Lars/mitai-jinkendo
1
0
Fork 0
Code Issues 23 Pull Requests Actions Packages Projects Releases 2 Wiki Activity

fix: Phase 0c - update all in-function imports to use data_layer
All checks were successful
Deploy Development / deploy (push) Successful in 44s
Details
Build Test / lint-backend (push) Successful in 0s
Details
Build Test / build-frontend (push) Successful in 14s
Details

Browse Source 
Critical bug fix: In-function imports were still referencing calculations/ module.
This caused all calculated placeholders to fail silently.

Fixed imports in:
- activity_metrics.py: calculate_activity_score (scores import)
- recovery_metrics.py: calculate_recent_load_balance_3d (activity_metrics import)
- scores.py: 12 function imports (body/nutrition/activity/recovery metrics)
- correlations.py: 11 function imports (scores, body, nutrition, activity, recovery metrics)

All data_layer modules now reference each other correctly.
Placeholders should resolve properly now.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
This commit is contained in:
Lars 2026-03-28 20:36:50 +01:00
parent befa060671
commit 5b7d7ec3bb
4 changed files with 34 additions and 34 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

2
backend/data_layer/activity_metrics.py
View File

@ -597,7 +597,7 @@ def calculate_activity_score(profile_id: str, focus_weights: Optional[Dict] = No
Weighted by user's activity-related focus areas
"""
if focus_weights is None:
from calculations.scores import get_user_focus_weights
from data_layer.scores import get_user_focus_weights
focus_weights = get_user_focus_weights(profile_id)
# Activity-related focus areas (English keys from DB)

