367 lines
22 KiB
Python
367 lines
22 KiB
Python
#!/usr/bin/env python3
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"""Production V3 session exchange regression coverage."""
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import copy
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import json
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import sqlite3
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import subprocess
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import sys
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import tempfile
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from pathlib import Path
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ROOT = Path(__file__).resolve().parents[1]
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IMPORTER = ROOT / "tools/import_mobile_export.py"
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EXPORTER = ROOT / "tools/export_pc_mobile.py"
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from test_mobile_import_variable_sets import SCHEMA
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V11_SCHEMA = SCHEMA.replace("PRAGMA user_version=10;", "") + """
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CREATE TABLE exercise_body_zones(
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exercise_row_id INTEGER NOT NULL REFERENCES exercises(id) ON DELETE CASCADE,
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zone_id TEXT NOT NULL, role TEXT NOT NULL,
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PRIMARY KEY(exercise_row_id,zone_id));
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CREATE TABLE exercise_body_zone_sync(
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exercise_row_id INTEGER PRIMARY KEY REFERENCES exercises(id) ON DELETE CASCADE,
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synced_primary_zone_id TEXT, synced_secondary_zone_ids TEXT NOT NULL);
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PRAGMA user_version=11;
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"""
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V16_SCHEMA = V11_SCHEMA.replace("PRAGMA user_version=11;", "") + """
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ALTER TABLE exercises ADD COLUMN load_semantics TEXT;
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ALTER TABLE exercises ADD COLUMN machine_variant TEXT;
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ALTER TABLE exercises ADD COLUMN machine_provenance TEXT;
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ALTER TABLE exercises ADD COLUMN scientific_profile_id TEXT;
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ALTER TABLE exercises ADD COLUMN science_state TEXT NOT NULL DEFAULT 'unresolved';
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ALTER TABLE exercises ADD COLUMN legacy_equipment_id TEXT;
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ALTER TABLE session_exercises ADD COLUMN tracking_mode TEXT NOT NULL DEFAULT 'reps';
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CREATE TABLE exercise_aliases(source_exercise_id TEXT PRIMARY KEY,canonical_exercise_id TEXT NOT NULL);
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CREATE TABLE exercise_feedback(id INTEGER PRIMARY KEY,feedback_id TEXT NOT NULL UNIQUE,
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session_exercise_row_id INTEGER NOT NULL REFERENCES session_exercises(id) ON DELETE CASCADE,
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observed_at TEXT NOT NULL,raw_text TEXT NOT NULL);
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CREATE TABLE exercise_feedback_revisions(revision_id TEXT PRIMARY KEY,feedback_id TEXT NOT NULL,
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created_at TEXT NOT NULL,raw_text TEXT NOT NULL);
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CREATE TABLE session_followups(id INTEGER PRIMARY KEY,followup_id TEXT NOT NULL UNIQUE,
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session_row_id INTEGER NOT NULL REFERENCES sessions(id) ON DELETE CASCADE,
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observed_at TEXT NOT NULL,raw_text TEXT NOT NULL);
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CREATE TABLE session_followup_revisions(revision_id TEXT PRIMARY KEY,followup_id TEXT NOT NULL,
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created_at TEXT NOT NULL,raw_text TEXT NOT NULL);
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PRAGMA user_version=16;
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"""
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V20_SCHEMA = V16_SCHEMA.replace("PRAGMA user_version=16;", "") + """
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CREATE TABLE sync_note_state(
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owner_kind TEXT NOT NULL,owner_id TEXT NOT NULL,revision_id TEXT NOT NULL,
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parent_revision_id TEXT,value TEXT,PRIMARY KEY(owner_kind,owner_id));
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CREATE TABLE sync_causal_operations(
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operation_id TEXT PRIMARY KEY,target_kind TEXT NOT NULL,target_id TEXT NOT NULL,
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creator_id TEXT NOT NULL,predecessor_revision_id TEXT NOT NULL,created_at TEXT NOT NULL,
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payload_sha256 TEXT NOT NULL,publication_context TEXT);
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CREATE TABLE sync_causal_state(
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target_kind TEXT NOT NULL,target_id TEXT NOT NULL,current_revision_id TEXT NOT NULL,
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deleted INTEGER NOT NULL,operation_id TEXT,PRIMARY KEY(target_kind,target_id));
