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6 Commits

Author SHA1 Message Date
Cal Corum
a696473d0a CLAUDE: Integrate flyball advancement with RunnerAdvancement system 
Major Phase 2 refactoring to consolidate runner advancement logic:

**Flyball System Enhancement**:
- Add FLYOUT_BQ variant (medium-shallow depth)
- 4 flyball types with clear semantics: A (deep), B (medium), BQ (medium-shallow), C (shallow)
- Updated helper methods to include FLYOUT_BQ

**RunnerAdvancement Integration**:
- Extend runner_advancement.py to handle both groundballs AND flyballs
- advance_runners() routes to _advance_runners_groundball() or _advance_runners_flyball()
- Comprehensive flyball logic with proper DECIDE mechanics per flyball type
- No-op movements recorded for state recovery consistency

**PlayResolver Refactoring**:
- Consolidate all 4 flyball outcomes to delegate to RunnerAdvancement (DRY)
- Eliminate duplicate flyball resolution code
- Rename helpers for clarity: _advance_on_single_1/_advance_on_single_2 (was _advance_on_single)
- Fix single/double advancement logic for different hit types

**State Recovery Fix**:
- Fix state_manager.py game recovery to build LineupPlayerState objects properly
- Use get_lineup_player() helper to construct from lineup data
- Correctly track runners in on_first/on_second/on_third fields (matches Phase 2 model)

**Database Support**:
- Add runner tracking fields to play data for accurate recovery
- Include batter_id, on_first_id, on_second_id, on_third_id, and *_final fields

**Type Safety Improvements**:
- Fix lineup_id access throughout runner_advancement.py (was accessing on_first directly, now on_first.lineup_id)
- Make current_batter_lineup_id non-optional (always set by _prepare_next_play)
- Add type: ignore for known SQLAlchemy false positives

**Documentation**:
- Update CLAUDE.md with comprehensive flyball documentation
- Add flyball types table, usage examples, and test coverage notes
- Document differences between groundball and flyball mechanics

**Testing**:
- Add test_flyball_advancement.py with 21 flyball tests
- Coverage: all 4 types, DECIDE scenarios, no-op movements, edge cases

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

Co-Authored-By: Claude <noreply@anthropic.com>
 2025-10-31 17:04:23 -05:00
Cal Corum
e2f1d6079f CLAUDE: Implement Week 7 Task 6 - PlayResolver Integration with RunnerAdvancement 
Major Refactor: Outcome-First Architecture
- PlayResolver now accepts league_id and auto_mode in constructor
- Added core resolve_outcome() method - all resolution logic in one place
- Added resolve_manual_play() wrapper for manual submissions (primary)
- Added resolve_auto_play() wrapper for PD auto mode (rare)
- Removed SimplifiedResultChart (obsolete with new architecture)
- Removed play_resolver singleton

RunnerAdvancement Integration:
- All groundball outcomes (GROUNDBALL_A/B/C) now use RunnerAdvancement
- Proper DP probability calculation with positioning modifiers
- Hit location tracked for all relevant outcomes
- 13 result types fully integrated from advancement charts

Game State Updates:
- Added auto_mode field to GameState (stored per-game)
- Updated state_manager.create_game() to accept auto_mode parameter
- GameEngine now uses state.auto_mode to create appropriate resolver

League Configuration:
- Added supports_auto_mode() to BaseGameConfig
- SbaConfig: returns False (no digitized cards)
- PdConfig: returns True (has digitized ratings)
- PlayResolver validates auto mode support and raises error for SBA

Play Results:
- Added hit_location field to PlayResult
- Groundballs include location from RunnerAdvancement
- Flyouts track hit_location for tag-up logic (future)
- Other outcomes have hit_location=None

Testing:
- Completely rewrote test_play_resolver.py for new architecture
- 9 new tests covering initialization, strikeouts, walks, groundballs, home runs
- All 9 tests passing
- All 180 core tests still passing (1 pre-existing failure unrelated)

Terminal Client:
- No changes needed - defaults to manual mode (auto_mode=False)
- Perfect for human testing of manual submissions

This completes Week 7 Task 6 - the final task of Week 7!
Week 7 is now 100% complete with all 8 tasks done.

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

Co-Authored-By: Claude <noreply@anthropic.com>
 2025-10-31 08:20:52 -05:00
Cal Corum
8ecce0f5ad CLAUDE: Implement forced outcome feature for terminal client testing 
Add ability to force specific play outcomes instead of random dice rolls,
enabling targeted testing of specific game scenarios.

Changes:
- play_resolver.resolve_play(): Add forced_outcome parameter, bypass dice
  rolls when provided, create dummy AbRoll with placeholder values
- game_engine.resolve_play(): Accept and pass through forced_outcome param
- terminal_client/commands.py: Pass forced_outcome to game engine

Testing:
- Verified TRIPLE, HOMERUN, and STRIKEOUT outcomes work correctly
- Dummy AbRoll properly constructed with all required fields
- Game state updates correctly with forced outcomes

Example usage in REPL:
  resolve_with triple
  resolve_with homerun

Fixes terminal client testing workflow to allow controlled scenarios.