40
backend/data_layer/correlations.py
View File

@ -164,7 +164,7 @@ def calculate_plateau_detected(profile_id: str) -> Optional[Dict]:
'top_factors': [list of potential causes]
}
"""
from calculations.scores import get_user_focus_weights
from data_layer.scores import get_user_focus_weights
focus_weights = get_user_focus_weights(profile_id)
@ -187,8 +187,8 @@ def calculate_plateau_detected(profile_id: str) -> Optional[Dict]:
def _detect_weight_plateau(profile_id: str) -> Dict:
"""Detect weight loss plateau"""
from calculations.body_metrics import calculate_weight_28d_slope
from calculations.nutrition_metrics import calculate_nutrition_score
from data_layer.body_metrics import calculate_weight_28d_slope
from data_layer.nutrition_metrics import calculate_nutrition_score
slope = calculate_weight_28d_slope(profile_id)
nutrition_score = calculate_nutrition_score(profile_id)
@ -207,13 +207,13 @@ def _detect_weight_plateau(profile_id: str) -> Dict:
factors.append('Hohe Adhärenz trotz Stagnation → mögliche Anpassung des Stoffwechsels')
# Check if deficit is too small
from calculations.nutrition_metrics import calculate_energy_balance_7d
from data_layer.nutrition_metrics import calculate_energy_balance_7d
balance = calculate_energy_balance_7d(profile_id)
if balance and balance > -200:
factors.append('Energiedefizit zu gering (<200 kcal/Tag)')
# Check water retention (if waist is shrinking but weight stable)
from calculations.body_metrics import calculate_waist_28d_delta
from data_layer.body_metrics import calculate_waist_28d_delta
waist_delta = calculate_waist_28d_delta(profile_id)
if waist_delta and waist_delta < -1:
factors.append('Taillenumfang sinkt → mögliche Wasserretention maskiert Fettabbau')
@ -231,9 +231,9 @@ def _detect_weight_plateau(profile_id: str) -> Dict:
def _detect_strength_plateau(profile_id: str) -> Dict:
"""Detect strength training plateau"""
from calculations.body_metrics import calculate_lbm_28d_change
from calculations.activity_metrics import calculate_activity_score
from calculations.recovery_metrics import calculate_recovery_score_v2
from data_layer.body_metrics import calculate_lbm_28d_change
from data_layer.activity_metrics import calculate_activity_score
from data_layer.recovery_metrics import calculate_recovery_score_v2
lbm_change = calculate_lbm_28d_change(profile_id)
activity_score = calculate_activity_score(profile_id)
@ -251,12 +251,12 @@ def _detect_strength_plateau(profile_id: str) -> Dict:
if recovery_score and recovery_score < 60:
factors.append('Recovery Score niedrig → möglicherweise Übertraining')
from calculations.nutrition_metrics import calculate_protein_adequacy_28d
from data_layer.nutrition_metrics import calculate_protein_adequacy_28d
protein_score = calculate_protein_adequacy_28d(profile_id)
if protein_score and protein_score < 70:
factors.append('Proteinzufuhr unter Zielbereich')
from calculations.activity_metrics import calculate_monotony_score
from data_layer.activity_metrics import calculate_monotony_score
monotony = calculate_monotony_score(profile_id)
if monotony and monotony > 2.0:
factors.append('Hohe Trainingsmonotonie → Stimulus-Anpassung')
@ -274,8 +274,8 @@ def _detect_strength_plateau(profile_id: str) -> Dict:
def _detect_endurance_plateau(profile_id: str) -> Dict:
"""Detect endurance plateau"""
from calculations.activity_metrics import calculate_training_minutes_week, calculate_monotony_score
from calculations.recovery_metrics import calculate_vo2max_trend_28d
from data_layer.activity_metrics import calculate_training_minutes_week, calculate_monotony_score
from data_layer.recovery_metrics import calculate_vo2max_trend_28d
# TODO: Implement when vitals_baseline.vo2_max is populated
return {'plateau_detected': False, 'reason': 'VO2max tracking not yet implemented'}
@ -303,7 +303,7 @@ def calculate_top_drivers(profile_id: str) -> Optional[List[Dict]]:
drivers = []
# 1. Energy balance
from calculations.nutrition_metrics import calculate_energy_balance_7d
from data_layer.nutrition_metrics import calculate_energy_balance_7d
balance = calculate_energy_balance_7d(profile_id)
if balance is not None:
if -500 <= balance <= -200:
@ -327,7 +327,7 @@ def calculate_top_drivers(profile_id: str) -> Optional[List[Dict]]:
})
# 2. Protein adequacy
from calculations.nutrition_metrics import calculate_protein_adequacy_28d
from data_layer.nutrition_metrics import calculate_protein_adequacy_28d
protein_score = calculate_protein_adequacy_28d(profile_id)
if protein_score is not None:
if protein_score >= 80:
@ -348,7 +348,7 @@ def calculate_top_drivers(profile_id: str) -> Optional[List[Dict]]:
})
# 3. Sleep duration
from calculations.recovery_metrics import calculate_sleep_avg_duration_7d
from data_layer.recovery_metrics import calculate_sleep_avg_duration_7d
sleep_hours = calculate_sleep_avg_duration_7d(profile_id)
if sleep_hours is not None:
if sleep_hours >= 7:
@ -369,7 +369,7 @@ def calculate_top_drivers(profile_id: str) -> Optional[List[Dict]]:
})
# 4. Sleep regularity
from calculations.recovery_metrics import calculate_sleep_regularity_proxy
from data_layer.recovery_metrics import calculate_sleep_regularity_proxy
regularity = calculate_sleep_regularity_proxy(profile_id)
if regularity is not None:
if regularity <= 45:
@ -390,7 +390,7 @@ def calculate_top_drivers(profile_id: str) -> Optional[List[Dict]]:
})
# 5. Training consistency
from calculations.activity_metrics import calculate_training_frequency_7d
from data_layer.activity_metrics import calculate_training_frequency_7d
frequency = calculate_training_frequency_7d(profile_id)
if frequency is not None:
if 3 <= frequency <= 6:
@ -411,7 +411,7 @@ def calculate_top_drivers(profile_id: str) -> Optional[List[Dict]]:
})
# 6. Quality sessions
from calculations.activity_metrics import calculate_quality_sessions_pct
from data_layer.activity_metrics import calculate_quality_sessions_pct
quality_pct = calculate_quality_sessions_pct(profile_id)
if quality_pct is not None:
if quality_pct >= 75:
@ -432,7 +432,7 @@ def calculate_top_drivers(profile_id: str) -> Optional[List[Dict]]:
})
# 7. Recovery score
from calculations.recovery_metrics import calculate_recovery_score_v2
from data_layer.recovery_metrics import calculate_recovery_score_v2
recovery = calculate_recovery_score_v2(profile_id)
if recovery is not None:
if recovery >= 70:
@ -453,7 +453,7 @@ def calculate_top_drivers(profile_id: str) -> Optional[List[Dict]]:
})
# 8. Rest day compliance
from calculations.activity_metrics import calculate_rest_day_compliance
from data_layer.activity_metrics import calculate_rest_day_compliance
compliance = calculate_rest_day_compliance(profile_id)
if compliance is not None:
if compliance >= 80:

