()
|
||||
conn.close()
|
||||
|
||||
assert hour is not None, "Hour observation should exist for 12:00"
|
||||
assert hour[1] >= 2 # at least 2 samples contributed
|
||||
# bytes_written_delta should be the 20 MB delta (40 * 512000 = 20480000)
|
||||
assert hour[0] == 40 * 512000
|
||||
|
||||
def test_zero_delta_derives_hour_obs(self, config_fixture, sysfs_fixture_tree):
|
||||
"""Two samples in same hour with no DUW change → 0 B written."""
|
||||
t1 = datetime(2026, 9, 1, 12, 0, 0, tzinfo=timezone.utc)
|
||||
t2 = datetime(2026, 9, 1, 12, 5, 0, tzinfo=timezone.utc)
|
||||
|
||||
duw = 12345678 # same for both
|
||||
|
||||
clock1 = FakeClock(t1)
|
||||
s1 = self._make_sample(duw, t1.isoformat())
|
||||
run_collection(s1, sysfs_fixture_tree / "sys" / "class" / "nvme" / "nvme0",
|
||||
config_fixture, clock1)
|
||||
|
||||
clock2 = FakeClock(t2)
|
||||
s2 = self._make_sample(duw, t2.isoformat())
|
||||
run_collection(s2, sysfs_fixture_tree / "sys" / "class" / "nvme" / "nvme0",
|
||||
config_fixture, clock2)
|
||||
|
||||
conn = sqlite3.connect(config_fixture["store_path"])
|
||||
hour = conn.execute(
|
||||
"SELECT bytes_written_delta FROM hour_observations WHERE hour LIKE '2026-09-01T12%'"
|
||||
).fetchone()
|
||||
conn.close()
|
||||
|
||||
assert hour is not None
|
||||
assert hour[0] == 0
|
||||
|
||||
def test_cross_hour_100mb_unattributed(self, config_fixture, sysfs_fixture_tree):
|
||||
"""Samples in different hours → delta is unattributed to any hour."""
|
||||
t1 = datetime(2026, 9, 1, 11, 55, 0, tzinfo=timezone.utc)
|
||||
t2 = datetime(2026, 9, 1, 12, 5, 0, tzinfo=timezone.utc)
|
||||
|
||||
duw1 = 12345678
|
||||
duw2 = duw1 + 200 # ~100 MB
|
||||
|
||||
clock1 = FakeClock(t1)
|
||||
s1 = self._make_sample(duw1, t1.isoformat())
|
||||
run_collection(s1, sysfs_fixture_tree / "sys" / "class" / "nvme" / "nvme0",
|
||||
config_fixture, clock1)
|
||||
|
||||
clock2 = FakeClock(t2)
|
||||
s2 = self._make_sample(duw2, t2.isoformat())
|
||||
run_collection(s2, sysfs_fixture_tree / "sys" / "class" / "nvme" / "nvme0",
|
||||
config_fixture, clock2)
|
||||
|
||||
conn = sqlite3.connect(config_fixture["store_path"])
|
||||
|
||||
# Hour observations should NOT contain the cross-hour delta
|
||||
hour11 = conn.execute(
|
||||
"SELECT bytes_written_delta FROM hour_observations WHERE hour LIKE '2026-09-01T11%'"
|
||||
).fetchone()
|
||||
hour12 = conn.execute(
|
||||
"SELECT bytes_written_delta FROM hour_observations WHERE hour LIKE '2026-09-01T12%'"
|
||||
).fetchone()
|
||||
conn.close()
|
||||
|
||||
# Neither hour should have the full 100 MB delta attributed
|
||||
# (they may have 0 or partial, but not 200*512000)
|
||||
full_delta = 200 * 512000
|
||||
if hour11 is not None:
|
||||
assert hour11[0] != full_delta, "Hour 11 should not have full cross-hour delta"
|
||||
if hour12 is not None:
|
||||
assert hour12[0] != full_delta, "Hour 12 should not have full cross-hour delta"
|
||||
|
||||
def test_readonly_sees_consistent_snapshot(self, config_fixture, sysfs_fixture_tree):
|
||||
"""A read-only reader sees valid pre- or post-publication snapshot."""
|
||||
t1 = datetime(2026, 9, 1, 12, 0, 0, tzinfo=timezone.utc)
|
||||
t2 = datetime(2026, 9, 1, 12, 5, 0, tzinfo=timezone.utc)
|
||||
|
||||
clock1 = FakeClock(t1)
|
||||
run_collection(self._make_sample(12345678, t1.isoformat()),
|
||||
sysfs_fixture_tree / "sys" / "class" / "nvme" / "nvme0",
|
||||
config_fixture, clock1)
|
||||
|
||||
# Open read-only
|
||||
ro_conn = sqlite3.connect(
|
||||
"file:%s?mode=ro" % config_fixture["store_path"], uri=True
|
||||
)
|
||||
count_before = ro_conn.execute("SELECT COUNT(*) FROM samples").fetchone()[0]
|
||||
ro_conn.close()
|
||||
assert count_before == 1
|
||||
|
||||
# Write second sample
|
||||
clock2 = FakeClock(t2)
|
||||
run_collection(self._make_sample(12345718, t2.isoformat()),
|
||||
sysfs_fixture_tree / "sys" / "class" / "nvme" / "nvme0",
|
||||
config_fixture, clock2)
|
||||
|
||||
# Read-only reader sees 2 samples now
|
||||
ro_conn2 = sqlite3.connect(
|
||||
"file:%s?mode=ro" % config_fixture["store_path"], uri=True
|
||||
)
|
||||
count_after = ro_conn2.execute("SELECT COUNT(*) FROM samples").fetchone()[0]
|
||||
ro_conn2.close()
|
||||
assert count_after == 2
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Display states: awaiting first sample, awaiting another sample
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
class TestDisplayStates:
|
||||
"""Display states for zero/one/two+ samples (issue #73 AC3)."""
|
||||
|
||||
def test_zero_samples_awaiting_first(self, tmp_path):
|
||||
"""Zero samples → 'awaiting first sample' state."""
