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maziggy
1e734fb7c6
Reporter (@IndividualGhost1905) saw Total: 20 / Success: 18 / Failed: 1 and asked where the 20th print went. The Quick Stats endpoint counted status == "completed" → Successful and status == "failed" → Failed, but used a raw count(*) for Total Prints, so the four other PrintLogEntry statuses (aborted, stopped, cancelled, skipped) silently inflated the total without showing up in any breakdown row. The earlier #1390 round had committed a test locking in this exact behaviour ("uses total_prints as denominator so cancelled/stopped events count"), which was wrong: it conflated user intent with print quality. Three-bucket classification, applied across the whole stats surface and matching how the rest of the codebase already groups statuses (main.py:430, 1729; failure_analysis status filter): successful = completed failed = failed + aborted (printer-detected quality failures) cancelled = stopped + cancelled + skipped (user/queue stopped) Quick Stats endpoint returns the new cancelled_prints field; ArchiveStats.cancelled_prints defaults to 0 so older fixtures still parse. SuccessRateWidget gauge now divides by successful + failed only — a cancelled roll no longer drags the gauge down — and a Cancelled row appears in the breakdown so the missing prints don't silently vanish from Total Prints. Failure Analysis service applies the same denominator fix to both the headline failure_rate and the per-week trend, so a week with several cancellations and zero failures reads as 0% rather than a misleading "failed / total". i18n: new stats.cancelled key in all 9 locales with real translations (no English fallback), parity script clean. Tests: the existing 'uses total_prints as denominator' assertion is inverted to assert the new behaviour (40 / 20 / 35 → 67% gauge, Cancelled: 35 visible). The unchanged-display path (140 / 10 / 0 → 93%) still holds since 140 / (140 + 10) = 93.33% rounds the same. 33 StatsPage tests + 6 backend stats/failure tests green.