workout generator audit: rules engine, structure rules, split patterns, injury UX, metadata cleanup
- Add rules_engine.py with quantitative rules for all 8 workout types - Add quality gate retry loop in generate_single_workout() - Expand calibrate_structure_rules to all 120 combinations (8 types × 5 goals × 3 sections) - Wire WeeklySplitPattern DB records into _pick_weekly_split() - Enforce movement patterns from WorkoutStructureRule in exercise selection - Add straight-set strength support (single main lift, 4-6 rounds) - Add modality consistency check for duration-dominant workout types - Add InjuryStep component to onboarding and preferences - Add sibling exercise exclusion in regenerate and preview_day endpoints - Display generator warnings on dashboard - Expand fix_rep_durations, fix_exercise_flags, fix_movement_pattern_typo - Add audit_exercise_data and check_rules_drift management commands - Add Next.js frontend with dashboard, onboarding, preferences, history pages - Add generator app with ML-powered workout generation pipeline - 96 new tests across 7 test modules Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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generator/tests/test_structure_rules.py
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generator/tests/test_structure_rules.py
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"""
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Tests for the calibrate_structure_rules management command.
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Verifies the full 120-rule matrix (8 types x 5 goals x 3 sections)
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is correctly populated, all values are sane, and the command is
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idempotent (running it twice doesn't create duplicates).
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"""
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from django.test import TestCase
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from django.core.management import call_command
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from generator.models import WorkoutStructureRule, WorkoutType
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WORKOUT_TYPE_NAMES = [
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'traditional_strength_training',
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'hypertrophy',
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'high_intensity_interval_training',
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'functional_strength_training',
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'cross_training',
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'core_training',
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'flexibility',
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'cardio',
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]
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GOAL_TYPES = [
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'strength', 'hypertrophy', 'endurance', 'weight_loss', 'general_fitness',
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]
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SECTION_TYPES = ['warm_up', 'working', 'cool_down']
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class TestStructureRules(TestCase):
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"""Verify calibrate_structure_rules produces the correct 120-rule matrix."""
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@classmethod
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def setUpTestData(cls):
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# Create all 8 workout types so the command can find them.
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cls.workout_types = []
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for name in WORKOUT_TYPE_NAMES:
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wt, _ = WorkoutType.objects.get_or_create(name=name)
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cls.workout_types.append(wt)
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# Run the calibration command.
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call_command('calibrate_structure_rules')
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# ------------------------------------------------------------------
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# Coverage tests
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# ------------------------------------------------------------------
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def test_all_120_combinations_exist(self):
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"""8 types x 5 goals x 3 sections = 120 rules."""
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count = WorkoutStructureRule.objects.count()
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self.assertEqual(count, 120, f'Expected 120 rules, got {count}')
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def test_each_type_has_15_rules(self):
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"""Each workout type should have 5 goals x 3 sections = 15 rules."""
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for wt in self.workout_types:
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count = WorkoutStructureRule.objects.filter(
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workout_type=wt,
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).count()
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self.assertEqual(
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count, 15,
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f'{wt.name} has {count} rules, expected 15',
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)
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def test_each_type_has_all_sections(self):
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"""Every type must cover warm_up, working, and cool_down."""
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for wt in self.workout_types:
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sections = set(
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WorkoutStructureRule.objects.filter(
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workout_type=wt,
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).values_list('section_type', flat=True)
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)
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self.assertEqual(
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sections,
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{'warm_up', 'working', 'cool_down'},
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f'{wt.name} missing sections: '
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f'{{"warm_up", "working", "cool_down"}} - {sections}',
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)
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def test_each_type_has_all_goals(self):
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"""Every type must have all 5 goal types."""
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for wt in self.workout_types:
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goals = set(
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WorkoutStructureRule.objects.filter(
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workout_type=wt,
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).values_list('goal_type', flat=True)
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)
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expected = set(GOAL_TYPES)
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self.assertEqual(
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goals, expected,
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f'{wt.name} goals mismatch: expected {expected}, got {goals}',
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)
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# ------------------------------------------------------------------
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# Value sanity tests
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# ------------------------------------------------------------------
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def test_working_rules_have_movement_patterns(self):
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"""All working-section rules must have at least one pattern."""
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working_rules = WorkoutStructureRule.objects.filter(
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section_type='working',
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)
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for rule in working_rules:
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self.assertTrue(
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len(rule.movement_patterns) > 0,
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f'Working rule {rule} has empty movement_patterns',
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)
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def test_warmup_and_cooldown_have_patterns(self):
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"""Warm-up and cool-down rules should also have patterns."""
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for section in ('warm_up', 'cool_down'):
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rules = WorkoutStructureRule.objects.filter(section_type=section)
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for rule in rules:
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self.assertTrue(
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len(rule.movement_patterns) > 0,
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f'{section} rule {rule} has empty movement_patterns',
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)
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def test_rep_ranges_valid(self):
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"""rep_min <= rep_max, and working rep_min >= 1."""