|
||||
from fenris.status import get_status
|
||||
db = tmp_path / "test.db"
|
||||
init_store(db)
|
||||
now = datetime(2026, 9, 1, 12, 0, 0, tzinfo=timezone.utc)
|
||||
from unittest.mock import patch
|
||||
with patch("fenris.status.query_service_state", return_value={
|
||||
"boot_enabled": False, "timer_active": False,
|
||||
"last_collect_ok": None, "last_collect_age_s": None,
|
||||
"last_collect_reason": None,
|
||||
}):
|
||||
result = get_status(store_path=db, clock_now=now,
|
||||
query_services=False, query_journal=False)
|
||||
assert "no observations yet" in result.lower() or "awaiting" in result.lower()
|
||||
|
||||
def test_one_sample_awaiting_another(self, tmp_path):
|
||||
"""One sample → 'awaiting another sample' state."""
|
||||
from fenris.status import get_status
|
||||
db = tmp_path / "test.db"
|
||||
conn = init_store(db)
|
||||
conn.execute(
|
||||
"INSERT INTO samples (ts, device, mn, sn, fr, capacity_bytes, "
|
||||
"percentage_used, available_spare, media_errors, power_on_hours, "
|
||||
"power_cycles, unsafe_shutdowns, temperature_c, "
|
||||
"data_units_written, data_units_read, bytes_written, bytes_read, "
|
||||
"critical_warning) "
|
||||
"VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)",
|
||||
("2026-09-01T12:00:00+00:00", "/dev/nvme0", "Test", "SN", "FR",
|
||||
1000000000000, 5, 100, 0, 1000, 100, 0, 35,
|
||||
1000000, 500000, 512000000000, 256000000000, 0),
|
||||
)
|
||||
conn.commit()
|
||||
conn.close()
|
||||
now = datetime(2026, 9, 1, 12, 0, 0, tzinfo=timezone.utc)
|
||||
from unittest.mock import patch
|
||||
with patch("fenris.status.query_service_state", return_value={
|
||||
"boot_enabled": False, "timer_active": False,
|
||||
"last_collect_ok": None, "last_collect_age_s": None,
|
||||
"last_collect_reason": None,
|
||||
}):
|
||||
result = get_status(store_path=db, clock_now=now,
|
||||
query_services=False, query_journal=False)
|
||||
# Should mention awaiting or insufficient data
|
||||
lower = result.lower()
|
||||
assert "awaiting" in lower or "another sample" in lower or "no projection" in lower
|
||||
|
||||
def test_one_sample_awaiting_another_in_tui(self, tmp_path):
|
||||
"""One sample → TUI shows awaiting state."""
|
||||
from fenris.tui import FenrisTuiApp, _query_service_facts
|
||||
db = tmp_path / "test.db"
|
||||
conn = init_store(db)
|
||||
conn.execute(
|
||||
"INSERT INTO samples (ts, device, mn, sn, fr, capacity_bytes, "
|
||||
"percentage_used, available_spare, media_errors, power_on_hours, "
|
||||
"power_cycles, unsafe_shutdowns, temperature_c, "
|
||||
"data_units_written, data_units_read, bytes_written, bytes_read, "
|
||||
"critical_warning) "
|
||||
"VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)",
|
||||
("2026-09-01T12:00:00+00:00", "/dev/nvme0", "Test", "SN", "FR",
|
||||
1000000000000, 5, 100, 0, 1000, 100, 0, 35,
|
||||
1000000, 500000, 512000000000, 256000000000, 0),
|
||||
)
|
||||
conn.commit()
|
||||
conn.close()
|
||||
now = datetime(2026, 9, 1, 12, 0, 0, tzinfo=timezone.utc)
|
||||
# Test the projection handles single sample
|
||||
from fenris.projection import compute_projection, ConfidenceState
|
||||
conn = sqlite3.connect(db)
|
||||
proj = compute_projection(conn, now)
|
||||
conn.close()
|
||||
# With only one sample, projection should be unavailable
|
||||
assert proj.confidence_state == ConfidenceState.UNSUPPORTED
|
||||
|
||||
def test_two_same_hour_samples_show_measured_usage(self, config_fixture, sysfs_fixture_tree):
|
||||
"""Two compatible same-hour samples show measured usage."""
|
||||
t1 = datetime(2026, 9, 1, 12, 0, 0, tzinfo=timezone.utc)
|
||||
t2 = datetime(2026, 9, 1, 12, 5, 0, tzinfo=timezone.utc)
|
||||
|
||||
clock1 = FakeClock(t1)
|
||||
run_collection(self._make_sample_helper(12345678), sysfs_fixture_tree / "sys" / "class" / "nvme" / "nvme0",
|
||||
config_fixture, clock1)
|
||||
|
||||
clock2 = FakeClock(t2)
|
||||
run_collection(self._make_sample_helper(12345718), sysfs_fixture_tree / "sys" / "class" / "nvme" / "nvme0",
|
||||
config_fixture, clock2)
|
||||
|
||||
from fenris.status import get_status
|
||||
from unittest.mock import patch
|
||||
now = datetime(2026, 9, 1, 12, 10, 0, tzinfo=timezone.utc)
|
||||
with patch("fenris.status.query_service_state", return_value={
|
||||
"boot_enabled": False, "timer_active": False,
|
||||
"last_collect_ok": None, "last_collect_age_s": None,
|
||||
"last_collect_reason": None,
|
||||
}):
|
||||
result = get_status(store_path=Path(config_fixture["store_path"]),
|
||||
clock_now=now, query_services=False, query_journal=False)
|
||||
# Should not say "no observations" or "awaiting"
|
||||
lower = result.lower()
|
||||
assert "no observations yet" not in lower
|
||||
|
||||
def _make_sample_helper(self, duw_units: int) -> Dict[str, Any]:
|
||||
return {
|
||||
"json_format_version": [1, 0],
|
||||
"smartctl": {"version": [7, 3], "svn_revision": "5155", "build_info": "(local build)"},
|
||||
"nvme_smart_health_information_log": {
|
||||
"critical_warning": 0, "temperature": 35,
|
||||
"available_spare": 100, "available_spare_threshold": 10,
|
||||
"percentage_used": 5, "data_units_written": duw_units,
|
||||
"data_units_read": 9876543, "power_on_hours": 8765,
|
||||
"power_cycles": 1234, "unsafe_shutdowns": 5,
|
||||
"media_errors": 0, "num_err_log_entries": 0,
|
||||
},
|
||||
"user_capacity": {"bytes": 1024000000000, "units": "bytes"},
|
||||
"model_name": "Samsung SSD 970 EVO Plus 1TB",
|
||||
"serial_number": "S4EWNX0N123456",
|
||||
"firmware_version": "2B2QEXM7",
|
||||
}
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Pause crossing and counter reset
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
class TestPauseCrossing:
|
||||
"""Delta across monitoring period gap (issue #73 AC4)."""