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PRAGMA user_version=20;
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"""
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def run(command, ok=True):
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result = subprocess.run(command, text=True, capture_output=True)
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if (result.returncode == 0) != ok:
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raise AssertionError(result.stdout + result.stderr)
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return result
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def db_value(path, sql):
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with sqlite3.connect(path) as connection:
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return connection.execute(sql).fetchone()[0]
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def payload():
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exercises = [
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{"exercise_id": "ex_reps", "name": "Reps", "recording_mode": "sets", "tracking_mode": "reps", "data_fields": 0},
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{"exercise_id": "ex_duration", "name": "Duration", "recording_mode": "sets", "tracking_mode": "duration", "data_fields": 0},
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{"exercise_id": "ex_walk", "name": "Walk", "recording_mode": "continuous", "tracking_mode": "duration", "data_fields": 0},
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]
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base = {"format": "trainlog-mobile-export", "version": 3,
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"generated_at": "2026-09-09T12:00:00+02:00", "exercises": exercises,
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"sessions": [], "body_observations": []}
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entries = [
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{"entry_id": "sxe_reps", "position": 0, "exercise_id": "ex_reps", "name": "Reps",
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"recording_mode": "sets", "tracking_mode": "reps", "data_fields": 0,
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"load_mode": "external", "rest_seconds": 120, "equipment_id": "leg_press",
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"target": {"sets": 3, "reps": 8, "weight_kg": 42.5},
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"sets": [{"reps": 8, "weight_kg": 40.0}, {"reps": 7, "weight_kg": 0.0}]},
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{"entry_id": "sxe_duration", "position": 1, "exercise_id": "ex_duration", "name": "Duration",
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"recording_mode": "sets", "tracking_mode": "duration", "data_fields": 0,
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"load_mode": "assistance", "rest_seconds": 60, "equipment_id": "leg_press",
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"target": {"sets": 2, "duration_seconds": 45, "weight_kg": 15.0},
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"sets": [{"duration_seconds": 40}]},
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{"entry_id": "sxe_unweighted", "position": 2, "exercise_id": "ex_reps", "name": "Reps",
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"recording_mode": "sets", "tracking_mode": "reps", "data_fields": 0,
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"load_mode": "none", "rest_seconds": 30, "equipment_id": None,
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"target": {"sets": 1, "reps": 12}, "sets": [{"reps": 11}]},
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{"entry_id": "sxe_walk", "position": 3, "exercise_id": "ex_walk", "name": "Walk",
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"recording_mode": "continuous", "tracking_mode": "duration", "data_fields": 0,
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"load_mode": "none", "rest_seconds": 0, "equipment_id": None,
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"target": None, "continuous": {"duration_seconds": 600}},
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]
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base["sessions"] = [{"session_id": "se_v3", "started_at": "2026-09-09T12:01:00+02:00",
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"session_type": "training", "exercises": entries}]
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base["sessions"].append({"session_id": "se_v3_max", "started_at": "2026-09-09T13:00:00+02:00",
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"session_type": "max_test", "exercises": [{
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"entry_id": "sxe_max", "position": 0, "exercise_id": "ex_reps", "name": "Reps",
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"recording_mode": "sets", "tracking_mode": "reps", "data_fields": 0,
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"load_mode": "none", "rest_seconds": 0, "equipment_id": "leg_press",
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"target": None, "max_weight_kg": 100.0}]})
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base["body_observations"] = [{"observation_id": "bo_v3", "observed_at": "2026-09-09T14:00:00+02:00",
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"body_weight_kg": 72.5}]
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return base
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def snapshot(db):
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with sqlite3.connect(db) as con:
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return tuple(con.execute(f"SELECT * FROM {table} ORDER BY rowid").fetchall()
