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trainlog/docs/current_state.md

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Current implementation state

Snapshot date: 2026-09-16.

This document owns the current implemented state. Historical checkpoints and closed incidents belong in reviews and the changelog.

Product boundary

Android is the field companion: it captures training and body data, preserves the active draft, receives AI proposals, triggers synchronization, and shows quick summaries. The C17/Notcurses TUI is the administration, inspection, maintenance, import/export, and technical-tooling surface. The local Web sibling now provides its embedded application shell; its future business surfaces will own analysis, visualization, and program/session preparation through Trainlog Core.

Trainlog Core owns business truth. The desktop SQLite database remains the canonical local source of truth and long-term history; no interface owns a parallel implementation of its rules.

Versions and compatibility

Boundary Current state
Frozen project exchange TRAINLOG_FORMAT_V1=PASS/FROZEN
Desktop SQLite schema v18
Android SQLite schema v17
Mobile snapshot V3 active; V1/V2 readable legacy inputs
Desktop terminal backend Notcurses only
Trainlog product version 0.1.2 development, synchronized across Android and desktop; latest stable release: v0.1.1
Interface language TRAINLOG_I18N_V0_1_1=PASS: French default; English selectable in Settings → Language on both surfaces
AI history export TRAINLOG_AI_EXPORT_V1 active
AI session proposals TRAINLOG_AI_SESSION_DRAFT_V1=VALIDATION_PENDING
Training knowledge TRAINING_KNOWLEDGE_V1=PASS
Session generator SESSION_GENERATOR_V1=PASS, hidden pending V2
Application shell APP_SHELL_V1=IMPLEMENTED_AWAITING_VISUAL_REVIEW_2
Statistics STATS_V1=IMPLEMENTED
Dashboard characterization WEB_DASHBOARD_CHARACTERIZATION_V1=PASS/FROZEN
Dashboard Core read model WEB_DASHBOARD_CORE_READ_MODEL_V1=PASS/FROZEN
TUI Dashboard adoption WEB_TUI_READ_MODEL_ADOPTION_V1=PASS/FROZEN
Web CLI/HTTP infrastructure WEB_CLI_HTTP_INFRASTRUCTURE_V1=PASS/FROZEN
Web frontend shell WEB_FRONTEND_SHELL_V1=PASS/FROZEN
Web Dashboard grid WEB_DASHBOARD_GRID_V1=PASS/FROZEN
Web Dashboard layout WEB_DASHBOARD_LAYOUT_V1=PASS/FROZEN
Web Dashboard tiles WEB_DASHBOARD_TILES_V1=PASS/FROZEN
Local Web TRAINLOG_WEB_V1=CONTRACT_FROZEN / IMPLEMENTATION_STARTED

Desktop and Android schema numbers are independent. Neither changes the frozen Trainlog JSON V1 contract.

Language is device-local presentation state. Android keeps it in dedicated SharedPreferences; desktop keeps it in the XDG configuration file trainlog/presentation.conf. A successful selection updates the UI immediately. It does not enter either SQLite database, training data, stable IDs, schemas, exchange artifacts, synchronization protocols, AI proposals, MAX, or feedback. User-defined exercise and catalogue names are never automatically translated. Where a recognized stable body-zone ID has a local presentation label, only that label is localized; unknown IDs retain their catalogue label. Numbers, dates, and other visible formatting are owned by the selected presentation language.

Synchronization remains a protocol boundary: core, receipt, and persisted history summaries stay opaque operational bytes. Android and the TUI render their current synchronization state from local typed status and counters; they never inject a raw cross-device French summary into the visible interface. No raw exchange or protocol format changed for interface language support.

