mitai-jinkendo/backend
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feat: filtered goal types - count specific training types
NEW FEATURE: Filter conditions for goal types
Enables counting/aggregating specific subsets of data.

Example use case: Count only strength training sessions per week
- Create goal type with filter: {"training_type": "strength"}
- count_7d now counts only strength training, not all activities

Implementation:
- Migration 026: filter_conditions JSONB column
- Backend: Dynamic WHERE clause building from JSON filters
- Supports single value: {"training_type": "strength"}
- Supports multiple values: {"training_type": ["strength", "hiit"]}
- Works with all 8 aggregation methods (count, avg, sum, min, max)
- Frontend: JSON textarea with example + validation
- Pydantic models: filter_conditions field added

Technical details:
- SQL injection safe (parameterized queries)
- Graceful degradation (invalid JSON ignored with warning)
- Backward compatible (NULL filters = no filtering)

Answers user question: 'Kann ich Trainingstypen wie Krafttraining separat zählen?'
Answer: YES! 🎯
2026-03-27 08:14:22 +01:00
..
migrations feat: filtered goal types - count specific training types 2026-03-27 08:14:22 +01:00
routers feat: filtered goal types - count specific training types 2026-03-27 08:14:22 +01:00
apply_v9c_migration.py feat: v9c Phase 1 - Feature consolidation & cleanup migration 2026-03-20 18:57:39 +01:00
auth.py fix: correct indentation in auth.py _check_impl function 2026-03-21 07:06:53 +01:00
check_features.py fix: pipeline typo and add features diagnostic script 2026-03-20 22:32:09 +01:00
check_migration_024.py debug: diagnostic script for Migration 024 state 2026-03-27 07:39:18 +01:00
db_init.py fix: only process numbered migrations (XXX_*.sql pattern) 2026-03-21 10:08:56 +01:00
db.py refactor: move init_db() to db.py 2026-03-19 09:49:46 +01:00
Dockerfile fix: replace psql with Python for DB checks (no apt-get needed!) 2026-03-18 10:01:19 +01:00
evaluation_helper.py fix: convert Decimal to float for JSON serialization in evaluation 2026-03-23 13:28:07 +01:00
feature_logger.py feat: add structured JSON logging for all feature usage (Phase 2) 2026-03-20 22:18:12 +01:00
fix_seed_goal_types.py fix: make Migration 024 idempotent + add seed data fix script 2026-03-27 07:40:42 +01:00
goal_utils.py feat: filtered goal types - count specific training types 2026-03-27 08:14:22 +01:00
main_old.py refactor: modular backend architecture with 14 router modules 2026-03-19 11:15:35 +01:00
main.py feat: Phase 0a - Minimal Goal System (Strategic + Tactical) 2026-03-26 16:20:35 +01:00
migrate_to_postgres.py fix: Migration-Fehler - meas_id Spalte in ai_insights 2026-03-19 08:39:36 +01:00
models.py feat: unified prompt system migration schema (Issue #28 Phase 1) 2026-03-25 10:43:10 +01:00
placeholder_resolver.py feat: circ_summary with best-of-each strategy and age annotations 2026-03-26 13:09:38 +01:00
profile_evaluator.py feat: Training Type Profiles - Phase 1.1 Foundation (#15) 2026-03-23 10:49:26 +01:00
profile_templates.py feat: Training Type Profiles Phase 2.1 - Backend Profile Management (#15) 2026-03-23 11:50:40 +01:00
prompt_executor.py fix: include stage outputs in debug info for value table 2026-03-26 14:33:00 +01:00
quality_filter.py feat: global quality filter setting (Issue #31) 2026-03-23 22:29:49 +01:00
requirements.txt fix: add python-dateutil dependency for vitals CSV import 2026-03-23 15:41:30 +01:00
rule_engine.py feat: Training Type Profiles - Phase 1.1 Foundation (#15) 2026-03-23 10:49:26 +01:00
run_migration_024.py feat: manual migration 024 runner script 2026-03-27 07:28:43 +01:00
schema.sql fix: add missing meas_id column to photos table 2026-03-18 12:23:13 +01:00
startup.sh fix: replace psql with Python for DB checks (no apt-get needed!) 2026-03-18 10:01:19 +01:00