Updated NEXT_SESSION.md to reflect Phase 3E-Main completion:
- Marked Phase 3E-Main as 100% complete (position ratings integration)
- Overall Phase 3E progress now 90%
- Updated Phase 3 overall progress to ~95%
- Documented all accomplishments and live test results
- Outlined remaining Phase 3E-Final tasks (10%):
* WebSocket event handlers for X-Check UI
* Redis caching upgrade from in-memory
* Full defensive lineup evaluation
* Manual vs Auto mode workflows
Included comprehensive session handoff:
- Live API test results with player 8807 (7 positions)
- Performance metrics (16,601x cache speedup)
- All files created/modified
- Quick start guide for next session
- Technical architecture notes
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Complete integration of position ratings system enabling X-Check defensive plays
to use actual player ratings from PD API with intelligent fallbacks for SBA.
**Live API Testing Verified**: ✅
- Endpoint: GET https://pd.manticorum.com/api/v2/cardpositions?player_id=8807
- Response: 200 OK, 7 positions retrieved successfully
- Cache performance: 16,601x faster (API: 0.214s, Cache: 0.000s)
- Data quality: Real defensive ratings (range 1-5, error 0-88)
**Architecture Overview**:
- League-aware: PD league fetches ratings from API, SBA uses defaults
- StateManager integration: Defenders retrieved from lineup cache
- Self-contained GameState: All data needed for X-Check in memory
- Graceful degradation: Falls back to league averages if ratings unavailable
**Files Created**:
1. app/services/pd_api_client.py (NEW)
- PdApiClient class for PD API integration
- Endpoint: GET /api/v2/cardpositions?player_id={id}&position={pos}
- Async HTTP client using httpx (already in requirements.txt)
- Optional position filtering: get_position_ratings(8807, ['SS', '2B'])
- Returns List[PositionRating] for all positions player can play
- Handles both list and dict response formats
- Comprehensive error handling with logging
2. app/services/position_rating_service.py (NEW)
- PositionRatingService with in-memory caching
- get_ratings_for_card(card_id, league_id) - All positions
- get_rating_for_position(card_id, position, league_id) - Specific position
- Cache performance: >16,000x faster on hits
- Singleton pattern: position_rating_service instance
- TODO Phase 3E-Final: Upgrade to Redis
3. app/services/__init__.py (NEW)
- Package exports for clean imports
4. test_pd_api_live.py (NEW)
- Live API integration test script
- Tests with real PD player 8807 (7 positions)
- Verifies caching, filtering, GameState integration
- Run: `python test_pd_api_live.py`
5. test_pd_api_mock.py (NEW)
- Mock integration test for CI/CD
- Demonstrates flow without API dependency
6. tests/integration/test_position_ratings_api.py (NEW)
- Pytest integration test suite
- Real API tests with player 8807
- Cache verification, SBA skip logic
- Full end-to-end GameState flow
**Files Modified**:
1. app/models/game_models.py
- LineupPlayerState: Added position_rating field (Optional[PositionRating])
- GameState: Added get_defender_for_position(position, state_manager)
- Uses StateManager's lineup cache to find active defender by position
- Iterates through lineup.players to match position + is_active
2. app/config/league_configs.py
- SbaConfig: Added supports_position_ratings() → False
- PdConfig: Added supports_position_ratings() → True
- Enables league-specific behavior without hardcoded conditionals
3. app/core/play_resolver.py
- __init__: Added state_manager parameter for X-Check defender lookup
- _resolve_x_check(): Replaced placeholder defender ratings with actual lookup
- Uses league config to check if ratings supported
- Fetches defender via state.get_defender_for_position()
- Falls back to defaults (range=3, error=15) if ratings unavailable
- Detailed logging for debugging rating lookups
4. app/core/game_engine.py
- Added _load_position_ratings_for_lineup() method
- Loads all position ratings at game start for PD league
- Skips loading for SBA (league config check)
- start_game(): Calls rating loader for both teams before marking active
- PlayResolver instantiation: Now passes state_manager parameter
- Logs: "Loaded X/9 position ratings for team Y"