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for rule in WorkoutStructureRule.objects.all():
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self.assertLessEqual(
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rule.typical_rep_range_min,
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rule.typical_rep_range_max,
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f'Rule {rule}: rep_min ({rule.typical_rep_range_min}) '
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f'> rep_max ({rule.typical_rep_range_max})',
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)
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if rule.section_type == 'working':
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self.assertGreaterEqual(
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rule.typical_rep_range_min, 1,
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f'Rule {rule}: working rep_min below floor',
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)
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def test_duration_ranges_valid(self):
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"""dur_min <= dur_max for every rule."""
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for rule in WorkoutStructureRule.objects.all():
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self.assertLessEqual(
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rule.typical_duration_range_min,
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rule.typical_duration_range_max,
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f'Rule {rule}: dur_min ({rule.typical_duration_range_min}) '
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f'> dur_max ({rule.typical_duration_range_max})',
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)
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def test_warm_up_rounds_are_one(self):
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"""All warm_up sections must have exactly 1 round."""
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warmup_rules = WorkoutStructureRule.objects.filter(
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section_type='warm_up',
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)
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for rule in warmup_rules:
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self.assertEqual(
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rule.typical_rounds, 1,
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f'Warm-up rule {rule} has rounds={rule.typical_rounds}, '
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f'expected 1',
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)
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def test_cool_down_rounds_are_one(self):
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"""All cool_down sections must have exactly 1 round."""
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cooldown_rules = WorkoutStructureRule.objects.filter(
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section_type='cool_down',
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)
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for rule in cooldown_rules:
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self.assertEqual(
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rule.typical_rounds, 1,
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f'Cool-down rule {rule} has rounds={rule.typical_rounds}, '
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f'expected 1',
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)
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def test_cardio_rounds_not_absurd(self):
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"""Cardio working rounds should be 2-3, not 23-25 (ML artifact)."""
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cardio_wt = WorkoutType.objects.get(name='cardio')
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cardio_working = WorkoutStructureRule.objects.filter(
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workout_type=cardio_wt,
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section_type='working',
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)
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for rule in cardio_working:
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self.assertLessEqual(
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rule.typical_rounds, 5,
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f'Cardio working {rule.goal_type} has '
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f'rounds={rule.typical_rounds}, expected <= 5',
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)
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self.assertGreaterEqual(
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rule.typical_rounds, 2,
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f'Cardio working {rule.goal_type} has '
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f'rounds={rule.typical_rounds}, expected >= 2',
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)
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def test_cool_down_has_stretch_or_mobility(self):
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"""Cool-down patterns should focus on stretch/mobility."""
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cooldown_rules = WorkoutStructureRule.objects.filter(
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section_type='cool_down',
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)
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stretch_mobility_patterns = {
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'mobility', 'mobility - static', 'yoga',
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'lower pull - hip hinge', 'cardio/locomotion',
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}
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for rule in cooldown_rules:
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patterns = set(rule.movement_patterns)
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overlap = patterns & stretch_mobility_patterns
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self.assertTrue(
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len(overlap) > 0,
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f'Cool-down rule {rule} has no stretch/mobility patterns: '
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f'{rule.movement_patterns}',
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)
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def test_no_rep_min_below_global_floor(self):
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"""After calibration, no rule should have rep_min < 6 (the floor)."""
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below_floor = WorkoutStructureRule.objects.filter(
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typical_rep_range_min__lt=6,
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typical_rep_range_min__gt=0,
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)
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self.assertEqual(
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below_floor.count(), 0,
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f'{below_floor.count()} rules have rep_min below 6',
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)
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# ------------------------------------------------------------------
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# Idempotency test
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# ------------------------------------------------------------------
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def test_calibrate_is_idempotent(self):
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"""Running the command again must not create duplicates."""
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# Run calibration a second time.
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call_command('calibrate_structure_rules')
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count = WorkoutStructureRule.objects.count()
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self.assertEqual(
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count, 120,
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f'After re-run, expected 120 rules, got {count}',
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)
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def test_calibrate_updates_existing_values(self):
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"""If a rule value is changed in DB, re-running restores it."""
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# Pick a rule and mutate it.
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rule = WorkoutStructureRule.objects.filter(
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section_type='working',
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goal_type='strength',
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).first()
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original_rounds = rule.typical_rounds
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rule.typical_rounds = 99
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rule.save()
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# Re-run calibration.
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call_command('calibrate_structure_rules')
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rule.refresh_from_db()
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self.assertEqual(
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rule.typical_rounds, original_rounds,
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f'Expected rounds to be restored to {original_rounds}, '
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f'got {rule.typical_rounds}',
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)
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