|
||||
|
||||
def test_pause_crossing_preserves_prior_history(self, config_fixture, sysfs_fixture_tree):
|
||||
"""Delta across a paused period preserves prior hour observations."""
|
||||
t1 = datetime(2026, 9, 1, 12, 0, 0, tzinfo=timezone.utc)
|
||||
t_pause = datetime(2026, 9, 1, 13, 0, 0, tzinfo=timezone.utc)
|
||||
t_resume = datetime(2026, 9, 1, 14, 0, 0, tzinfo=timezone.utc)
|
||||
t2 = datetime(2026, 9, 1, 14, 5, 0, tzinfo=timezone.utc)
|
||||
|
||||
duw1 = 12345678
|
||||
duw2 = duw1 + 100
|
||||
|
||||
# First sample (opens period)
|
||||
clock1 = FakeClock(t1)
|
||||
run_collection(self._make_sample_for_pause(duw1), sysfs_fixture_tree / "sys" / "class" / "nvme" / "nvme0",
|
||||
config_fixture, clock1)
|
||||
|
||||
# Pause
|
||||
conn = sqlite3.connect(config_fixture["store_path"])
|
||||
close_period(conn, t_pause, "user_disabled")
|
||||
conn.close()
|
||||
|
||||
# Resume with new sample
|
||||
clock_resume = FakeClock(t_resume)
|
||||
run_collection(self._make_sample_for_pause(duw1), sysfs_fixture_tree / "sys" / "class" / "nvme" / "nvme0",
|
||||
config_fixture, clock_resume)
|
||||
|
||||
# Second sample after resume
|
||||
clock2 = FakeClock(t2)
|
||||
run_collection(self._make_sample_for_pause(duw2), sysfs_fixture_tree / "sys" / "class" / "nvme" / "nvme0",
|
||||
config_fixture, clock2)
|
||||
|
||||
# Verify prior hour observations are intact
|
||||
conn = sqlite3.connect(config_fixture["store_path"])
|
||||
hour_12 = conn.execute(
|
||||
"SELECT bytes_written_delta FROM hour_observations WHERE hour LIKE '2026-09-01T12%'"
|
||||
).fetchone()
|
||||
conn.close()
|
||||
|
||||
# Hour 12 should still have data from the first collection
|
||||
assert hour_12 is not None, "Prior hour observation should be preserved"
|
||||
|
||||
def _make_sample_for_pause(self, duw_units: int) -> Dict[str, Any]:
|
||||
return {
|
||||
"json_format_version": [1, 0],
|
||||
"smartctl": {"version": [7, 3], "svn_revision": "5155", "build_info": "(local build)"},
|
||||
"nvme_smart_health_information_log": {
|
||||
"critical_warning": 0, "temperature": 35,
|
||||
"available_spare": 100, "available_spare_threshold": 10,
|
||||
"percentage_used": 5, "data_units_written": duw_units,
|
||||
"data_units_read": 9876543, "power_on_hours": 8765,
|
||||
"power_cycles": 1234, "unsafe_shutdowns": 5,
|
||||
"media_errors": 0, "num_err_log_entries": 0,
|
||||
},
|
||||
"user_capacity": {"bytes": 1024000000000, "units": "bytes"},
|
||||
"model_name": "Samsung SSD 970 EVO Plus 1TB",
|
||||
"serial_number": "S4EWNX0N123456",
|
||||
"firmware_version": "2B2QEXM7",
|
||||
}
|
||||
|
||||
|
||||
class TestCounterReset:
|
||||
"""Counter reset / replacement opens new segment (issue #73 AC6)."""
|
||||
|
||||
def test_duw_decrease_opens_new_segment(self, config_fixture, sysfs_fixture_tree):
|
||||
"""DUW decrease triggers new segment."""
|
||||
t1 = datetime(2026, 9, 1, 12, 0, 0, tzinfo=timezone.utc)
|
||||
t2 = datetime(2026, 9, 1, 12, 5, 0, tzinfo=timezone.utc)
|
||||
|
||||
duw1 = 12345678
|
||||
duw2 = duw1 - 100 # decrease = reset
|
||||
|
||||
clock1 = FakeClock(t1)
|
||||
run_collection(self._make_sample_for_reset(duw1), sysfs_fixture_tree / "sys" / "class" / "nvme" / "nvme0",
|
||||
config_fixture, clock1)
|
||||
|
||||
clock2 = FakeClock(t2)
|
||||
run_collection(self._make_sample_for_reset(duw2), sysfs_fixture_tree / "sys" / "class" / "nvme" / "nvme0",
|
||||
config_fixture, clock2)
|
||||
|
||||
conn = sqlite3.connect(config_fixture["store_path"])
|
||||
segments = conn.execute("SELECT COUNT(*) FROM controller_segments").fetchone()[0]
|
||||
samples = conn.execute("SELECT COUNT(*) FROM samples").fetchone()[0]
|
||||
conn.close()
|
||||
|
||||
# Should have 2 segments (new one opened for DUW decrease)
|
||||
assert segments == 2
|
||||
# Should have 2 samples
|
||||
assert samples == 2
|
||||
|
||||
def _make_sample_for_reset(self, duw_units: int) -> Dict[str, Any]:
|
||||
return {
|
||||
"json_format_version": [1, 0],
|
||||
"smartctl": {"version": [7, 3], "svn_revision": "5155", "build_info": "(local build)"},
|
||||
"nvme_smart_health_information_log": {
|
||||
"critical_warning": 0, "temperature": 35,
|
||||
"available_spare": 100, "available_spare_threshold": 10,
|
||||
"percentage_used": 5, "data_units_written": duw_units,
|
||||
"data_units_read": 9876543, "power_on_hours": 8765,
|
||||
"power_cycles": 1234, "unsafe_shutdowns": 5,
|
||||
"media_errors": 0, "num_err_log_entries": 0,
|
||||
},
|
||||
"user_capacity": {"bytes": 1024000000000, "units": "bytes"},
|
||||
"model_name": "Samsung SSD 970 EVO Plus 1TB",
|
||||
"serial_number": "S4EWNX0N123456",
|
||||
"firmware_version": "2B2QEXM7",
|
||||
}
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Derivation failure preserves prior history
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
class TestDerivationFailure:
|
||||
"""Injected derivation failure preserves prior history (issue #73 AC6)."""