**X-Check Resolution Flow**:
1. League check: config.supports_position_ratings()?
2. Get defender: state.get_defender_for_position(pos, state_manager)
3. If PD + defender.position_rating exists: Use actual range/error
4. Else if defender found: Use defaults (range=3, error=15)
5. Else: Log warning, use defaults
**Position Rating Loading (Game Start)**:
1. Check if league supports ratings (PD only)
2. Get lineup from StateManager cache
3. For each player:
- Fetch rating from position_rating_service (with caching)
- Set player.position_rating field
4. Cache API responses (16,000x faster on subsequent access)
5. Log success: "Loaded X/9 position ratings for team Y"
**Live Test Results (Player 8807)**:
```
Position Range Error Innings
CF 3 2 372
2B 3 8 212
SS 4 12 159
RF 2 2 74
LF 3 2 62
1B 4 0 46
3B 3 65 34
```
**Testing**:
- ✅ Live API: Player 8807 → 7 positions retrieved successfully
- ✅ Caching: 16,601x performance improvement
- ✅ League config: SBA=False, PD=True
- ✅ GameState integration: Defender lookup working
- ✅ Existing tests: 27/28 config tests passing (1 pre-existing URL failure)
- ✅ Syntax validation: All files compile successfully
**Benefits**:
- ✅ X-Check now uses real defensive ratings in PD league
- ✅ SBA league continues working with manual entry (uses defaults)
- ✅ No breaking changes to existing functionality
- ✅ Graceful degradation if API unavailable
- ✅ In-memory caching reduces API calls by >99%
- ✅ League-agnostic design via config system
- ✅ Production-ready with live API verification
**Phase 3E Status**: Main complete (85% → 90%)
**Next**: Phase 3E-Final (WebSocket events, Redis upgrade, full defensive lineup)
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**Documentation Updates**:
NEXT_SESSION.md:
- Updated status: Phase 3 now 85% complete (was 80%)
- Added Phase 3E-Prep section documenting GameState refactor
- Updated current context with new approach
- Added Architecture Decision #6: Unified Player References
- Updated Tasks for Next Session to reflect simplified Phase 3E-Main
- Last commit: d560844
- Date: 2025-11-03
**Key Changes Documented**:
1. GameState refactor complete (all player refs now full objects)
2. Foundation ready for Phase 3E-Main (add position ratings)
3. Simplified approach: just add field, load at game start
4. X-Check resolution gets direct access: state.current_batter.position_rating
**Next Steps**: Phase 3E-Main tasks updated to reflect new architecture
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**Architectural Improvement**: Unified player references in GameState
**Changed**: Make all player references consistent
- BEFORE: current_batter/pitcher/catcher were IDs (int)
- AFTER: current_batter/pitcher/catcher are full LineupPlayerState objects
- Matches pattern of on_first/on_second/on_third (already objects)
**Benefits**:
1. Consistent API - all player references use same type
2. Self-contained GameState - everything needed for resolution
3. No lookups needed - direct access to player data
4. Sets foundation for Phase 3E-Main (adding position ratings)
**Files Modified**:
- app/models/game_models.py: Changed current_batter/pitcher/catcher to objects
- app/core/game_engine.py: Updated _prepare_next_play() to populate full objects
- app/core/state_manager.py: Create placeholder batter on game creation
- tests/unit/models/test_game_models.py: Updated all 27 GameState tests
**Database Operations**:
- No schema changes needed
- Play table still stores IDs (for referential integrity)
- IDs extracted from objects when saving: state.current_batter.lineup_id
**Testing**:
- All 27 GameState tests passing
- No regressions in existing functionality
- Type checking passes
**Next**: Phase 3E-Main - Add PositionRating dataclass and load ratings at game start
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Updated documentation to accurately reflect all work completed in Phase 2:
**NEXT_SESSION.md Updates**:
- Updated last commit reference: 4cf349a → 313c2c8 (Phase 2 merge)
- Added "Additional Phase 2 Completions" section documenting:
- 8,799 lines of comprehensive CLAUDE.md documentation
- Flyball advancement system integration (21 new tests)
- FLYOUT_BQ variant addition (4 flyball types total)
- ManualOutcomeSubmission enum refactoring
- State recovery fixes
- Updated test counts: ~540 total tests (all passing)
- Added branch information: implementation-phase-3
- Clarified status: Phase 2 COMPLETE → Phase 3 Ready to Begin
**00-index.md Updates**:
- Expanded implementation status table with Phase 2 completions:
- Runner Advancement, Strategic Decisions, Result Charts
- WebSocket Manual Mode, Terminal Client, Comprehensive Docs
- Updated test suite status: ~540 tests passing
- Added Phase 2 completion to decisions log (2025-10-31)
- Updated "Last Updated" section for 2025-11-03
- Changed phase status to "Ready to Begin" for Phase 3
These notes now accurately reflect all commits from 4cf349a through 313c2c8,
including the major flyball integration, documentation additions, and test
updates that happened after the initial Week 7 completion.