Storage and synchronization

  • Android stores capture data in its private SQLite database.
  • Android reads and writes exchange artifacts only in /storage/emulated/0/Documents/Trainlog after the user grants all-files access through system settings.
  • The old SAF/tree-URI path and Download/Trainlog are historical recovery boundaries, not active storage choices.
  • Desktop synchronization uses direct libudev/libmtp discovery and object access. No GVFS/FUSE mount is required.
  • trainlog_sync_run() is shared by the TUI and trainlog-syncd.
  • The desktop imports Android snapshots, publishes catalog/profile/feedback/AI companions, and returns a receipt. Stable IDs and tombstones make defined replay paths idempotent.
  • SQLite database files are never synchronized.
  • The desktop AI flow uses external rclone for Drive inbox/archive and read-only history export. Android owns no Drive credentials.

Android

Android currently provides:

  • metadata-driven SETS+REPS, SETS+DURATION, and CONTINUOUS+DURATION capture;
  • actual per-set values, optional occurrence equipment, and explicit MAX rows;
  • exactly one durable active session draft with identity-preserving continuous multi-position drag reorder, resume, confirmed discard, and atomic completion;
  • completed-session consultation, transient drag reorder, and atomic factual or order correction while retaining session/occurrence/feedback identities for synchronization;
  • exercise catalogue editing with stable exercise_id and referenced-profile protection;
  • supplied/custom equipment and machine-exercise metadata;
  • body measurements and recent BODY ZONES summaries;
  • immediate exercise feedback, immutable wording revisions, and J+1/session follow-ups;
  • pending AI proposal collection, explicit start/delete, and durable tombstones;
  • 7/30/90-day, year, and all-history quick statistics;
  • direct-storage snapshot publication, sync triggering, locally rendered typed receipt status/counters, and companion application.
  • French-default/English-selectable presentation from Settings → Language, applied immediately without changing repository or synchronization state.

Android does not own canonical long-term analytics. The V1 session generator is implemented but intentionally hidden from normal navigation pending V2.

Desktop TUI

The desktop is a strict C17 application using Notcurses. It currently provides:

  • a keyboard-first seven-section shell, semantic true-color roles, UTF-8 input, resize recovery, and a 72x20 minimum-terminal fallback;
  • session creation, history, detail, and transactional correction;
  • exercise and equipment catalogue management;
  • explicit measured-MAX consultation and working-load calculations;
  • body observation history, correction, derived analytics, and longitudinal graphs;
  • statistics derived from canonical occurrence-owned actual work, including exact calendar-week/month buckets, performance, body, frequency, exercise, and BODY ZONES views;
  • detailed locally rendered typed synchronization status/history through the shared engine.
  • French-default/English-selectable presentation from Settings → Language, including selected-language formatting without changing canonical data.

Rendering is not permitted to own SQL or business rules. Statistics are read-only projections; they are not persisted as facts. The former Dashboard exception is resolved: its typed Core read model owns the SQLite projection and all characterized calculations, while the TUI supplies query state and renders the result. The Web aggregate now exposes the distinct factual snapshot through GET /api/v1/dashboard without changing the frozen TUI projection.

Local Web

TRAINLOG_WEB_V1 architecture, API independence, local-network boundary, browser shell, Dashboard, layout ownership, build/runtime separation, and security invariants are canonical. The CLI/local HTTP infrastructure and embedded frontend shell are implemented: -w/--web, optional --port, exact IPv4 loopback binding, /api/v1/health, React navigation and the persistent Header/Body/Footer shell. Production assets are generated from the npm lockfile and linked into the binary. The read-only Dashboard business snapshot and factual Footer integration exist; no grid engine, business mutation, automatic browser launch or layout persistence exists yet.

Data semantics

  • exercise_id identifies a catalogue exercise; entry_id identifies one ordered occurrence in a session.
  • Plans and performed work are distinct. A continuous activity is not a fake performed set, and actual repetitions may be heterogeneous.
  • Explicit MAX results are occurrence-owned and distinct from ordinary best sets. Equipment/resistance/execution context remains relevant.
  • BODY ZONES are a UX/business projection over explicit scientific knowledge, not a complete anatomical taxonomy.
  • Feedback roots retain identity while append-only revisions preserve wording history. J+1/session follow-ups are session-owned.
  • AI proposals contain target-only plans and never create performed work, history, MAX, or feedback until the user explicitly starts and completes a normal capture draft.