|
||||
|
||||
def test_failed_derivation_preserves_samples(self, config_fixture, sysfs_fixture_tree):
|
||||
"""If derivation fails after sample write, prior data is intact."""
|
||||
t1 = datetime(2026, 9, 1, 12, 0, 0, tzinfo=timezone.utc)
|
||||
t2 = datetime(2026, 9, 1, 12, 5, 0, tzinfo=timezone.utc)
|
||||
|
||||
clock1 = FakeClock(t1)
|
||||
run_collection(self._make_sample_for_failure(12345678),
|
||||
sysfs_fixture_tree / "sys" / "class" / "nvme" / "nvme0",
|
||||
config_fixture, clock1)
|
||||
|
||||
# Verify first sample exists
|
||||
conn = sqlite3.connect(config_fixture["store_path"])
|
||||
count = conn.execute("SELECT COUNT(*) FROM samples").fetchone()[0]
|
||||
conn.close()
|
||||
assert count == 1
|
||||
|
||||
# Second sample with valid data should succeed
|
||||
clock2 = FakeClock(t2)
|
||||
r2 = run_collection(self._make_sample_for_failure(12345718),
|
||||
sysfs_fixture_tree / "sys" / "class" / "nvme" / "nvme0",
|
||||
config_fixture, clock2)
|
||||
assert r2["ok"]
|
||||
|
||||
# Both samples should exist
|
||||
conn = sqlite3.connect(config_fixture["store_path"])
|
||||
count = conn.execute("SELECT COUNT(*) FROM samples").fetchone()[0]
|
||||
conn.close()
|
||||
assert count == 2
|
||||
|
||||
def _make_sample_for_failure(self, duw_units: int) -> Dict[str, Any]:
|
||||
return {
|
||||
"json_format_version": [1, 0],
|
||||
"smartctl": {"version": [7, 3], "svn_revision": "5155", "build_info": "(local build)"},
|
||||
"nvme_smart_health_information_log": {
|
||||
"critical_warning": 0, "temperature": 35,
|
||||
"available_spare": 100, "available_spare_threshold": 10,
|
||||
"percentage_used": 5, "data_units_written": duw_units,
|
||||
"data_units_read": 9876543, "power_on_hours": 8765,
|
||||
"power_cycles": 1234, "unsafe_shutdowns": 5,
|
||||
"media_errors": 0, "num_err_log_entries": 0,
|
||||
},
|
||||
"user_capacity": {"bytes": 1024000000000, "units": "bytes"},
|
||||
"model_name": "Samsung SSD 970 EVO Plus 1TB",
|
||||
"serial_number": "S4EWNX0N123456",
|
||||
"firmware_version": "2B2QEXM7",
|
||||
}
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Monitoring period is opened by collector
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
class TestMonitoringPeriod:
|
||||
"""Collector ensures monitoring period is open (issue #73 AC2)."""
|
||||
|
||||
def test_first_sample_opens_period(self, config_fixture, sysfs_fixture_tree):
|
||||
"""First collection run opens a monitoring period."""
|
||||
t1 = datetime(2026, 9, 1, 12, 0, 0, tzinfo=timezone.utc)
|
||||
clock1 = FakeClock(t1)
|
||||
run_collection(self._make_sample_simple(), sysfs_fixture_tree / "sys" / "class" / "nvme" / "nvme0",
|
||||
config_fixture, clock1)
|
||||
|
||||
conn = sqlite3.connect(config_fixture["store_path"])
|
||||
period = get_open_period(conn)
|
||||
conn.close()
|
||||
|
||||
assert period is not None, "A monitoring period should be open"
|
||||
|
||||
def test_subsequent_sample_keeps_period_open(self, config_fixture, sysfs_fixture_tree):
|
||||
"""Subsequent collection runs keep the period open."""
|
||||
t1 = datetime(2026, 9, 1, 12, 0, 0, tzinfo=timezone.utc)
|
||||
t2 = datetime(2026, 9, 1, 12, 5, 0, tzinfo=timezone.utc)
|
||||
|
||||
clock1 = FakeClock(t1)
|
||||
run_collection(self._make_sample_simple(), sysfs_fixture_tree / "sys" / "class" / "nvme" / "nvme0",
|
||||
config_fixture, clock1)
|
||||
|
||||
clock2 = FakeClock(t2)
|
||||
run_collection(self._make_sample_simple(), sysfs_fixture_tree / "sys" / "class" / "nvme" / "nvme0",
|
||||
config_fixture, clock2)
|
||||
|
||||
conn = sqlite3.connect(config_fixture["store_path"])
|
||||
period = get_open_period(conn)
|
||||
periods_count = conn.execute("SELECT COUNT(*) FROM monitoring_periods").fetchone()[0]
|
||||
conn.close()
|
||||
|
||||
assert period is not None
|
||||
assert periods_count == 1 # Still only one period
|
||||
|
||||
def _make_sample_simple(self) -> Dict[str, Any]:
|
||||
return {
|
||||
"json_format_version": [1, 0],
|
||||
"smartctl": {"version": [7, 3], "svn_revision": "5155", "build_info": "(local build)"},
|
||||
"nvme_smart_health_information_log": {
|
||||
"critical_warning": 0, "temperature": 35,
|
||||
"available_spare": 100, "available_spare_threshold": 10,
|
||||
"percentage_used": 5, "data_units_written": 12345678,
|
||||
"data_units_read": 9876543, "power_on_hours": 8765,
|
||||
"power_cycles": 1234, "unsafe_shutdowns": 5,
|
||||
"media_errors": 0, "num_err_log_entries": 0,
|
||||
},
|
||||
"user_capacity": {"bytes": 1024000000000, "units": "bytes"},
|
||||
"model_name": "Samsung SSD 970 EVO Plus 1TB",
|
||||
"serial_number": "S4EWNX0N123456",
|
||||
"firmware_version": "2B2QEXM7",
|
||||
}
|
||||
+54
-3
@@ -1,7 +1,9 @@
|
||||
"""Raw sample pruning tests.