Updated X-Check runner advancement functions to properly delegate to
existing result handlers for non-error cases.
Changes:
- Updated x_check_g1/g2/g3 signatures to accept GameState, hit_location,
and defensive_decision parameters
- Updated x_check_f1/f2/f3 signatures to accept GameState and hit_location
- Implemented delegation logic: error cases use simple tables, non-error
cases delegate to existing tested result handlers (_execute_result,
_fb_result_*)
- Updated PlayResolver._get_x_check_advancement() to pass new parameters
- Updated all tests to provide required GameState fixtures
Benefits:
- Reuses 13 existing groundball + 4 flyball result handlers (DRY)
- No DP probability needed - X-Check d20 already tested defender
- Full game context: real lineup IDs, outs count, conditional logic
- Error cases remain simple and efficient
Test Results: 264/265 core tests passing (1 pre-existing dice failure)
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Fixed incorrect double play logic that was rolling for probability
twice - once for the chart result and again for execution.
Changes:
- Removed _calculate_double_play_probability() method entirely
- Updated _gb_result_2() to execute DP deterministically
- Updated _gb_result_10() to execute DP deterministically
- Updated _gb_result_13() to execute DP deterministically
- Removed TestDoublePlayProbability test class (5 tests)
- Updated DP tests to reflect deterministic behavior
Logic: Chart already determines outcome via dice roll. When chart
says "Result 2: Double Play", the DP happens (if <2 outs and runner
on 1st exists). No additional probability roll needed.
Tests: 55/55 runner advancement tests passing
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Fixed two critical bugs in Phase 3D X-Check implementation plus
improved dice audit trail for better tracking.
BUG #1: on_base_code Mapping Error (Sequential vs Bit Field)
============================================================
The implementation incorrectly treated on_base_code as a bit field
when it is actually a sequential lookup mapping.
WRONG (bit field):
Code 3 (0b011) → R1 + R2
Code 4 (0b100) → R3 only
CORRECT (sequential):
Code 3 → R3 only
Code 4 → R1 + R2
Fixed:
- build_advancement_from_code() decoder (sequential mapping)
- build_flyball_advancement_with_error() decoder (sequential mapping)
- 13 test on_base_code values (3↔4 corrections)
- Updated documentation to clarify NOT a bit field
BUG #2: Table Data Not Matching Official Charts
================================================
7 table entries in G1_ADVANCEMENT_TABLE and G2_ADVANCEMENT_TABLE
did not match the official rulebook charts provided by user.
Fixed table entries:
- G1 Code 1, Infield In: Changed Result 3 → 2
- G1 Code 3, Normal: Changed Result 13 → 3
- G1 Code 3, Infield In: Changed Result 3 → 1
- G1 Code 4, Normal: Changed Result 3 → 13
- G1 Code 4, Infield In: Changed Result 4 → 2
- G2 Code 3, Infield In: Changed Result 3 → 1
- G2 Code 4, Normal: Changed Result 5 → 4
Also fixed 7 test expectations to match corrected tables.
IMPROVEMENT: Better Dice Audit Trail
=====================================
Updated _resolve_x_check() in PlayResolver to use proper
dice_system.roll_fielding() instead of manual die rolling.
Benefits:
- All dice tracked in audit trail (roll_id, timestamp, position)
- Automatic error_total calculation (no manual 3d6 addition)
- Consistent with codebase patterns
- Position recorded for historical analysis
Testing:
- All 59 X-Check advancement tests passing (100%)
- All 9 PlayResolver tests passing (100%)
- All table entries validated against official charts
- Complete codebase scan: no bit field operations found
Files modified:
- backend/app/core/x_check_advancement_tables.py
- backend/tests/unit/core/test_x_check_advancement_tables.py
- backend/app/core/play_resolver.py
- .claude/implementation/PHASE_3D_CRITICAL_FIX.md (documentation)
- .claude/implementation/GROUNDBALL_CHART_REFERENCE.md (new)
- .claude/implementation/XCHECK_TEST_VALIDATION.md (new)
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Added comprehensive Phase 3C documentation to CLAUDE.md:
- X-Check resolution logic implementation details
- Helper methods and integration points
- Key features and algorithms
- Placeholders for future phases
- Test coverage and verification results
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Implemented complete X-Check resolution system in PlayResolver with
defense range and error table lookups.
