## Authentication Implementation
### Backend
- Implemented complete Discord OAuth flow in auth.py:
* POST /api/auth/discord/callback - Exchange code for tokens
* POST /api/auth/refresh - Refresh JWT tokens
* GET /api/auth/me - Get authenticated user info
* GET /api/auth/verify - Verify auth status
- JWT token creation with 7-day expiration
- Refresh token support for session persistence
- Bearer token authentication for Discord API calls
### Frontend
- Created auth/login.vue - Discord OAuth initiation page
- Created auth/callback.vue - OAuth callback handler with states
- Integrated with existing auth store (already implemented)
- LocalStorage persistence for tokens and user data
- Full error handling and loading states
### Configuration
- Updated backend .env with Discord OAuth credentials
- Updated frontend .env with Discord Client ID
- Fixed redirect URI to port 3001
## SBA API Integration
### Backend
- Extended SbaApiClient with get_teams(season, active_only=True)
- Added bearer token auth support (_get_headers method)
- Created /api/teams route with TeamResponse model
- Registered teams router in main.py
- Filters out IL (Injured List) teams automatically
- Returns team data: id, abbrev, names, color, gmid, division
### Integration
- Connected to production SBA API: https://api.sba.manticorum.com
- Bearer token authentication working
- Successfully fetches ~16 active Season 3 teams
## Documentation
- Created SESSION_NOTES.md - Current session accomplishments
- Created NEXT_SESSION.md - Game creation implementation guide
- Updated implementation/NEXT_SESSION.md
## Testing
- ✅ Discord OAuth flow tested end-to-end
- ✅ User authentication and session persistence verified
- ✅ Teams API returns real data from production
- ✅ All services running and communicating
## What Works Now
- User can sign in with Discord
- Sessions persist across reloads
- Backend fetches real teams from SBA API
- Ready for game creation implementation
## Next Steps
See .claude/NEXT_SESSION.md for detailed game creation implementation plan.
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Removed outdated TODO comments and updated documentation to reflect
work completed in Phase 3E (Position Ratings and WebSocket Handlers).
Changes:
- Removed 2 stale WebSocket emission TODOs in game_engine.py (lines 319, 387)
These referenced Phase 3E-Final work completed on 2025-01-10
- Updated backend/CLAUDE.md Phase 3E status section
Marked defender retrieval as COMPLETE (Phase 3E-Main)
Clarified SPD test still pending (needs batter speed rating)
Marked runner advancement as COMPLETE (Phase 3D)
- Updated TODO_RESOLUTION_SUMMARY.md
Marked defender lookup TODO as resolved with implementation details
Documentation:
- Created TODO_AUDIT_2025-01-14.md - Complete TODO audit (53 items)
- Created TODO_VERIFICATION_RESULTS.md - Verification of resolved items
- Created TODO_SUMMARY.md - Quick reference priority matrix
- Created TODO_CLEANUP_COMPLETE.md - Cleanup work summary
Test Status:
- Backend: 9/9 PlayResolver tests passing
- No regressions introduced
Remaining Work:
- 41 legitimate TODOs properly categorized for future phases
- 8 Phase F6 TODOs (game page integration)
- 5 Quick win TODOs (optional polish)
- 28 Future phase TODOs (auth, AI, advanced features)
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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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**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.
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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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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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
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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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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- 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
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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- 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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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)
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Split player model architecture into dedicated documentation files for clarity
and maintainability. Added Phase 1 status tracking and comprehensive player
model specs covering API models, game models, mappers, and testing strategy.
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Add comprehensive unit and integration tests for Week 5 deliverables:
- test_play_resolver.py: 18 tests covering outcome resolution and runner advancement
- test_validators.py: 36 tests covering game state, decisions, lineups, and flow
- test_game_engine.py: 7 test classes for complete game flow integration
Update implementation documentation to reflect completed status:
- 00-index.md: Mark Phase 2 Weeks 4-5 complete with test coverage
- 02-week5-game-logic.md: Comprehensive test details and completion status
- 02-game-engine.md: Forward-looking snapshot pattern documentation
Week 5 now fully complete with 54 unit tests + 7 integration test classes passing.
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Initialize both Nuxt 3 frontends (SBA and PD) with full configuration:
Frontend Setup:
- Initialized Nuxt 3 projects for both leagues (SBA and PD)
- Installed dependencies: Tailwind CSS, Pinia, Socket.io-client, Axios
- Configured league-specific settings in nuxt.config.ts
- Created WebSocket plugins for real-time communication
- Set up TypeScript with strict mode and type checking
- Configured Tailwind CSS for styling
Backend Updates:
- Updated database models documentation in backend/CLAUDE.md
- Enhanced db_models.py with additional relationship patterns
Documentation:
- Updated Phase 1 completion checklist (12/12 items - 100% complete)
- Marked all infrastructure objectives as complete
Running Services:
- Backend (FastAPI + Socket.io): http://localhost:8000
- Frontend SBA: http://localhost:3000
- Frontend PD: http://localhost:3001
- Redis: port 6379
- PostgreSQL: Connected to remote server
Phase 1 is now complete. Ready to proceed to Phase 2 (Game Engine Core).
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Add comprehensive project documentation and Docker infrastructure for
Paper Dynasty Real-Time Game Engine - a web-based multiplayer baseball
simulation platform replacing the legacy Google Sheets system.
Documentation Added:
- Complete PRD (Product Requirements Document)
- Project README with dual development workflows
- Implementation guide with 5-phase roadmap
- Architecture docs (backend, frontend, database, WebSocket)
- CLAUDE.md context files for each major directory
Infrastructure Added:
- Root docker-compose.yml for full stack orchestration
- Dockerfiles for backend and both frontends (multi-stage builds)
- .dockerignore files for optimal build context
- .env.example with all required configuration
- Updated .gitignore for Python, Node, Nuxt, and Docker
Project Structure:
- backend/ - FastAPI + Socket.io game engine (Python 3.11+)
- frontend-sba/ - SBA League Nuxt 3 frontend
- frontend-pd/ - PD League Nuxt 3 frontend
- .claude/implementation/ - Detailed implementation guides
Supports two development workflows:
1. Local dev (recommended): Services run natively with hot-reload
2. Full Docker: One-command stack orchestration for testing/demos
Next: Phase 1 implementation (backend/frontend foundations)
