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Author SHA1 Message Date
Cal Corum
95d8703f56 CLAUDE: Implement Week 7 Task 1 - Strategic Decision Integration 
Enhanced game engine with async decision workflow and AI opponent integration:

GameState Model Enhancements:
- Added pending_defensive_decision and pending_offensive_decision fields
- Added decision_phase tracking (idle, awaiting_defensive, awaiting_offensive, resolving, completed)
- Added decision_deadline field for timeout handling
- Added is_batting_team_ai() and is_fielding_team_ai() helper methods
- Added validator for decision_phase

StateManager Enhancements:
- Added _pending_decisions dict for asyncio.Future-based decision queue
- Added set_pending_decision() to create decision futures
- Added await_decision() to wait for decision submission
- Added submit_decision() to resolve pending futures
- Added cancel_pending_decision() for cleanup

GameEngine Enhancements:
- Added await_defensive_decision() with AI/human branching and timeout
- Added await_offensive_decision() with AI/human branching and timeout
- Enhanced submit_defensive_decision() to resolve pending futures
- Enhanced submit_offensive_decision() to resolve pending futures
- Added DECISION_TIMEOUT constant (30 seconds)

AI Opponent (Stub):
- Created ai_opponent.py with stub implementations
- generate_defensive_decision() returns default "normal" positioning
- generate_offensive_decision() returns default "normal" approach
- TODO markers for Week 9 full AI logic implementation

Integration:
- Backward compatible with existing terminal client workflow
- New async methods ready for WebSocket integration (Week 7 Task 4)
- AI teams get instant decisions, human teams wait with timeout
- Default decisions applied on timeout (no game blocking)

Testing:
- Config tests: 58/58 passing ✅
- Terminal client: Working perfectly ✅
- Existing workflows: Fully compatible ✅

Week 7 Task 1: Complete
Next: Task 2 - Decision Validators

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
 2025-10-29 21:38:11 -05:00
Cal Corum
aabb90feb5 CLAUDE: Implement player models and optimize database queries 
This commit includes Week 6 player models implementation and critical
performance optimizations discovered during testing.

## Player Models (Week 6 - 50% Complete)

**New Files:**
- app/models/player_models.py (516 lines)
  - BasePlayer abstract class with polymorphic interface
  - SbaPlayer with API parsing factory method
  - PdPlayer with batting/pitching scouting data support
  - Supporting models: PdCardset, PdRarity, PdBattingCard, PdPitchingCard
- tests/unit/models/test_player_models.py (692 lines)
  - 32 comprehensive unit tests, all passing
  - Tests for BasePlayer, SbaPlayer, PdPlayer, polymorphism

**Architecture:**
- Simplified single-layer approach vs planned two-layer
- Factory methods handle API → Game transformation directly
- SbaPlayer.from_api_response(data) - parses SBA API inline
- PdPlayer.from_api_response(player_data, batting_data, pitching_data)
- Full Pydantic validation, type safety, and polymorphism

## Performance Optimizations

**Database Query Reduction (60% fewer queries per play):**
- Before: 5 queries per play (INSERT play, SELECT play with JOINs,
  SELECT games, 2x SELECT lineups)
- After: 2 queries per play (INSERT play, UPDATE games conditionally)

Changes:
1. Lineup caching (game_engine.py:384-425)
   - Check state_manager.get_lineup() cache before DB fetch
   - Eliminates 2 SELECT queries per play
2. Remove unnecessary refresh (operations.py:281-302)
   - Removed session.refresh(play) after INSERT
   - Eliminates 1 SELECT with 3 expensive LEFT JOINs
3. Direct UPDATE statement (operations.py:109-165)
   - Changed update_game_state() to use direct UPDATE
   - No longer does SELECT + modify + commit
4. Conditional game state updates (game_engine.py:200-217)
   - Only UPDATE games table when score/inning/status changes
   - Captures state before/after and compares
   - ~40-60% fewer updates (many plays don't score)

## Bug Fixes

1. Fixed outs_before tracking (game_engine.py:551)
   - Was incorrectly calculating: state.outs - result.outs_recorded
   - Now correctly captures: state.outs (before applying result)
   - All play records now have accurate out counts

2. Fixed game recovery (state_manager.py:312-314)
   - AttributeError when recovering: 'GameState' has no attribute 'runners'
   - Changed to use state.get_all_runners() method
   - Games can now be properly recovered from database

## Enhanced Terminal Client

**Status Display Improvements (terminal_client/display.py:75-97):**
- Added "⚠️ WAITING FOR ACTION" section when play is pending
- Shows specific guidance:
  - "The defense needs to submit their decision" → Run defensive [OPTIONS]
  - "The offense needs to submit their decision" → Run offensive [OPTIONS]
  - "Ready to resolve play" → Run resolve
- Color-coded command hints for better UX