Changes:
- Added X_CHECK case to resolve_outcome() method
- Implemented _resolve_x_check() main resolution method
- Added _adjust_range_for_defensive_position() for playing in logic
- Added _lookup_defense_table() for defense range table lookups
- Added _apply_hash_conversion() for G2#/G3# to SI2 conversion
- Added _lookup_error_chart() for error determination
- Added _determine_final_x_check_outcome() for final outcome mapping
- Added XCheckResult to PlayResult dataclass
- Integrated all Phase 3B tables (defense, error, holding runners)
Features:
- Full defense table lookup (infield, outfield, catcher)
- Error chart lookup with priority ordering (RP > E3 > E2 > E1 > NO)
- Range adjustment for playing in (+1, max 5)
- Hash conversion based on playing in OR holding runner
- Error overrides outs to ERROR outcome
- Rare play handling
- Detailed X-Check audit trail in XCheckResult
Placeholders (to be completed in later phases):
- Defender retrieval from lineup (currently uses placeholder ratings)
- SPD test implementation (currently defaults to G3)
- Batter handedness from player model
- Runner advancement tables (Phase 3D)
Testing:
- All 9 PlayResolver tests passing
- All 36 X-Check table tests passing
- All 51 runner advancement tests passing
- 325/327 total tests passing (2 pre-existing failures unrelated)
- play_resolver.py compiles successfully
Phase 3C Status: 100% COMPLETE ✅
Ready for Phase 3D (Runner Advancement Tables)
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Add foundational data structures for X-Check play resolution system:
Models Added:
- PositionRating: Defensive ratings (range 1-5, error 0-88) for X-Check resolution
- XCheckResult: Dataclass tracking complete X-Check resolution flow with dice rolls,
conversions (SPD test, G2#/G3#→SI2), error results, and final outcomes
- BasePlayer.active_position_rating: Optional field for current defensive position
Enums Extended:
- PlayOutcome.X_CHECK: New outcome type requiring special resolution
- PlayOutcome.is_x_check(): Helper method for type checking
Documentation Enhanced:
- Play.check_pos: Documented as X-Check position identifier
- Play.hit_type: Documented with examples (single_2_plus_error_1, etc.)
Utilities Added:
- app/core/cache.py: Redis cache key helpers for player positions and game state
Implementation Planning:
- Complete 6-phase implementation plan (3A-3F) documented in .claude/implementation/
- Phase 3A complete with all acceptance criteria met
- Zero breaking changes, all existing tests passing
Next: Phase 3B will add defense tables, error charts, and advancement logic
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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
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- Update test fixtures to provide required current_batter_lineup_id field
- Update validator tests for new infield depth values (infield_in, normal, corners_in)
- Update runner advancement tests to match refactored runner management
- Update game model tests to work with direct base references
- Update play resolver tests for enhanced logic
- Add missing imports in test files
All changes ensure tests align with recent Phase 2 implementation updates
including the transition from RunnerState list to direct base references
(on_first, on_second, on_third) in GameState model.
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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.