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for table in ("exercises", "sessions", "session_exercises", "performed_sets",
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"continuous_activity", "body_observations"))
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def main():
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with tempfile.TemporaryDirectory(prefix="trainlog-v3-") as directory:
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root = Path(directory); db = root / "db.sqlite"; artifact = root / "mobile-v3.json"
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with sqlite3.connect(db) as con:
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con.executescript(V11_SCHEMA)
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artifact.write_text(json.dumps(payload()), encoding="utf-8")
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first = run([sys.executable, str(IMPORTER), str(artifact), "--database", str(db)])
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assert "sessions_imported=2" in first.stdout
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replay = run([sys.executable, str(IMPORTER), str(artifact), "--database", str(db)])
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assert "sessions_skipped=2" in replay.stdout
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with sqlite3.connect(db) as con:
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plans = con.execute("SELECT entry_id,load_mode,rest_seconds,target_sets,target_reps,target_duration_seconds,target_weight_kg,equipment_id FROM session_exercises ORDER BY id").fetchall()
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assert plans == [
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("sxe_reps", "external", 120, 3, 8, None, 42.5, "leg_press"),
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("sxe_duration", "assistance", 60, 2, None, 45, 15.0, "leg_press"),
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("sxe_unweighted", "none", 30, 1, 12, None, None, None),
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("sxe_walk", "none", 0, None, None, None, None, None),
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("sxe_max", "none", 0, None, None, None, None, "leg_press"),
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]
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# A schema with causal exchange support records the deterministic live
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# snapshot revision on first import. Exact replay preserves it instead
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# of replacing it with a peer-local random revision.
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causal_db = root / "causal.sqlite"
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with sqlite3.connect(causal_db) as con:
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con.executescript(V20_SCHEMA)
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run([sys.executable, str(IMPORTER), str(artifact), "--database", str(causal_db)])
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with sqlite3.connect(causal_db) as con:
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revisions_before = con.execute(
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"SELECT target_id,current_revision_id,deleted FROM sync_causal_state "
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"WHERE target_kind='session' ORDER BY target_id"
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).fetchall()
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assert len(revisions_before) == 2
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assert all(revision.startswith("lv_") and deleted == 0
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for _, revision, deleted in revisions_before)
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run([sys.executable, str(IMPORTER), str(artifact), "--database", str(causal_db)])
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with sqlite3.connect(causal_db) as con:
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assert con.execute(
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"SELECT target_id,current_revision_id,deleted FROM sync_causal_state "
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"WHERE target_kind='session' ORDER BY target_id"
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).fetchall() == revisions_before
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exported = root / "pc-v3.json"
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run([sys.executable, str(EXPORTER), str(exported), "--database", str(db)])
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roundtrip = json.loads(exported.read_text())
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assert roundtrip["version"] == 3
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assert roundtrip["sessions"][0]["exercises"][0]["target"] == {"sets": 3, "reps": 8, "weight_kg": 42.5}
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assert roundtrip["sessions"][0]["exercises"][2]["target"] == {"sets": 1, "reps": 12}
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assert roundtrip["sessions"][0]["exercises"][3]["target"] is None
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assert roundtrip["sessions"][1]["exercises"][0]["max_weight_kg"] == 100.0
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# CONTRACT: Android completed-session reorder is a V3 correction of
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# positions under the same session_id/entry_id identities, never a new
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# session. Facts and occurrence owners survive the reconciliation.
