feat: Training Type Profiles - Phase 1.1 Foundation (#15)
## Implemented
### DB-Schema (Migrations)
- Migration 013: training_parameters table (16 standard parameters)
- Migration 014: training_types.profile + activity_log.evaluation columns
- Performance metric calculations (avg_hr_percent, kcal_per_km)
### Backend - Rule Engine
- RuleEvaluator: Generic rule evaluation with 9 operators
- gte, lte, gt, lt, eq, neq, between, in, not_in
- Weighted scoring system
- Pass strategies: all_must_pass, weighted_score, at_least_n
- IntensityZoneEvaluator: HR zone analysis
- TrainingEffectsEvaluator: Abilities development
### Backend - Master Evaluator
- TrainingProfileEvaluator: 7-dimensional evaluation
1. Minimum Requirements (Quality Gates)
2. Intensity Zones (HR zones)
3. Training Effects (Abilities)
4. Periodization (Frequency & Recovery)
5. Performance Indicators (KPIs)
6. Safety (Warnings)
7. AI Context (simplified for MVP)
- evaluation_helper.py: Utilities for loading + saving
- routers/evaluation.py: API endpoints
- POST /api/evaluation/activity/{id}
- POST /api/evaluation/batch
- GET /api/evaluation/parameters
### Integration
- main.py: Router registration
## TODO (Phase 1.2)
- Auto-evaluation on activity INSERT/UPDATE
- Admin-UI for profile editing
- User-UI for results display
## Testing
- ✅ Syntax checks passed
- 🔲 Runtime testing pending (after auto-evaluation)
Part of Issue #15 - Training Type Profiles System
Lars
1b9cd6d5e6