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Author SHA1 Message Date
Cal Corum
76e24ab22b CLAUDE: Refactor ManualOutcomeSubmission to use PlayOutcome enum + comprehensive documentation 
## Refactoring
- Changed `ManualOutcomeSubmission.outcome` from `str` to `PlayOutcome` enum type
- Removed custom validator (Pydantic handles enum validation automatically)
- Added direct import of PlayOutcome (no circular dependency due to TYPE_CHECKING guard)
- Updated tests to use enum values while maintaining backward compatibility

Benefits:
- Better type safety with IDE autocomplete
- Cleaner code (removed 15 lines of validator boilerplate)
- Backward compatible (Pydantic auto-converts strings to enum)
- Access to helper methods (is_hit(), is_out(), etc.)

Files modified:
- app/models/game_models.py: Enum type + import
- tests/unit/config/test_result_charts.py: Updated 7 tests + added compatibility test

## Documentation
Created comprehensive CLAUDE.md files for all backend/app/ subdirectories to help future AI agents quickly understand and work with the code.

Added 8,799 lines of documentation covering:
- api/ (906 lines): FastAPI routes, health checks, auth patterns
- config/ (906 lines): League configs, PlayOutcome enum, result charts
- core/ (1,288 lines): GameEngine, StateManager, PlayResolver, dice system
- data/ (937 lines): API clients (planned), caching layer
- database/ (945 lines): Async sessions, operations, recovery
- models/ (1,270 lines): Pydantic/SQLAlchemy models, polymorphic patterns
- utils/ (959 lines): Logging, JWT auth, security
- websocket/ (1,588 lines): Socket.io handlers, real-time events
- tests/ (475 lines): Testing patterns and structure

Each CLAUDE.md includes:
- Purpose & architecture overview
- Key components with detailed explanations
- Patterns & conventions
- Integration points
- Common tasks (step-by-step guides)
- Troubleshooting with solutions
- Working code examples
- Testing guidance

Total changes: +9,294 lines / -24 lines
Tests: All passing (62/62 model tests, 7/7 ManualOutcomeSubmission tests)
 2025-10-31 16:03:54 -05:00
Cal Corum
9b03fb555b CLAUDE: Implement play rollback functionality for error recovery 
Add ability to roll back the last N plays, useful for correcting mistakes
or recovering from corrupted plays. Deletes plays from database and
reconstructs game state by replaying remaining plays.

Database Operations (app/database/operations.py):
- delete_plays_after(): Delete plays with play_number > target
- delete_substitutions_after(): Delete lineup entries with after_play >= target
- delete_rolls_after(): Delete dice rolls (kept for reference, not used)

Game Engine (app/core/game_engine.py):
- rollback_plays(): Main rollback orchestration
  - Validates: num_plays > 0, enough plays exist, game not completed
  - Deletes plays and substitutions from database
  - Clears in-memory roll tracking
  - Calls state_manager.recover_game() to rebuild state
  - Returns updated GameState

Terminal Client (terminal_client/commands.py, terminal_client/repl.py):
- rollback_plays(): Command wrapper with user-friendly output
- do_rollback(): REPL command with argument parsing

Usage:
  ⚾ > rollback 3

Validations:
- Cannot roll back more plays than exist
- Cannot roll back completed games
- Rolling back across innings is allowed
- Substitutions after rolled-back plays are undone

Testing:
- ✅ Successfully rolls back 2 plays from 5-play game
- ✅ Correctly validates rollback of 10 plays when only 2 exist
- ✅ Game state properly reconstructed via replay

Note: Dice rolls kept in database for auditing (don't affect state).

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

Co-Authored-By: Claude <noreply@anthropic.com>
 2025-10-30 16:02:51 -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
874e24dc75 CLAUDE: Implement comprehensive dice roll system with persistence 
Core Implementation:
- Created roll_types.py with AbRoll, JumpRoll, FieldingRoll, D20Roll dataclasses
- Implemented DiceSystem singleton with cryptographically secure random generation
- Added Roll model to db_models.py with JSONB storage for roll history
- Implemented save_rolls_batch() and get_rolls_for_game() in database operations

Testing:
- 27 unit tests for roll type dataclasses (100% passing)
- 35 unit tests for dice system (34/35 passing, 1 timing issue)
- 16 integration tests for database persistence (uses production DiceSystem)

Features:
- Unique roll IDs using secrets.token_hex()
- League-specific logic (SBA d100 rare plays, PD error-based rare plays)
- Automatic derived value calculation (d6_two_total, jump_total, error_total)
- Full audit trail with context metadata
- Support for batch saving rolls per inning

Technical Details:
- Fixed dataclass inheritance with kw_only=True for Python 3.13
- Roll data stored as JSONB for flexible querying
- Indexed on game_id, roll_type, league_id, team_id for efficient retrieval
- Supports filtering by roll type, team, and timestamp ordering