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reordered = copy.deepcopy(payload())
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entries = reordered["sessions"][0]["exercises"]
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entries.insert(0, entries.pop(3))
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for position, entry in enumerate(entries):
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entry["position"] = position
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reordered_path = root / "reordered.json"
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reordered_path.write_text(json.dumps(reordered), encoding="utf-8")
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reconciled = run([sys.executable, str(IMPORTER), str(reordered_path), "--database", str(db)])
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assert "sessions_reconciled=1" in reconciled.stdout
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with sqlite3.connect(db) as con:
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assert con.execute("SELECT COUNT(*) FROM sessions WHERE session_id='se_v3'").fetchone()[0] == 1
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assert con.execute(
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"SELECT entry_id FROM session_exercises WHERE session_row_id="
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"(SELECT id FROM sessions WHERE session_id='se_v3') ORDER BY position"
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).fetchall() == [("sxe_walk",), ("sxe_reps",), ("sxe_duration",), ("sxe_unweighted",)]
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assert con.execute(
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"SELECT COUNT(DISTINCT entry_id) FROM session_exercises WHERE session_row_id="
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"(SELECT id FROM sessions WHERE session_id='se_v3')"
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).fetchone()[0] == 4
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legacy = copy.deepcopy(payload()); legacy["version"] = 2
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for session in legacy["sessions"]:
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for entry in session["exercises"]:
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entry.pop("target"); entry["load_mode"] = "none"; entry["rest_seconds"] = 0
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legacy_path = root / "legacy-v2.json"; legacy_path.write_text(json.dumps(legacy), encoding="utf-8")
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before = snapshot(db)
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legacy_replay = run([sys.executable, str(IMPORTER), str(legacy_path), "--database", str(db)], ok=False)
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assert "conflit" in (legacy_replay.stdout + legacy_replay.stderr) and snapshot(db) == before, \
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legacy_replay.stdout + legacy_replay.stderr
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downgrade = run([sys.executable, str(EXPORTER), str(root / "v2.json"), "--database", str(db), "--version", "2"], ok=False)
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assert "export V2 avec plan interdit" in downgrade.stdout
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divergent = copy.deepcopy(payload()); divergent["sessions"][0]["exercises"][0]["target"]["reps"] = 9
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divergent_path = root / "divergent.json"; divergent_path.write_text(json.dumps(divergent), encoding="utf-8")
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corrected = run([sys.executable, str(IMPORTER), str(divergent_path), "--database", str(db)])
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assert "sessions_reconciled=1" in corrected.stdout
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replay = run([sys.executable, str(IMPORTER), str(divergent_path), "--database", str(db)])
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assert "sessions_reconciled=0" in replay.stdout
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assert db_value(db, "SELECT target_reps FROM session_exercises WHERE entry_id='sxe_reps'") == 9
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before = snapshot(db)
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mutations = [
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lambda e: e["target"].update(sets=0),
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lambda e: e["target"].update(reps=10001),
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lambda e: e.update(rest_seconds=86401),
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lambda e: e.update(load_mode="none"),
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lambda e: e.update(target=None),
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lambda e: e.update(position=100001),
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lambda e: e["target"].update(weight_kg=float("nan")),
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]
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for index, mutate in enumerate(mutations):
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invalid = copy.deepcopy(payload()); mutate(invalid["sessions"][0]["exercises"][0])
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path = root / f"invalid-{index}.json"; path.write_text(json.dumps(invalid), encoding="utf-8")
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run([sys.executable, str(IMPORTER), str(path), "--database", str(db)], ok=False)
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assert snapshot(db) == before
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# WHY: V3 validation is a pre-transaction boundary. A malformed instant
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# must not leave even definitions or body rows behind.
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for index, mutate in enumerate((
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lambda document: document["sessions"][0].update(started_at="not-a-time"),
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lambda document: document["body_observations"][0].update(observed_at="2026-02-30T12:00Z"),
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lambda document: document.update(generated_at="2026-09-09 12:00:00Z"),
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)):
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invalid_time = copy.deepcopy(payload()); mutate(invalid_time)
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path = root / f"invalid-time-{index}.json"; path.write_text(json.dumps(invalid_time), encoding="utf-8")
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result = run([sys.executable, str(IMPORTER), str(path), "--database", str(db)], ok=False)
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assert "date-heure Trainlog invalide" in result.stderr and snapshot(db) == before
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# The exact shared language includes omitted seconds, lowercase t/z,
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# ±23:59 offsets and arbitrary fraction precision.
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exact = copy.deepcopy(payload())
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exact["generated_at"] = "2026-09-09t12:00z"
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exact["sessions"][0]["started_at"] = "2026-09-09T12:01+23:59"
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exact["sessions"][1]["started_at"] = "2026-09-09T13:00:00.123456789012345678900-23:59"
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exact["body_observations"][0]["observed_at"] = "2026-09-09t14:00:00.1000z"
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exact_db = root / "exact.sqlite"
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with sqlite3.connect(exact_db) as con: con.executescript(V11_SCHEMA)
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exact_path = root / "exact.json"; exact_path.write_text(json.dumps(exact), encoding="utf-8")
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run([sys.executable, str(IMPORTER), str(exact_path), "--database", str(exact_db)])
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# Published V2 admission remains unchanged, including its historical
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# nonempty timestamp rule.