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Updated documentation to reflect completion of runner advancement logic
and double play mechanics:
Status Changes:
- Week 7 progress: 62% → 87% complete
- Tasks complete: 7 of 8 (only Task 6 remaining)
- Test count: 489 → 519 tests passing (94% of target)
Completed Tasks:
- Task 4: Runner advancement logic (30 tests)
- GroundballResultType IntEnum with 13 result constants
- Infield Back and Infield In chart implementations
- Corners In hybrid positioning support
- DECIDE mechanic foundation
- Task 5: Double play mechanics (integrated into Task 4)
- Probability-based DP calculation (45% base)
- Positioning and hit location modifiers
- Integrated into results 2, 10, and 13
Documentation Updates:
- Added comprehensive Task 4 & 5 completion summary
- Updated "What We Just Completed" with full implementation details
- Resolved outstanding questions (TOOTBLAN/FARTSLAM deprecated)
- Updated Quick Reference with new test counts
- Streamlined "Tasks for Next Session" to focus on Task 6
- Updated commit history and progress metrics
Next Steps:
- Task 6: PlayResolver Integration (final task, 3-4 hours)
- Integrate RunnerAdvancement into play_resolver.py
- Update all existing tests
- Week 7 completion at 100%
Related: #week7 #task4 #task5 #runner-advancement #documentation
- Created runner_advancement.py with complete groundball advancement system
- Implemented GroundballResultType IntEnum with 13 rulebook-aligned results
- Built RunnerAdvancement class with chart lookup logic (Infield Back/In)
- Implemented all 13 result handlers (gb_result_1 through gb_result_13)
- Added DECIDE mechanic support for interactive runner advancement decisions
- Implemented double play probability calculation with positioning modifiers
- Created 30 comprehensive unit tests covering all scenarios (100% passing)
Key Features:
- Supports Infield Back and Infield In defensive positioning
- Handles Corners In hybrid positioning (applies In rules to corner fielders)
- Conditional results based on hit location (middle IF, right side, corners)
- Force play detection and advancement logic
- Double play mechanics with probability-based success (45% base rate)
- Result types match official rulebook exactly (1-13)
Architecture:
- IntEnum for result types (type-safe, self-documenting)
- Comprehensive hit location tracking (1B, 2B, SS, 3B, P, C, LF, CF, RF)
- Dataclasses for movements (RunnerMovement, AdvancementResult)
- Probability modifiers: Infield In (-15%), hit location (±10%)
Testing:
- 30 unit tests covering chart lookup, all result types, and edge cases
- Double play probability validation
- All on-base codes (0-7) tested
- All groundball types (A, B, C) verified
Status: Week 7 Tasks 4 & 5 complete (~87% of Week 7 finished)
Next: Task 6 (PlayResolver Integration)
Related: #task4 #task5 #runner-advancement #double-play #week7
Complete manual outcome workflow for SBA and PD manual mode gameplay:
**WebSocket Event Handlers** (app/websocket/handlers.py):
- roll_dice: Server rolls dice, stores in state, broadcasts to players
- submit_manual_outcome: Validates and processes player submissions
- Events: dice_rolled, outcome_accepted, outcome_rejected, play_resolved
**Game Engine Integration** (app/core/game_engine.py):
- resolve_manual_play(): Processes manual outcomes with server dice
- Uses ab_roll for audit trail, player outcome for resolution
- Same orchestration as resolve_play() (save, update, advance inning)
**Data Model** (app/models/game_models.py):
- pending_manual_roll: Stores server dice between roll and submission
**Terminal Client** (terminal_client/):
- roll_dice command: Roll dice and display results
- manual_outcome command: Submit outcomes from physical cards
- Both integrated into REPL for testing
**Tests** (tests/unit/websocket/test_manual_outcome_handlers.py):
- 12 comprehensive tests covering all validation paths
- All tests passing (roll_dice: 4, submit_manual_outcome: 8)
**Key Decisions**:
- Server rolls dice for fairness (not players!)
- One-time roll usage (cleared after submission)
- Early validation (check pending roll before accepting)
- Field-level error messages for clear feedback
**Impact**:
- Complete manual mode workflow ready
- Frontend WebSocket integration supported
- Terminal testing commands available
- Audit trail with server-rolled dice maintained
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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).
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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.
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Update session planning document to reflect Task 3 completion:
- Result chart abstraction implemented
- PD auto mode with rating-based outcome generation
- Manual outcome submission model for human players
- 21 new tests passing
Week 7 now 50% complete (3 of 7 tasks done).
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Co-Authored-By: Claude <noreply@anthropic.com>
Remove unused PlayResult creation code that had incorrect import path
and missing required fields. The forced outcome feature is experimental
and not yet implemented - the code was just showing warnings anyway.
Fixes ImportError when running 'resolve_with <outcome>' command.
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New Commands:
- manual_outcome <outcome> [location] - Validates ManualOutcomeSubmission
- Tests outcome and location validation
- Shows which outcomes require hit location
- Displays clear validation errors
- test_location <outcome> [handedness] [count] - Tests hit location distribution
- Generates sample hit locations for an outcome
- Shows distribution table with percentages
- Validates pull rates (45% pull, 35% center, 20% opposite)
- Supports both LHB and RHB
Implementation:
- Added validate_manual_outcome() to GameCommands class
- Added test_hit_location() to GameCommands class
- Added do_manual_outcome() to REPL
- Added do_test_location() to REPL
- Uses ManualOutcomeSubmission model from Task 3
- Uses calculate_hit_location() helper from Task 3
Testing:
- Tested manual_outcome with valid outcomes (groundball_c SS, strikeout)
- Tested manual_outcome with invalid outcome (proper error display)
- Tested test_location with groundball_c for RHB (shows distribution)
- All validation and display working correctly
Note: Full play resolution integration deferred to Week 7 Task 6 (WebSocket handlers).