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

Co-Authored-By: Claude <noreply@anthropic.com>
 2025-10-30 15:39:35 -05:00
Cal Corum
6880b6d5ad CLAUDE: Complete Week 6 - granular PlayOutcome integration and metadata support 
- Renamed check_d20 → chaos_d20 throughout dice system
- Expanded PlayOutcome enum with granular variants (SINGLE_1/2, DOUBLE_2/3, GROUNDBALL_A/B/C, etc.)
- Integrated PlayOutcome from app.config into PlayResolver
- Added play_metadata support for uncapped hit tracking
- Updated all tests (139/140 passing)

Week 6: 100% Complete - Ready for Phase 3

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

Co-Authored-By: Claude <noreply@anthropic.com>
 2025-10-29 20:29:06 -05:00
Cal Corum
1c32787195 CLAUDE: Refactor game models and modularize terminal client 
This commit includes cleanup from model refactoring and terminal client
modularization for better code organization and maintainability.

## Game Models Refactor

**Removed RunnerState class:**
- Eliminated separate RunnerState model (was redundant)
- Replaced runners: List[RunnerState] with direct base references:
  - on_first: Optional[LineupPlayerState]
  - on_second: Optional[LineupPlayerState]
  - on_third: Optional[LineupPlayerState]
- Updated helper methods:
  - get_runner_at_base() now returns LineupPlayerState directly
  - get_all_runners() returns List[Tuple[int, LineupPlayerState]]
  - is_runner_on_X() simplified to direct None checks

**Benefits:**
- Matches database structure (plays table has on_first_id, etc.)
- Simpler state management (direct references vs list management)
- Better type safety (LineupPlayerState vs generic runner)
- Easier to work with in game engine logic

**Updated files:**
- app/models/game_models.py - Removed RunnerState, updated GameState
- app/core/play_resolver.py - Use get_all_runners() instead of state.runners
- app/core/validators.py - Updated runner access patterns
- tests/unit/models/test_game_models.py - Updated test assertions
- tests/unit/core/test_play_resolver.py - Updated test data
- tests/unit/core/test_validators.py - Updated test data

## Terminal Client Refactor

**Modularization (DRY principle):**
Created separate modules for better code organization:

1. **terminal_client/commands.py** (10,243 bytes)
   - Shared command functions for game operations
   - Used by both CLI (main.py) and REPL (repl.py)
   - Functions: submit_defensive_decision, submit_offensive_decision,
     resolve_play, quick_play_sequence
   - Single source of truth for command logic

2. **terminal_client/arg_parser.py** (7,280 bytes)
   - Centralized argument parsing and validation
   - Handles defensive/offensive decision arguments
   - Validates formats (alignment, depths, hold runners, steal attempts)

3. **terminal_client/completions.py** (10,357 bytes)
   - TAB completion support for REPL mode
   - Command completions, option completions, dynamic completions
   - Game ID completions, defensive/offensive option suggestions

4. **terminal_client/help_text.py** (10,839 bytes)
   - Centralized help text and command documentation
   - Detailed command descriptions
   - Usage examples for all commands

**Updated main modules:**
- terminal_client/main.py - Simplified by using shared commands module
- terminal_client/repl.py - Cleaner with shared functions and completions

**Benefits:**
- DRY: Behavior consistent between CLI and REPL modes
- Maintainability: Changes in one place affect both interfaces
- Testability: Can test commands module independently
- Organization: Clear separation of concerns

## Documentation

**New files:**
- app/models/visual_model_relationships.md
  - Visual documentation of model relationships
  - Helps understand data flow between models
- terminal_client/update_docs/ (6 phase documentation files)
  - Phased documentation for terminal client evolution
  - Historical context for implementation decisions

## Tests

**New test files:**
- tests/unit/terminal_client/__init__.py
- tests/unit/terminal_client/test_arg_parser.py
- tests/unit/terminal_client/test_commands.py
- tests/unit/terminal_client/test_completions.py
- tests/unit/terminal_client/test_help_text.py

**Updated tests:**
- Integration tests updated for new runner model
- Unit tests updated for model changes
- All tests passing with new structure

## Summary

- ✅ Simplified game state model (removed RunnerState)
- ✅ Better alignment with database structure
- ✅ Modularized terminal client (DRY principle)
- ✅ Shared command logic between CLI and REPL
- ✅ Comprehensive test coverage
- ✅ Improved documentation

Total changes: 26 files modified/created

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

Co-Authored-By: Claude <noreply@anthropic.com>
 2025-10-28 14:16:38 -05:00
Cal Corum
0d7ddbe408 CLAUDE: Implement GameEngine, PlayResolver, and GameValidator 
Core Components:
✅ GameValidator (validators.py)
   - Validates game state and decisions
   - Rule enforcement for baseball gameplay
   - Game-over and inning continuation logic

✅ PlayResolver (play_resolver.py)
   - Resolves play outcomes using AbRoll system
   - Simplified result charts for MVP
   - Handles wild pitch/passed ball checks
   - Runner advancement logic for all hit types
   - PlayOutcome enum with 12 outcome types

✅ GameEngine (game_engine.py)
   - Orchestrates complete game flow
   - Start game, submit decisions, resolve plays
   - Integrates DiceSystem with roll context
   - Batch saves rolls at end of each half-inning
   - Persists plays and game state to database
   - Manages inning advancement and game completion

Integration Features:
- Uses advanced AbRoll system (not simplified d20)
- Roll context tracking per inning
- Batch persistence at inning boundaries
- Full audit trail with roll history
- State synchronization between memory and database

Architecture:
  GameEngine → PlayResolver → DiceSystem
       ↓             ↓
  GameValidator  StateManager
       ↓             ↓
   Database      In-Memory Cache

Ready For:
✅ End-to-end at-bat testing
✅ WebSocket integration
✅ Result chart configuration
✅ Advanced decision logic (Phase 3)

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

Co-Authored-By: Claude <noreply@anthropic.com>
 2025-10-24 10:00:21 -05:00