Validation status

The durable commands are owned by tests.md. On 2026-09-15 final validation passed desktop compilation, 60/60 normal Meson tests and 60/60 ASan/UBSan Meson tests, Android debug assembly and 202 Android tests (198 passed, 4 skipped, 0 failed), the JSON validator, and the import-contract validator. The source-derived TUI TRANSLATABLE_UI=0 check and Android resource parity also passed. Link and diff safety checks pass in the final audit evidence.

The Dashboard Core extraction tranche passes 62/62 normal Meson tests and 62/62 ASan/UBSan Meson tests, including the standalone public-header and Core characterization targets, plus both canonical JSON validators.

The CLI/HTTP infrastructure tranche passes 67/67 normal Meson tests, adding pure CLI parsing, process-level help/version checks and an isolated loopback HTTP lifecycle/security suite. The same suite is required under ASan/UBSan.

The frontend shell tranche passes 70/70 normal and ASan/UBSan Meson tests, including TypeScript typecheck, 10 Vitest component tests, deterministic asset generation bounds, real embedded-asset HTTP coverage, SPA/API separation and runtime execution without Node/npm or web/dist.

The Dashboard data-contract tranche passes 71/71 normal and ASan/UBSan Meson tests, including the bounded Core/JSON target, HTTP endpoint coverage and 12 Vitest tests for parsing and factual Footer integration.

WEB_DASHBOARD_GRID_V1=PASS/FROZEN uses react-grid-layout 2.2.4 behind an independent Trainlog model/validator. Its 12-column desktop layout has seven stable tile IDs, bounded per-tile dimensions, vertical collision compaction, explicit edit/cancel/reset behavior, mouse drag/two-axis resize, an announced keyboard alternative, and derived six/one-column responsive projections. Persistence is supplied by the following frozen slice.

WEB_DASHBOARD_LAYOUT_V1=PASS/FROZEN adds a strict versioned seven-tile file under the private XDG configuration directory, backend revalidation, atomic 0600 replacement, ETag/If-Match conflict control, Origin plus ephemeral CSRF protection, and durable React load/save/reset behavior. Only the desktop 12-column canon persists.

WEB_DASHBOARD_TILES_V1=PASS/FROZEN renders all seven domains from the one validated /api/v1/dashboard snapshot. Compact, medium and large densities only reveal existing facts. Activity uses a factual CSS day map, MAX lists are bounded 1/3/8, and muscle bars encode session_count only. Unavailable, partial, invalid and transport-error states never synthesize values.

TRAINLOG_I18N_V0_1_1=PASS is covered by desktop presentation, persistence, formatting, layout-invariance and source-derived text-boundary tests, plus Android resource-parity, language-owner, typed sync-presentation, and stable-data presentation tests. A real-device/manual visual language-switch smoke remains a manual validation; it does not change the validated status.

Hardware-dependent MTP and the final real Drive plus Android-triggered AI-draft smoke test are not automated. The latter is why TRAINLOG_AI_SESSION_DRAFT_V1 remains VALIDATION_PENDING.

Active limitations

  • WEB_DASHBOARD_VISUALIZATIONS_V1: advanced curves and muscle visualization remain future work; Tile V1 intentionally uses bounded text, CSS and direct factual encodings without ECharts.
  • APP_SHELL_V1 still awaits the recorded human visual/accessibility review.
  • AI proposal exchange still awaits one real Drive plus Android-triggered bidirectional smoke test.
  • Session Generator V1 is hidden while V2 planning semantics are developed.
  • Hardware MTP validation requires a connected unlocked Android device.
  • Scientific knowledge is bounded to reviewed catalog entries; unknown custom exercises remain unclassified rather than inferred from names.