These commands validate and test the new models but don't resolve plays yet.
Files Modified:
- terminal_client/commands.py (+117 lines)
- terminal_client/repl.py (+65 lines)
- Updated current status to 33% complete (2 of 6 tasks done)
- Added comprehensive Task 2 completion details
- Updated success criteria to show 24/85 new tests passing
- Set next task to Task 3: Complete Result Charts - Part A
- Enhanced validate_defensive_decision() with comprehensive validation:
- Validate all alignments (normal, shifted_left, shifted_right, extreme_shift)
- Validate all infield depths (in, normal, back, double_play)
- Validate all outfield depths (in, normal, back)
- Validate hold_runners require actual runners on specified bases
- Validate hold_runners only on bases 1, 2, or 3
- Validate double_play depth requires runner on first
- Validate double_play depth not allowed with 2 outs
- Enhanced validate_offensive_decision() with comprehensive validation:
- Validate all approaches (normal, contact, power, patient)
- Validate steal_attempts only to bases 2, 3, or 4
- Validate steal_attempts require runner on base-1
- Validate bunt_attempt not allowed with 2 outs
- Validate bunt_attempt and hit_and_run cannot be simultaneous
- Validate hit_and_run requires at least one runner on base
- Added 24+ comprehensive test cases covering all edge cases:
- 13 new defensive decision validation tests
- 16 new offensive decision validation tests
- All tests pass (54/54 passing)
Clear error messages for all validation failures.
Follows 'Raise or Return' pattern with ValidationError exceptions.
Terminal Client Enhancements:
- Added list_outcomes command to display all PlayOutcome values
- Added resolve_with <outcome> command for testing specific scenarios
- TAB completion for all outcome names
- Full help documentation and examples
- Infrastructure ready for Week 7 integration
Files Modified:
- terminal_client/commands.py - list_outcomes() and forced outcome support
- terminal_client/repl.py - do_list_outcomes() and do_resolve_with() commands
- terminal_client/completions.py - VALID_OUTCOMES and complete_resolve_with()
- terminal_client/help_text.py - Help entries for new commands
Phase 3 Planning:
- Created comprehensive Week 7 implementation plan (25 pages)
- 6 major tasks covering strategic decisions and result charts
- Updated 00-index.md to mark Week 6 as 100% complete
- Documented manual outcome testing feature
Week 6: 100% Complete ✅
Phase 3 Week 7: Ready to begin
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Co-Authored-By: Claude <noreply@anthropic.com>
- 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
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Updated week 6 status and created comprehensive next session plan.
## Changes
### Implementation Status Updates
- Updated 00-index.md with Week 6 progress (75% complete)
- Updated 02-week6-league-features.md status and goals
- Added new components to status table:
- League Configs: ✅ Complete
- PlayOutcome Enum: ✅ Complete
- PlayResolver Integration: 🟡 Partial
### Next Session Plan (NEW)
Created NEXT_SESSION.md with detailed task breakdown:
**Task 1: Update Dice System** (30 min)
- Rename check_d20 → chaos_d20
- Update docstrings for chaos die purpose
- Update all references
**Task 2: Integrate PlayOutcome** (60 min)
- Replace old local enum with universal enum
- Update SimplifiedResultChart
- Add uncapped hit handling
- Update all outcome references
**Task 3: Add Play.metadata** (30 min)
- Add JSONB metadata field to Play model
- Log uncapped hits in metadata
- Update game_engine._save_play_to_db()
## Quick Context for Next Session
**What's Complete**: Config system, PlayOutcome enum, 58 tests passing
**What's Remaining**: Dice system update, PlayResolver integration, metadata support
**Estimated Time**: 2 hours
**Success Criteria**: All tests passing, uncapped hits tracked, terminal client works
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Co-Authored-By: Claude <noreply@anthropic.com>
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
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Co-Authored-By: Claude <noreply@anthropic.com>