Note: Integration tests have async connection pool issue when run together
(tests work individually, fixture cleanup needed in follow-up branch)

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

Co-Authored-By: Claude <noreply@anthropic.com>
 2025-10-24 08:29:02 -05:00
Cal Corum
9284162682 Clean up false positive Pylance errors 2025-10-23 09:10:41 -05:00
Cal Corum
8f67883be1 CLAUDE: Implement polymorphic Lineup model for PD and SBA leagues 
Updated Lineup model to support both leagues using the same pattern as RosterLink:
- Made card_id nullable (PD league)
- Added player_id nullable (SBA league)
- Added XOR CHECK constraint to ensure exactly one ID is populated
- Created league-specific methods: add_pd_lineup_card() and add_sba_lineup_player()
- Replaced generic create_lineup_entry() with league-specific methods

Database migration applied to convert existing schema.

Bonus fix: Resolved Pendulum DateTime + asyncpg timezone compatibility issue
by using .naive() on all DateTime defaults in Game, Play, and GameSession models.

Updated tests to use league-specific lineup methods.
Archived migration docs and script to .claude/archive/ for reference.

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

Co-Authored-By: Claude <noreply@anthropic.com>
 2025-10-23 08:35:24 -05:00
Cal Corum
3c5055dbf6 CLAUDE: Implement polymorphic RosterLink for both PD and SBA leagues 
Added league-agnostic roster tracking with single-table design:

Database Changes:
- Modified RosterLink model with surrogate primary key (id)
- Added nullable card_id (PD) and player_id (SBA) columns
- Added CHECK constraint ensuring exactly one ID populated (XOR logic)
- Added unique constraints for (game_id, card_id) and (game_id, player_id)
- Imported CheckConstraint and UniqueConstraint from SQLAlchemy

New Files:
- app/models/roster_models.py: Pydantic models for type safety
  - BaseRosterLinkData: Abstract base class
  - PdRosterLinkData: PD league card-based rosters
  - SbaRosterLinkData: SBA league player-based rosters
  - RosterLinkCreate: Request validation model

- tests/unit/models/test_roster_models.py: 24 unit tests (all passing)
  - Tests for PD/SBA roster link creation and validation
  - Tests for RosterLinkCreate XOR validation
  - Tests for polymorphic behavior

Database Operations:
- add_pd_roster_card(): Add PD card to game roster
- add_sba_roster_player(): Add SBA player to game roster
- get_pd_roster(): Get PD cards with optional team filter
- get_sba_roster(): Get SBA players with optional team filter
- remove_roster_entry(): Remove roster entry by ID

Tests:
- Added 12 integration tests for roster operations
- Fixed setup_database fixture scope (module → function)

Documentation:
- Updated backend/CLAUDE.md with RosterLink documentation
- Added usage examples and design rationale
- Updated Game model relationship description

Design Pattern:
Single table with application-layer type safety rather than SQLAlchemy
polymorphic inheritance. Simpler queries, database-enforced integrity,
and Pydantic type safety at application layer.

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

Co-Authored-By: Claude <noreply@anthropic.com>
 2025-10-22 22:45:44 -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
Cal Corum
fc7f53adf3 CLAUDE: Complete Phase 1 backend infrastructure setup 
Implemented full FastAPI backend with WebSocket support, database models,
and comprehensive documentation for the Paper Dynasty game engine.

Backend Implementation:
- FastAPI application with Socket.io WebSocket server
- SQLAlchemy async database models (Game, Play, Lineup, GameSession)
- PostgreSQL connection to dev server (10.10.0.42:5432)
- Connection manager for WebSocket lifecycle
- JWT authentication utilities
- Health check and stub API endpoints
- Rotating file logger with Pendulum datetime handling
- Redis via Docker Compose for caching

Technical Details:
- Python 3.13 with updated package versions
- Pendulum 3.0 for all datetime operations
- Greenlet for SQLAlchemy async support
- Fixed SQLAlchemy reserved column names (metadata -> *_metadata)
- Pydantic Settings with JSON array format for lists
- Docker Compose V2 commands

Documentation:
- Updated backend/CLAUDE.md with environment-specific details
- Created .claude/ENVIRONMENT.md for gotchas and quirks
- Created QUICKSTART.md for developer onboarding
- Documented all critical learnings and troubleshooting steps

Database:
- Tables created: games, plays, lineups, game_sessions
- All indexes and foreign keys configured
- Successfully tested connection and health checks

Verified:
- Server starts at http://localhost:8000
- Health endpoints responding
- Database connection working
- WebSocket infrastructure functional
- Hot-reload working

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

Co-Authored-By: Claude <noreply@anthropic.com>
 2025-10-21 19:46:16 -05:00