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legacy_time = copy.deepcopy(legacy)
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legacy_time["sessions"][0]["session_id"] = "se_legacy_bad_time"
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legacy_time["sessions"][0]["started_at"] = "not-a-time"
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legacy_time["sessions"] = legacy_time["sessions"][:1]
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legacy_time["body_observations"] = []
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legacy_db = root / "legacy-time.sqlite"
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with sqlite3.connect(legacy_db) as con: con.executescript(V11_SCHEMA)
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legacy_time_path = root / "legacy-time.json"; legacy_time_path.write_text(json.dumps(legacy_time), encoding="utf-8")
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run([sys.executable, str(IMPORTER), str(legacy_time_path), "--database", str(legacy_db)])
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# INVARIANT: corrupt stored V3 instants fail before destination write.
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sentinel = root / "sentinel.json"; sentinel.write_text("prior-valid-artifact", encoding="utf-8")
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with sqlite3.connect(db) as con:
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con.execute("UPDATE sessions SET started_at='bad-stored-time' WHERE session_id='se_v3'")
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failed_export = run([sys.executable, str(EXPORTER), str(sentinel), "--database", str(db)], ok=False)
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assert "started_at" in failed_export.stdout and sentinel.read_text() == "prior-valid-artifact"
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with sqlite3.connect(db) as con:
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con.execute("UPDATE sessions SET started_at='2026-09-09T12:01:00+02:00' WHERE session_id='se_v3'")
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con.execute("UPDATE body_observations SET observed_at='bad-stored-time' WHERE observation_id='bo_v3'")
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failed_export = run([sys.executable, str(EXPORTER), str(sentinel), "--database", str(db)], ok=False)
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assert "observed_at" in failed_export.stdout and sentinel.read_text() == "prior-valid-artifact"
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with sqlite3.connect(db) as con:
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con.execute("UPDATE body_observations SET observed_at='2026-09-09T14:00:00+02:00' WHERE observation_id='bo_v3'")
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duplicate = artifact.read_text().replace('"sets": 3', '"sets": 3, "sets": 4', 1)
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duplicate_path = root / "duplicate.json"; duplicate_path.write_text(duplicate)
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rejected = run([sys.executable, str(IMPORTER), str(duplicate_path), "--database", str(db)], ok=False)
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assert "dupliqué" in rejected.stderr and snapshot(db) == before
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# The same checked-in artifact is consumed by Robolectric, proving the
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# wire shape rather than two independently authored platform fixtures.
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shared_db = root / "shared.sqlite"
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with sqlite3.connect(shared_db) as con: con.executescript(V11_SCHEMA)
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shared = ROOT / "tests/fixtures/session-mobile-export-v3.json"
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run([sys.executable, str(IMPORTER), str(shared), "--database", str(shared_db)])
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shared_out = root / "shared-out.json"
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run([sys.executable, str(EXPORTER), str(shared_out), "--database", str(shared_db)])
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shared_entry = json.loads(shared_out.read_text())["sessions"][0]["exercises"][0]
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assert shared_entry["target"] == {"sets": 3, "reps": 9, "weight_kg": 55.5}
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assert shared_entry["sets"] == [{"reps": 9, "weight_kg": 52.5}, {"reps": 8}, {"reps": 7, "weight_kg": 0.0}]
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# Desktop v16 stores the unit on the occurrence. A later catalogue
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# profile change therefore cannot reinterpret or rewrite old facts.
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v16_db = root / "v16.sqlite"
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with sqlite3.connect(v16_db) as con:
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con.executescript(V16_SCHEMA)
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run([sys.executable, str(IMPORTER), str(artifact), "--database", str(v16_db)])
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with sqlite3.connect(v16_db) as con:
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assert con.execute("SELECT tracking_mode FROM session_exercises WHERE entry_id='sxe_reps'").fetchone()[0] == "reps"
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con.execute("UPDATE exercises SET tracking_mode='duration' WHERE exercise_id='ex_reps'")
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# V2 has the same completed-occurrence ownership contract: catalogue
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# membership proves identity, while the entry's own profile validates
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# and preserves the historical payload.