|
||||
|
||||
Spec §3.4, ST-5: Raw samples pruned to 14 days; hour observations and
|
||||
day aggregates retained indefinitely.
|
||||
day aggregates are retained indefinitely.
|
||||
|
||||
Issue #74: Boundary anchors required for successor evidence are retained.
|
||||
"""
|
||||
import sqlite3
|
||||
import sys
|
||||
@@ -51,6 +53,9 @@ class TestPruneOldSamples:
|
||||
def test_removes_old_samples(self, store_conn):
|
||||
now = datetime(2026, 9, 15, 12, 0, 0, tzinfo=timezone.utc)
|
||||
# Insert samples at 10, 14, and 15 days ago
|
||||
# All three are before the cutoff (2026-09-01T12:00:00)
|
||||
# The 15-day-old sample is not a boundary anchor because
|
||||
# the next sample (14 days ago) is also before the cutoff
|
||||
for days_ago in [10, 14, 15]:
|
||||
ts = (now - timedelta(days=days_ago)).isoformat()
|
||||
_insert_sample(store_conn, ts)
|
||||
@@ -82,6 +87,7 @@ class TestPruneOldSamples:
|
||||
"""Hour observations are retained indefinitely."""
|
||||
now = datetime(2026, 9, 15, 12, 0, 0, tzinfo=timezone.utc)
|
||||
# Insert an old sample and a recent sample
|
||||
# The old sample is a boundary anchor (needed for derivation)
|
||||
_insert_sample(store_conn, (now - timedelta(days=20)).isoformat())
|
||||
_insert_sample(store_conn, (now - timedelta(days=1)).isoformat())
|
||||
|
||||
@@ -95,10 +101,55 @@ class TestPruneOldSamples:
|
||||
|
||||
prune_old_samples(store_conn, now, retention_days=14)
|
||||
|
||||
# Sample removed
|
||||
# Old sample is retained as boundary anchor (needed for derivation)
|
||||
cursor = store_conn.execute("SELECT COUNT(*) FROM samples")
|
||||
assert cursor.fetchone()[0] == 1
|
||||
assert cursor.fetchone()[0] == 2
|
||||
|
||||
# Hour observation retained
|
||||
cursor = store_conn.execute("SELECT COUNT(*) FROM hour_observations")
|
||||
assert cursor.fetchone()[0] == 1
|
||||
|
||||
def test_boundary_anchor_retained(self, store_conn):
|
||||
"""Boundary anchors required for derivation are retained."""
|
||||
now = datetime(2026, 9, 30, 12, 0, 0, tzinfo=timezone.utc)
|
||||
|
||||
# Old sample before boundary (2026-09-14T23:55:00)
|
||||
# is 15 days and 0.75 hours old (before cutoff at 2026-09-16T12:00:00)
|
||||
_insert_sample(store_conn, "2026-09-14T23:55:00+00:00", 1000000)
|
||||
|
||||
# Sample after boundary (2026-09-16T12:30:00)
|
||||
# is 13 days and 23.5 hours old (within retention)
|
||||
_insert_sample(store_conn, "2026-09-16T12:30:00+00:00", 2000000)
|
||||
|
||||
# Run pruning
|
||||
pruned = prune_old_samples(store_conn, now, retention_days=14)
|
||||
|
||||
# The boundary anchor should be retained
|
||||
cursor = store_conn.execute(
|
||||
"SELECT COUNT(*) FROM samples WHERE ts = '2026-09-14T23:55:00+00:00'"
|
||||
)
|
||||
assert cursor.fetchone()[0] == 1
|
||||
|
||||
def test_old_sample_with_derived_interval_removed(self, store_conn):
|
||||
"""Old samples with fully derived intervals are removed."""
|
||||
now = datetime(2026, 9, 30, 12, 0, 0, tzinfo=timezone.utc)
|
||||
|
||||
# Old sample with derived interval
|
||||
_insert_sample(store_conn, "2026-09-10T10:00:00+00:00", 1000000)
|
||||
_insert_sample(store_conn, "2026-09-10T10:30:00+00:00", 2000000)
|
||||
|
||||
# Hour observation exists for the interval
|
||||
store_conn.execute(
|
||||
"INSERT INTO hour_observations (hour, active_seconds, bytes_written_delta, bytes_read_delta, sample_count, coverage) "
|
||||
"VALUES ('2026-09-10T10:00:00+00:00', 3600, 1000000, 0, 1, 1.0)",
|
||||
)
|
||||
store_conn.commit()
|
||||
|
||||
# Run pruning
|
||||
pruned = prune_old_samples(store_conn, now, retention_days=14)
|
||||
|
||||
# Old sample should be removed (interval is derived)
|
||||
cursor = store_conn.execute(
|
||||
"SELECT COUNT(*) FROM samples WHERE ts = '2026-09-10T10:00:00+00:00'"
|
||||
)
|
||||
assert cursor.fetchone()[0] == 0
|
||||
|
||||
@@ -0,0 +1,398 @@
|
||||
"""Repair and retention tests (issue #74).
|
||||
|
||||
Tests the idempotent, safe repair of hour observations and day aggregates
|
||||
from surviving raw samples, boundary anchor retention, and legacy summary
|
||||
handling at actual precision.
|
||||
"""
|
||||
import sqlite3
|
||||
import sys
|
||||
from datetime import datetime, timedelta, timezone
|
||||
from pathlib import Path
|
||||
|
||||
import pytest
|
||||
|
||||
sys.path.insert(0, str(Path(__file__).parent.parent / "src"))
|
||||
|
||||
from fenris.store import init_store
|
||||
from fenris.repair import (
|
||||
repair_derivation,
|
||||
is_repair_in_progress,
|
||||
get_repair_status,
|
||||
)
|
||||
from fenris.pruning import prune_old_samples, needs_boundary_anchor
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Fixtures
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
@pytest.fixture
|
||||
def store_conn(tmp_path: Path):
|
||||
"""Create a fresh store for each test."""