2
backend/data_layer/recovery_metrics.py
View File

@ -742,7 +742,7 @@ def calculate_sleep_regularity_proxy(profile_id: str) -> Optional[float]:
def calculate_recent_load_balance_3d(profile_id: str) -> Optional[int]:
"""Calculate proxy internal load last 3 days"""
from calculations.activity_metrics import calculate_proxy_internal_load_7d
from data_layer.activity_metrics import calculate_proxy_internal_load_7d
with get_db() as conn:
cur = get_cursor(conn)

24
backend/data_layer/scores.py
View File

@ -183,10 +183,10 @@ def calculate_goal_progress_score(profile_id: str) -> Optional[int]:
return None # No goals/focus areas configured
# Calculate sub-scores
from calculations.body_metrics import calculate_body_progress_score
from calculations.nutrition_metrics import calculate_nutrition_score
from calculations.activity_metrics import calculate_activity_score
from calculations.recovery_metrics import calculate_recovery_score_v2
from data_layer.body_metrics import calculate_body_progress_score
from data_layer.nutrition_metrics import calculate_nutrition_score
from data_layer.activity_metrics import calculate_activity_score
from data_layer.recovery_metrics import calculate_recovery_score_v2
body_score = calculate_body_progress_score(profile_id, focus_weights)
nutrition_score = calculate_nutrition_score(profile_id, focus_weights)
@ -404,10 +404,10 @@ def calculate_data_quality_score(profile_id: str) -> int:
Overall data quality score (0-100)
Combines quality from all modules
"""
from calculations.body_metrics import calculate_body_data_quality
from calculations.nutrition_metrics import calculate_nutrition_data_quality
from calculations.activity_metrics import calculate_activity_data_quality
from calculations.recovery_metrics import calculate_recovery_data_quality
from data_layer.body_metrics import calculate_body_data_quality
from data_layer.nutrition_metrics import calculate_nutrition_data_quality
from data_layer.activity_metrics import calculate_activity_data_quality
from data_layer.recovery_metrics import calculate_recovery_data_quality
body_quality = calculate_body_data_quality(profile_id)
nutrition_quality = calculate_nutrition_data_quality(profile_id)
@ -566,16 +566,16 @@ def calculate_category_progress(profile_id: str, category: str) -> Optional[int]
# Call the appropriate score function
if score_func_name == 'body_progress_score':
from calculations.body_metrics import calculate_body_progress_score
from data_layer.body_metrics import calculate_body_progress_score
return calculate_body_progress_score(profile_id)
elif score_func_name == 'nutrition_score':
from calculations.nutrition_metrics import calculate_nutrition_score
from data_layer.nutrition_metrics import calculate_nutrition_score
return calculate_nutrition_score(profile_id)
elif score_func_name == 'activity_score':
from calculations.activity_metrics import calculate_activity_score
from data_layer.activity_metrics import calculate_activity_score
return calculate_activity_score(profile_id)
elif score_func_name == 'recovery_score':
from calculations.recovery_metrics import calculate_recovery_score_v2
from data_layer.recovery_metrics import calculate_recovery_score_v2
return calculate_recovery_score_v2(profile_id)
elif score_func_name == 'data_quality_score':
return calculate_data_quality_score(profile_id)