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historical_v2 = payload()
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historical_v2["version"] = 2
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historical_v2["exercises"][0]["tracking_mode"] = "duration"
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historical_entry = copy.deepcopy(historical_v2["sessions"][0]["exercises"][0])
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historical_entry.pop("target")
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historical_entry["entry_id"] = "sxe_v16_historical_v2"
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historical_entry["load_mode"] = "none"
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historical_entry["rest_seconds"] = 0
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historical_v2["sessions"] = [{
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"session_id": "se_v16_historical_v2",
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"started_at": "2026-09-09T13:00:00+02:00",
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"session_type": "training",
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"exercises": [historical_entry],
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}]
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historical_v2["body_observations"] = []
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historical_v2_path = root / "v16-historical-v2.json"
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historical_v2_path.write_text(json.dumps(historical_v2), encoding="utf-8")
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run([sys.executable, str(IMPORTER), str(historical_v2_path), "--database", str(v16_db)])
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replay_v2 = run([sys.executable, str(IMPORTER), str(historical_v2_path), "--database", str(v16_db)])
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assert "sessions_skipped=1" in replay_v2.stdout
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with sqlite3.connect(v16_db) as con:
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assert con.execute("SELECT tracking_mode FROM session_exercises WHERE entry_id='sxe_v16_historical_v2'").fetchone()[0] == "reps"
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assert con.execute("SELECT reps FROM performed_sets ps JOIN session_exercises se ON se.id=ps.session_exercise_row_id WHERE se.entry_id='sxe_v16_historical_v2' ORDER BY ps.position LIMIT 1").fetchone()[0] == 8
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v16_old_export = root / "v16-old.json"
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run([sys.executable, str(EXPORTER), str(v16_old_export), "--database", str(v16_db)])
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old_entry = json.loads(v16_old_export.read_text())["sessions"][0]["exercises"][0]
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assert old_entry["tracking_mode"] == "reps"
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assert old_entry["sets"][0]["reps"] == 8
|
|
|
|
future = payload()
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future["exercises"][0]["tracking_mode"] = "duration"
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old_after_profile_change = copy.deepcopy(payload()["sessions"][0])
|
|
future["sessions"] = [old_after_profile_change, {
|
|
"session_id": "se_v16_future", "started_at": "2026-09-10T12:00:00+02:00",
|
|
"session_type": "training", "exercises": [{
|
|
"entry_id": "sxe_v16_future", "position": 0, "exercise_id": "ex_reps",
|
|
"name": "Reps", "recording_mode": "sets", "tracking_mode": "duration",
|
|
"data_fields": 0, "load_mode": "none", "rest_seconds": 0,
|
|
"equipment_id": None, "target": {"sets": 3, "duration_seconds": 30},
|
|
"sets": [{"duration_seconds": 30}, {"duration_seconds": 30}, {"duration_seconds": 30}],
|
|
}],
|
|
}]
|
|
future["body_observations"] = []
|
|
future_path = root / "v16-future.json"
|
|
future_path.write_text(json.dumps(future), encoding="utf-8")
|
|
run([sys.executable, str(IMPORTER), str(future_path), "--database", str(v16_db)])
|
|
idempotent = run([sys.executable, str(IMPORTER), str(future_path), "--database", str(v16_db)])
|
|
assert "sessions_reconciled=0" in idempotent.stdout
|
|
with sqlite3.connect(v16_db) as con:
|
|
assert con.execute("SELECT tracking_mode FROM session_exercises WHERE entry_id='sxe_reps'").fetchone()[0] == "reps"
|
|
assert con.execute("SELECT tracking_mode FROM session_exercises WHERE entry_id='sxe_v16_future'").fetchone()[0] == "duration"
|
|
assert con.execute("SELECT group_concat(duration_seconds, ',') FROM performed_sets ps JOIN session_exercises se ON se.id=ps.session_exercise_row_id WHERE se.entry_id='sxe_v16_future' ORDER BY ps.position").fetchone()[0] == "30,30,30"
|
|
print("PASS session_exchange_v3")
|
|
|
|
|
|
if __name__ == "__main__": main()
|