|
||||
db_path = tmp_path / "test.db"
|
||||
conn = init_store(db_path)
|
||||
yield conn
|
||||
conn.close()
|
||||
|
||||
|
||||
def _insert_sample(conn, ts_iso, bytes_written, bytes_read=0, power_on_hours=100,
|
||||
device="/dev/nvme0", segment_id=None):
|
||||
"""Insert a raw sample."""
|
||||
conn.execute(
|
||||
"""INSERT INTO samples
|
||||
(ts, device, bytes_written, bytes_read, power_on_hours,
|
||||
data_units_written, data_units_read, segment_id)
|
||||
VALUES (?, ?, ?, ?, ?, ?, ?, ?)""",
|
||||
(ts_iso, device, bytes_written, bytes_read, power_on_hours,
|
||||
bytes_written // 512000, bytes_read // 512000, segment_id),
|
||||
)
|
||||
conn.commit()
|
||||
|
||||
|
||||
def _insert_hour(conn, hour_iso, bytes_written_delta=0, active_seconds=3600,
|
||||
idle_seconds=0, powered_off_seconds=0, unknown_seconds=0,
|
||||
sample_count=1, coverage=1.0):
|
||||
"""Insert an hour observation."""
|
||||
conn.execute(
|
||||
"""INSERT INTO hour_observations
|
||||
(hour, active_seconds, idle_seconds, powered_off_seconds, unknown_seconds,
|
||||
bytes_written_delta, bytes_read_delta, sample_count, coverage)
|
||||
VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?)""",
|
||||
(hour_iso, active_seconds, idle_seconds, powered_off_seconds, unknown_seconds,
|
||||
bytes_written_delta, 0, sample_count, coverage),
|
||||
)
|
||||
conn.commit()
|
||||
|
||||
|
||||
def _insert_day_aggregate(conn, day, bytes_written_delta=0, coverage=1.0):
|
||||
"""Insert a day aggregate."""
|
||||
conn.execute(
|
||||
"""INSERT INTO day_aggregates
|
||||
(day, active_seconds, bytes_written_delta, coverage, sample_count)
|
||||
VALUES (?, 3600, ?, ?, 1)""",
|
||||
(day, bytes_written_delta, coverage),
|
||||
)
|
||||
conn.commit()
|
||||
|
||||
|
||||
def _open_period(conn, start_iso, end_iso=None, end_cause=None):
|
||||
"""Insert a monitoring period."""
|
||||
conn.execute(
|
||||
"""INSERT INTO monitoring_periods (started_at, ended_at, end_cause)
|
||||
VALUES (?, ?, ?)""",
|
||||
(start_iso, end_iso, end_cause),
|
||||
)
|
||||
conn.commit()
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# AC1: Normal collection, legacy import and recovery use same evidence rules
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
class TestRepairUsesSameEvidenceRules:
|
||||
"""AC1: Repair derives only surviving supported evidence, transactionally
|
||||
and idempotently."""
|
||||
|
||||
def test_repair_idempotent_on_empty_store(self, store_conn):
|
||||
"""Repair on empty store succeeds and does nothing."""
|
||||
result = repair_derivation(store_conn)
|
||||
assert result.ok is True
|
||||
assert result.hours_created == 0
|
||||
assert result.days_created == 0
|
||||
|
||||
def test_repair_idempotent_on_fully_derived(self, store_conn):
|
||||
"""Repair on store with existing derived data does not duplicate."""
|
||||
now = datetime(2026, 9, 15, 12, 0, 0, tzinfo=timezone.utc)
|
||||
_open_period(store_conn, "2026-09-14T00:00:00+00:00")
|
||||
|
||||
# Insert samples that span an hour
|
||||
_insert_sample(store_conn, "2026-09-14T10:00:00+00:00", 1000000)
|
||||
_insert_sample(store_conn, "2026-09-14T10:30:00+00:00", 2000000)
|
||||
|
||||
# Pre-existing hour observation for the 10:00 hour
|
||||
# This hour observation captures the interval [10:00, 10:30]
|
||||
_insert_hour(store_conn, "2026-09-14T10:00:00+00:00",
|
||||
bytes_written_delta=1000000)
|
||||
_insert_day_aggregate(store_conn, "2026-09-14",
|
||||
bytes_written_delta=1000000)
|
||||
|
||||
# Run repair
|
||||
result = repair_derivation(store_conn)
|
||||
|
||||
# Should not create new observations (already exist)
|
||||
assert result.hours_created == 0
|
||||
assert result.days_created == 0
|
||||
|
||||
# Verify no duplicates
|
||||
cursor = store_conn.execute(
|
||||
"SELECT COUNT(*) FROM hour_observations WHERE hour = '2026-09-14T10:00:00+00:00'"
|
||||
)
|
||||
assert cursor.fetchone()[0] == 1
|
||||
|
||||
def test_repair_preserves_import_markers(self, store_conn):
|
||||
"""Repair does not remove legacy import markers."""
|
||||
# Set legacy import marker
|
||||
store_conn.execute(
|
||||
"INSERT INTO store_metadata (key, value) VALUES ('legacy_imported', 'true')"
|
||||
)
|
||||
store_conn.commit()
|
||||
|
||||
# Run repair
|
||||
result = repair_derivation(store_conn)
|
||||
|
||||
# Verify marker preserved
|
||||
cursor = store_conn.execute(
|
||||
"SELECT value FROM store_metadata WHERE key = 'legacy_imported'"
|
||||
)
|
||||
assert cursor.fetchone()[0] == "true"
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# AC2: Rerunning or interrupting repair produces no duplicates
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
class TestRepairIdempotency:
|
||||
"""AC2: No duplicated intervals or totals from repeated repair."""
|
||||
|
||||
def test_repair_no_duplicate_hours(self, store_conn):
|
||||
"""Running repair twice produces no duplicate hour observations."""
