c80c66c2e5
Deep audit identified 106 findings; 102 fixed, 4 deferred. Covers 8 areas: - Settings & deploy: env-gated DEBUG/SECRET_KEY, HTTPS headers, gunicorn, celery worker - Auth (registered_user): password write_only, request.data fixes, transaction safety, proper HTTP status codes - Workout app: IDOR protection, get_object_or_404, prefetch_related N+1 fixes, transaction.atomic - Video/scripts: path traversal sanitization, HLS trigger guard, auth on cache wipe - Models (exercise/equipment/muscle/superset): null-safe __str__, stable IDs, prefetch support - Generator views: helper for registered_user lookup, logger.exception, bulk_update, transaction wrapping - Generator core (rules/selector/generator): push-pull ratio, type affinity normalization, modality checks, side-pair exact match, word-boundary regex, equipment cache clearing - Generator services (plan_builder/analyzer/normalizer): transaction.atomic, muscle cache, bulk_update, glutes classification fix Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
137 lines
4.5 KiB
Python
137 lines
4.5 KiB
Python
from django.test import SimpleTestCase
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from generator.services.workout_generation.entry_rules import (
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apply_rep_volume_floor,
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pick_reps_for_exercise,
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working_rest_seconds,
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)
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from generator.services.workout_generation.focus import (
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focus_key_for_exercise,
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has_duplicate_focus,
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)
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from generator.services.workout_generation.modality import (
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clamp_duration_bias,
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plan_superset_modalities,
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)
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from generator.services.workout_generation.pattern_planning import (
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merge_pattern_preferences,
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rotated_muscle_subset,
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working_position_label,
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)
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from generator.services.workout_generation.recovery import is_recovery_exercise
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from generator.services.workout_generation.scaling import apply_fitness_scaling
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from generator.services.workout_generation.section_builders import (
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build_duration_entries,
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build_section_superset,
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section_exercise_count,
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)
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class _Rng:
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def __init__(self, randint_values=None):
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self._randint_values = list(randint_values or [])
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def randint(self, low, high):
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if self._randint_values:
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return self._randint_values.pop(0)
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return low
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def shuffle(self, arr):
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# Deterministic for tests.
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return None
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class _Ex:
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def __init__(self, **kwargs):
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self.__dict__.update(kwargs)
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class TestWorkoutGenerationModules(SimpleTestCase):
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def test_section_count_and_duration_entries(self):
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rng = _Rng([6, 27, 31])
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self.assertEqual(section_exercise_count('warmup', 1, rng=rng), 6)
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exercises = [_Ex(name='A'), _Ex(name='B')]
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entries = build_duration_entries(
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exercises,
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duration_min=20,
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duration_max=40,
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min_duration=20,
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duration_multiple=5,
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rng=rng,
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)
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self.assertEqual(entries[0]['duration'], 25)
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self.assertEqual(entries[1]['duration'], 30)
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section = build_section_superset('Warm Up', entries)
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self.assertEqual(section['name'], 'Warm Up')
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self.assertEqual(section['rounds'], 1)
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def test_scaling_and_rest_floor(self):
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params = {
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'rep_min': 4,
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'rep_max': 10,
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'rounds': (3, 4),
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'rest_between_rounds': 60,
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}
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scaling = {
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1: {'rep_min_mult': 1.1, 'rep_max_mult': 1.2, 'rounds_adj': -1, 'rest_adj': 15},
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2: {'rep_min_mult': 1.0, 'rep_max_mult': 1.0, 'rounds_adj': 0, 'rest_adj': 0},
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}
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out = apply_fitness_scaling(
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params,
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fitness_level=1,
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scaling_config=scaling,
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min_reps=6,
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min_reps_strength=1,
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is_strength=True,
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)
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self.assertGreaterEqual(out['rep_min'], 5)
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self.assertEqual(working_rest_seconds(-5, 0), 15)
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def test_modality_helpers(self):
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self.assertEqual(clamp_duration_bias(0.9, (0.2, 0.6)), 0.6)
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modalities = plan_superset_modalities(
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num_supersets=4,
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duration_bias=0.5,
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duration_bias_range=(0.25, 0.5),
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is_strength_workout=False,
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rng=_Rng(),
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)
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self.assertEqual(len(modalities), 4)
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self.assertTrue(any(modalities))
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def test_pattern_and_focus_helpers(self):
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self.assertEqual(working_position_label(0, 3), 'early')
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self.assertEqual(working_position_label(1, 3), 'middle')
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self.assertEqual(working_position_label(2, 3), 'late')
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self.assertEqual(
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merge_pattern_preferences(['upper pull', 'core'], ['core', 'lunge']),
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['core'],
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)
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self.assertEqual(
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rotated_muscle_subset(['a', 'b', 'c'], 1),
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['b', 'c', 'a'],
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)
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curl_a = _Ex(name='Alternating Bicep Curls', movement_patterns='upper pull')
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curl_b = _Ex(name='Bicep Curls', movement_patterns='upper pull')
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self.assertEqual(focus_key_for_exercise(curl_a), 'bicep_curl')
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self.assertTrue(has_duplicate_focus([curl_a, curl_b]))
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def test_recovery_and_rep_selection(self):
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stretch = _Ex(name='Supine Pec Stretch - T', movement_patterns='mobility - static')
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self.assertTrue(is_recovery_exercise(stretch))
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ex = _Ex(exercise_tier='primary')
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reps = pick_reps_for_exercise(
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ex,
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{'rep_min': 8, 'rep_max': 12},
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{'primary': (3, 6)},
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rng=_Rng([5]),
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)
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self.assertEqual(reps, 5)
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entries = [{'reps': 3}, {'duration': 30}]
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apply_rep_volume_floor(entries, rounds=3, min_volume=12)
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self.assertEqual(entries[0]['reps'], 4)
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