5c75b935f0
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)
156 lines
5.0 KiB
Markdown
156 lines
5.0 KiB
Markdown
# 🚨 CRITICAL: @ MENTION HANDLING 🚨
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When ANY file is mentioned with @ syntax, you MUST IMMEDIATELY call Read tool on that file BEFORE responding.
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You will see automatic loads of any @ mentioned filed, this is NOT ENOUGH, it only loads the file contents.
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You MUST perform Read tool calls on the files directly, even if they were @ included.
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This is NOT optional - it loads required CLAUDE.md context. along the file path.
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See @./.claude/force-claude-reads.md for details.
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---
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# Paper Dynasty Real-Time Game Engine - Development Guide
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## Project Overview
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Web-based real-time multiplayer baseball simulation platform replacing legacy Google Sheets system. Consists of:
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- **Shared Backend**: FastAPI (Python 3.11+) with WebSocket support, PostgreSQL persistence
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- **Dual Frontends**: Separate Vue 3/Nuxt 3 apps per league (SBA and PD) with shared component library
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**Critical Business Driver**: Legacy Google Sheets being deprecated - this is mission-critical replacement.
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## Architecture Principles
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### Backend Philosophy
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- **Hybrid State Model**: In-memory game state for performance + PostgreSQL for persistence/recovery
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- **League-Agnostic Core**: Polymorphic player models, config-driven league variations
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- **Async-First**: All I/O operations use async/await patterns
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- **Type Safety**: Pydantic models for validation, SQLAlchemy for ORM
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### Frontend Philosophy
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- **Mobile-First**: Primary design target is mobile portrait mode
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- **Real-Time Updates**: WebSocket (Socket.io) for all game state changes
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- **Shared Components**: Maximize reuse between league frontends
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- **Type Safety**: TypeScript with strict mode
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## Technology Stack
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### Backend
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- FastAPI + Socket.io (WebSocket)
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- PostgreSQL 14+ with SQLAlchemy 2.0
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- Pydantic for data validation
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- pytest for testing
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### Frontend (Per League)
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- Vue 3 Composition API + Nuxt 3
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- TypeScript (strict mode)
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- Tailwind CSS
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- Pinia for state management
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- Socket.io-client
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- @nuxtjs/auth-next (Discord OAuth)
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## Key Technical Patterns
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### Polymorphic Player Architecture
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Use factory pattern for league-specific player types:
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- `BasePlayer` (abstract base)
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- `SbaPlayer` (simple model)
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- `PdPlayer` (detailed scouting data)
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- `Lineup.from_api_data(config, data)` factory method
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### WebSocket Event Flow
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1. Player action → WebSocket → Backend
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2. Validate against in-memory state
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3. Process + resolve outcome
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4. Update in-memory state
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5. Async write to PostgreSQL
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6. Broadcast state update to all clients
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### Game State Recovery
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On reconnect: Load plays from DB → Replay to rebuild state → Send current state
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## Project Structure
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```
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strat-gameplay-webapp/
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├── backend/ # FastAPI game engine
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│ ├── app/
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│ │ ├── core/ # Game engine, dice, state management
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│ │ ├── config/ # League configs and result charts
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│ │ ├── websocket/ # Socket.io handlers
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│ │ ├── models/ # Pydantic + SQLAlchemy models
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│ │ └── api/ # REST endpoints
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│ └── tests/
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├── frontend-sba/ # SBA League Nuxt app
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├── frontend-pd/ # PD League Nuxt app
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└── shared-components/ # Shared Vue components (optional)
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```
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## Development Guidelines
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### Code Quality
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- **Python**: Dataclasses preferred, rotating loggers with `f'{__name__}.<className>'`
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- **Error Handling**: "Raise or Return" pattern - no Optional unless required
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- **Testing**: Run tests freely without asking permission
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- **Imports**: Always verify imports during code review to prevent NameErrors
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- **Git Commits**: Prefix with "CLAUDE: "
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### Performance Targets
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- Action response: < 500ms
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- WebSocket delivery: < 200ms
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- DB writes: < 100ms (async)
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- State recovery: < 2 seconds
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### Security Requirements
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- Discord OAuth for authentication
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- Server-side game logic only (zero client trust)
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- Cryptographically secure dice rolls
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- All rules enforced server-side
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## Phase 1 MVP Scope (Weeks 1-13)
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**Core Deliverables**:
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1. Authentication (Discord OAuth)
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2. Game creation & lobby
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3. Complete turn-based gameplay with all strategic decisions
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4. Real-time WebSocket updates
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5. Game persistence & recovery
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6. Spectator mode
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7. Mobile-optimized UI
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8. AI opponent support
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**Explicitly Out of Scope for MVP**:
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- Roster management
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- Marketplace
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- Tournaments
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- Advanced analytics
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## Critical References
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- **Full PRD**: `/mnt/NV2/Development/strat-gameplay-webapp/prd-web-scorecard-1.1.md`
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- **Player Model Architecture**: PRD lines 378-551
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- **Database Schema**: PRD lines 553-628
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- **WebSocket Events**: PRD lines 630-669
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- **League Config System**: PRD lines 780-846
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## League Differences
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### SBA League
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- Minimal player data (id, name, image)
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- Simpler rules configuration
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### PD League
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- Detailed scouting data on players
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- Complex probability calculations
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- Additional analytics requirements
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## Success Metrics
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- 90% player migration within 1 month
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- 99.5% uptime
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- < 500ms average action latency
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- 60%+ mobile usage
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- Zero data corruption
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---
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**Note**: Subdirectories will have their own CLAUDE.md files with implementation-specific details to minimize context usage.
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