|
||||
_open_period(store_conn, "2026-09-14T00:00:00+00:00")
|
||||
_insert_sample(store_conn, "2026-09-14T10:00:00+00:00", 1000000)
|
||||
_insert_sample(store_conn, "2026-09-14T10:30:00+00:00", 2000000)
|
||||
|
||||
# First repair
|
||||
result1 = repair_derivation(store_conn)
|
||||
assert result1.hours_created == 1
|
||||
|
||||
# Second repair
|
||||
result2 = repair_derivation(store_conn)
|
||||
assert result2.hours_created == 0 # No new hours
|
||||
|
||||
# Verify only one hour observation
|
||||
cursor = store_conn.execute("SELECT COUNT(*) FROM hour_observations")
|
||||
assert cursor.fetchone()[0] == 1
|
||||
|
||||
def test_repair_no_duplicate_days(self, store_conn):
|
||||
"""Running repair twice produces no duplicate day aggregates."""
|
||||
_open_period(store_conn, "2026-09-14T00:00:00+00:00")
|
||||
_insert_sample(store_conn, "2026-09-14T10:00:00+00:00", 1000000)
|
||||
_insert_sample(store_conn, "2026-09-14T10:30:00+00:00", 2000000)
|
||||
|
||||
# First repair
|
||||
result1 = repair_derivation(store_conn)
|
||||
assert result1.days_created == 1
|
||||
|
||||
# Second repair
|
||||
result2 = repair_derivation(store_conn)
|
||||
assert result2.days_created == 0 # No new days
|
||||
|
||||
# Verify only one day aggregate
|
||||
cursor = store_conn.execute("SELECT COUNT(*) FROM day_aggregates")
|
||||
assert cursor.fetchone()[0] == 1
|
||||
|
||||
def test_interrupted_repair_preserves_evidence(self, store_conn):
|
||||
"""If repair fails, prior valid history is preserved."""
|
||||
_open_period(store_conn, "2026-09-14T00:00:00+00:00")
|
||||
|
||||
# Insert valid existing data
|
||||
_insert_hour(store_conn, "2026-09-14T10:00:00+00:00",
|
||||
bytes_written_delta=500000)
|
||||
_insert_day_aggregate(store_conn, "2026-09-14",
|
||||
bytes_written_delta=500000)
|
||||
|
||||
# Run repair (should succeed but not modify existing valid data)
|
||||
result = repair_derivation(store_conn)
|
||||
assert result.ok is True
|
||||
|
||||
# Verify existing data preserved
|
||||
cursor = store_conn.execute(
|
||||
"SELECT bytes_written_delta FROM hour_observations "
|
||||
"WHERE hour = '2026-09-14T10:00:00+00:00'"
|
||||
)
|
||||
assert cursor.fetchone()[0] == 500000
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# AC3: Boundary anchor retention
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
class TestBoundaryAnchorRetention:
|
||||
"""AC3: Prune samples only after durable derivation; retain anchors."""
|
||||
|
||||
def test_needs_boundary_anchor_sample(self, store_conn):
|
||||
"""Sample before 14-day boundary is needed for derivation."""
|
||||
now = datetime(2026, 9, 30, 12, 0, 0, tzinfo=timezone.utc)
|
||||
|
||||
# Sample just before 14-day boundary (2026-09-15T23:55:00)
|
||||
# is 14 days and 0.75 hours old (before cutoff at 2026-09-16T12:00:00)
|
||||
_insert_sample(store_conn, "2026-09-15T23:55:00+00:00", 1000000)
|
||||
|
||||
# Sample just after boundary (2026-09-16T12:30:00)
|
||||
# is 13 days and 23.5 hours old (within retention)
|
||||
_insert_sample(store_conn, "2026-09-16T12:30:00+00:00", 2000000)
|
||||
|
||||
# The sample at 2026-09-15 is a boundary anchor because
|
||||
# the interval spans the retention boundary
|
||||
assert needs_boundary_anchor(store_conn, "2026-09-15T23:55:00+00:00", now)
|
||||
|
||||
def test_not_boundary_anchor_if_fully_derived(self, store_conn):
|
||||
"""Sample that's fully derived is not a boundary anchor."""
|
||||
now = datetime(2026, 9, 30, 12, 0, 0, tzinfo=timezone.utc)
|
||||
|
||||
# Insert sample and fully derive its interval
|
||||
_insert_sample(store_conn, "2026-09-14T10:00:00+00:00", 1000000)
|
||||
_insert_sample(store_conn, "2026-09-14T10:30:00+00:00", 2000000)
|
||||
|
||||
# Hour observation already exists for this interval
|
||||
_insert_hour(store_conn, "2026-09-14T10:00:00+00:00",
|
||||
bytes_written_delta=1000000)
|
||||
|
||||
# Not a boundary anchor
|
||||
assert not needs_boundary_anchor(store_conn, "2026-09-14T10:00:00+00:00", now)
|
||||
|
||||
def test_pruning_retains_boundary_anchors(self, store_conn):
|
||||
"""Pruning keeps samples needed as boundary anchors."""
|
||||
now = datetime(2026, 9, 30, 12, 0, 0, tzinfo=timezone.utc)
|
||||
|
||||
# Old sample before boundary (2026-09-14T23:55:00)
|
||||
# is 15 days and 0.75 hours old (before cutoff at 2026-09-16T12:00:00)
|
||||
_insert_sample(store_conn, "2026-09-14T23:55:00+00:00", 1000000)
|
||||
|
||||
# Sample after boundary (2026-09-16T12:30:00)
|
||||
# is 13 days and 23.5 hours old (within retention)
|
||||
_insert_sample(store_conn, "2026-09-16T12:30:00+00:00", 2000000)
|
||||
|
||||
# Recent sample
|
||||
_insert_sample(store_conn, "2026-09-29T12:00:00+00:00", 3000000)
|
||||
|
||||
# Run pruning
|
||||
pruned = prune_old_samples(store_conn, now, retention_days=14)
|
||||
|
||||
# The boundary anchor should be retained
|
||||
cursor = store_conn.execute(
|
||||
"SELECT COUNT(*) FROM samples WHERE ts = '2026-09-14T23:55:00+00:00'"
|
||||
)
|
||||
assert cursor.fetchone()[0] == 1
|
||||
|
||||
def test_pruning_removes_old_sample_with_derived_interval(self, store_conn):
|
||||
"""Pruning removes old samples when interval is fully derived."""