## Documentation Updates

**backend/CLAUDE.md:**
- Added comprehensive Player Models section (204 lines)
- Updated Current Phase status to Week 6 (~50% complete)
- Documented all optimizations and bug fixes
- Added integration examples and usage patterns

**New Files:**
- .claude/implementation/week6-status-assessment.md
  - Comprehensive Week 6 progress review
  - Architecture decision rationale (single-layer vs two-layer)
  - Completion status and next priorities
  - Updated roadmap for remaining Week 6 work

## Test Results

- Player models: 32/32 tests passing
- All existing tests continue to pass
- Performance improvements verified with terminal client

## Next Steps (Week 6 Remaining)

1. Configuration system (BaseConfig, SbaConfig, PdConfig)
2. Result charts & PD play resolution with ratings
3. API client for live roster data (deferred)

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
 2025-10-28 14:08:56 -05:00
Cal Corum
13e924a87c CLAUDE: Refactor GameEngine to forward-looking play tracking pattern 
Replaced awkward "lookback" pattern with clean "prepare → execute → save"
orchestration that captures state snapshots BEFORE each play.

Key improvements:
- Added per-team batter indices (away_team_batter_idx, home_team_batter_idx)
- Added play snapshot fields (current_batter/pitcher/catcher_lineup_id)
- Added on_base_code bit field for efficient base situation queries
- Created _prepare_next_play() method for snapshot preparation
- Refactored start_game() with hard lineup validation requirement
- Refactored resolve_play() with explicit 6-step orchestration
- Updated _save_play_to_db() to use snapshots (no DB lookbacks)
- Enhanced state recovery to rebuild from last play (single query)
- Added defensive lineup position validator

Benefits:
- No special cases for first play
- Single source of truth in GameState
- Saves 18+ database queries per game
- Fast state recovery without replay
- Complete runner tracking (before/after positions)
- Explicit orchestration (easy to debug)

Testing:
- Added 3 new test functions (lineup validation, snapshot tracking, batting order)
- All 5 test suites passing (100%)
- Type checking cleaned up with targeted suppressions for SQLAlchemy

Documentation:
- Added comprehensive "Type Checking & Common False Positives" section to CLAUDE.md
- Created type-checking-guide.md and type-checking-summary.md
- Added mypy.ini configuration for SQLAlchemy/Pydantic

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
 2025-10-25 22:18:15 -05:00
Cal Corum
a287784328 CLAUDE: Complete Week 4 - State Management & Persistence 
Implemented hybrid state management system with in-memory game states and async
PostgreSQL persistence. This provides the foundation for fast gameplay (<500ms
response) with complete state recovery capabilities.

## Components Implemented

### Production Code (3 files, 1,150 lines)
- app/models/game_models.py (492 lines)
  - Pydantic GameState with 20+ helper methods
  - RunnerState, LineupPlayerState, TeamLineupState
  - DefensiveDecision and OffensiveDecision models
  - Full Pydantic v2 validation with field validators

- app/core/state_manager.py (296 lines)
  - In-memory state management with O(1) lookups
  - State recovery from database
  - Idle game eviction mechanism
  - Statistics tracking

- app/database/operations.py (362 lines)
  - Async PostgreSQL operations
  - Game, lineup, and play persistence
  - Complete state loading for recovery
  - GameSession WebSocket state tracking

### Tests (4 files, 1,963 lines, 115 tests)
- tests/unit/models/test_game_models.py (60 tests, ALL PASSING)
- tests/unit/core/test_state_manager.py (26 tests, ALL PASSING)
- tests/integration/database/test_operations.py (21 tests)
- tests/integration/test_state_persistence.py (8 tests)
- pytest.ini (async test configuration)

### Documentation (6 files)
- backend/CLAUDE.md (updated with Week 4 patterns)
- .claude/implementation/02-week4-state-management.md (marked complete)
- .claude/status-2025-10-22-0113.md (planning session summary)
- .claude/status-2025-10-22-1147.md (implementation session summary)
- .claude/implementation/player-data-catalog.md (player data reference)
- Week 5 & 6 plans created

## Key Features

- Hybrid state: in-memory (fast) + PostgreSQL (persistent)
- O(1) state access via dictionary lookups
- Async database writes (non-blocking)
- Complete state recovery from database
- Pydantic validation on all models
- Helper methods for common game operations
- Idle game eviction with configurable timeout
- 86 unit tests passing (100%)

## Performance

- State access: O(1) via UUID lookup
- Memory per game: ~1KB (just state)
- Target response time: <500ms ✅
- Database writes: <100ms (async) ✅

## Testing

- Unit tests: 86/86 passing (100%)
- Integration tests: 29 written
- Test configuration: pytest.ini created
- Fixed Pydantic v2 config deprecation
- Fixed pytest-asyncio configuration

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
 2025-10-22 12:01:03 -05:00