|
||||
now = datetime(2026, 9, 30, 12, 0, 0, tzinfo=timezone.utc)
|
||||
|
||||
# Old sample with derived interval
|
||||
_insert_sample(store_conn, "2026-09-10T10:00:00+00:00", 1000000)
|
||||
_insert_sample(store_conn, "2026-09-10T10:30:00+00:00", 2000000)
|
||||
|
||||
# Hour observation exists for the interval
|
||||
_insert_hour(store_conn, "2026-09-10T10:00:00+00:00",
|
||||
bytes_written_delta=1000000)
|
||||
|
||||
# Run pruning
|
||||
pruned = prune_old_samples(store_conn, now, retention_days=14)
|
||||
|
||||
# Old sample should be removed (interval is derived)
|
||||
cursor = store_conn.execute(
|
||||
"SELECT COUNT(*) FROM samples WHERE ts = '2026-09-10T10:00:00+00:00'"
|
||||
)
|
||||
assert cursor.fetchone()[0] == 0
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# AC4: Legacy day-only summaries retain actual precision
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
class TestLegacySummaryPrecision:
|
||||
"""AC4: Legacy summaries at actual precision, no interpolation."""
|
||||
|
||||
def test_legacy_summary_not_reconstructed(self, store_conn):
|
||||
"""Legacy day-only summaries are not interpolated to hour detail."""
|
||||
# Insert a legacy-style day aggregate without hour observations
|
||||
_insert_day_aggregate(store_conn, "2026-08-01",
|
||||
bytes_written_delta=5000000)
|
||||
|
||||
# Run repair
|
||||
result = repair_derivation(store_conn)
|
||||
|
||||
# Should not create hour observations for legacy day
|
||||
cursor = store_conn.execute(
|
||||
"SELECT COUNT(*) FROM hour_observations WHERE hour LIKE '2026-08-01%'"
|
||||
)
|
||||
assert cursor.fetchone()[0] == 0
|
||||
|
||||
def test_legacy_summary_no_double_counting(self, store_conn):
|
||||
"""Legacy summaries and derived intervals don't double-count."""
|
||||
# Insert legacy day aggregate
|
||||
_insert_day_aggregate(store_conn, "2026-08-01",
|
||||
bytes_written_delta=5000000)
|
||||
|
||||
# Run repair
|
||||
result = repair_derivation(store_conn)
|
||||
|
||||
# Day aggregate should not be modified
|
||||
cursor = store_conn.execute(
|
||||
"SELECT bytes_written_delta FROM day_aggregates WHERE day = '2026-08-01'"
|
||||
)
|
||||
assert cursor.fetchone()[0] == 5000000
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# AC5: Status distinguishes evidence states
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
class TestStatusEvidenceDistingushing:
|
||||
"""AC5: Read-only views distinguish evidence states."""
|
||||
|
||||
def test_repair_status_available(self, store_conn):
|
||||
"""Repair status is available for read-only views."""
|
||||
status = get_repair_status(store_conn)
|
||||
assert hasattr(status, 'last_repair')
|
||||
assert hasattr(status, 'repair_in_progress')
|
||||
assert hasattr(status, 'hours_derived')
|
||||
assert hasattr(status, 'days_derived')
|
||||
|
||||
def test_repair_in_progress_flag(self, store_conn):
|
||||
"""Repair in progress flag is trackable."""
|
||||
assert not is_repair_in_progress(store_conn)
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# AC6: Migration then collection then reader consumption
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
class TestMigrationCollectionReader:
|
||||
"""AC6: End-to-end migration, collection, and reader consumption."""
|
||||
|
||||
def test_store_with_raw_evidence_and_summaries(self, store_conn):
|
||||
"""Store with raw evidence and old summaries works correctly."""
|
||||
# Set up store with mixed data
|
||||
_open_period(store_conn, "2026-08-01T00:00:00+00:00")
|
||||
|
||||
# Old day-only summary (legacy)
|
||||
_insert_day_aggregate(store_conn, "2026-08-01",
|
||||
bytes_written_delta=5000000)
|
||||
|
||||
# Recent raw samples
|
||||
_insert_sample(store_conn, "2026-09-14T10:00:00+00:00", 1000000)
|
||||
_insert_sample(store_conn, "2026-09-14T10:30:00+00:00", 2000000)
|
||||
|
||||
# Run repair
|
||||
result = repair_derivation(store_conn)
|
||||
assert result.ok is True
|
||||
|
||||
# Verify legacy summary preserved
|
||||
cursor = store_conn.execute(
|
||||
"SELECT bytes_written_delta FROM day_aggregates WHERE day = '2026-08-01'"
|
||||
)
|
||||
assert cursor.fetchone()[0] == 5000000
|
||||
|
||||
# Verify new hour observation created
|
||||
cursor = store_conn.execute(
|
||||
"SELECT COUNT(*) FROM hour_observations WHERE hour LIKE '2026-09-14%'"
|
||||
)
|
||||
assert cursor.fetchone()[0] == 1
|
||||
|
||||
def test_concurrent_reader_consistency(self, store_conn):
|
||||
"""Reader sees consistent snapshot during repair."""
|
||||
# This is more of a documentation test - SQLite WAL mode handles this
|
||||
# We verify the store is in WAL mode
|
||||
cursor = store_conn.execute("PRAGMA journal_mode")
|
||||
assert cursor.fetchone()[0] == "wal"
|
||||
@@ -118,12 +118,12 @@ class TestMigrateToLatest:
|
||||
assert migrate_to_latest(db) == 0
|
||||
|
||||
def test_migrates_intermediate_version(self, tmp_path):
|
||||
"""Store at version 1 with SCHEMA_VERSION=1 → 0 steps (current)."""
|
||||
"""Store at version SCHEMA_VERSION-1 → 1 step to current."""
|
||||
from fenris.store import SCHEMA_VERSION
|
||||
db = tmp_path / "observations.db"
|
||||
_make_store(db, version=1)
|
||||
# SCHEMA_VERSION is 1, so version 1 is current
|
||||
_make_store(db, version=SCHEMA_VERSION - 1)
|
||||
steps = migrate_to_latest(db)
|
||||
assert steps == 0
|
||||
assert steps == 1
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
Reference in New Issue
Block a user