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# POWR Database Implementation PRD
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# [Feature Name] Design Document
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## Problem Statement
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## Problem Statement
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POWR requires a robust SQLite database implementation that enables local-first fitness tracking while supporting future Nostr protocol integration. The database must efficiently handle exercise definitions (NIP-33401), workout templates (NIP-33402), and workout records (NIP-33403) while maintaining a clean separation between local storage needs and Nostr protocol compatibility.
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[Concise description of the problem being solved]
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## Requirements
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## Requirements
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### Functional Requirements
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### Functional Requirements
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- Store and process exercise definitions with complete metadata
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- [List of must-have functionality]
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- Support workout template creation and management
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- [User-facing features]
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- Track workout records and performance history
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- [Core capabilities]
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- Enable efficient content querying and filtering
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- Handle both local and Nostr-sourced content seamlessly
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- Support offline-first operations with sync capabilities
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- Manage template dependencies and incomplete references
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- Track exercise history and performance metrics
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- Support batch operations and migrations
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### Non-Functional Requirements
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### Non-Functional Requirements
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- Query response time < 100ms for common operations
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- Performance targets
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- Support concurrent read/write operations safely
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- Security requirements
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- Minimize memory usage through efficient caching
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- Reliability goals
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- Maintain data integrity across sync operations
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- Usability standards
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- Scale to handle 1000+ exercises and 100+ templates
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- Support incremental sync with Nostr relays
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- Ensure consistent performance on mobile devices
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- Support automated testing and validation
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## Design Decisions
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## Design Decisions
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### 1. Storage Architecture
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### 1. [Major Decision Area]
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Use a dual storage approach with separate tables for raw events and processed data:
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[Description of approach chosen]
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Rationale:
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Rationale:
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- Maintains perfect relay replication capability
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- [Key reason]
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- Enables efficient local querying
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- [Supporting factors]
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- Supports dependency tracking
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- [Trade-offs considered]
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- Facilitates future sync operations
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- Allows for flexible schema evolution
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### 2. Cache Management
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### 2. [Major Decision Area]
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Implement an LRU cache system with configurable limits:
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[Description of approach chosen]
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Rationale:
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Rationale:
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- Improves read performance for common queries
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- [Key reason]
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- Manages memory usage effectively
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- [Supporting factors]
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- Supports write buffering for batch operations
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- [Trade-offs considered]
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- Provides tunable performance controls
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### 3. Schema Design
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Use a normalized schema with proper constraints and indexing:
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Rationale:
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- Ensures data integrity
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- Enables efficient querying
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- Supports future extensions
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- Maintains clear relationships
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## Technical Design
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## Technical Design
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### Core Schema
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```sql
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-- Schema Version
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CREATE TABLE schema_version (
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version INTEGER PRIMARY KEY,
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updated_at INTEGER NOT NULL
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);
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-- Raw Events
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CREATE TABLE nostr_events (
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id TEXT PRIMARY KEY,
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kind INTEGER NOT NULL,
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pubkey TEXT NOT NULL,
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created_at INTEGER NOT NULL,
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content TEXT,
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raw_event TEXT NOT NULL,
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source TEXT DEFAULT 'local'
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);
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-- Processed Exercises
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CREATE TABLE exercise_definitions (
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event_id TEXT PRIMARY KEY,
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title TEXT NOT NULL,
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type TEXT NOT NULL,
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category TEXT NOT NULL,
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equipment TEXT,
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description TEXT,
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format_json TEXT,
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format_units_json TEXT,
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FOREIGN KEY(event_id) REFERENCES nostr_events(id)
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);
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-- Templates
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CREATE TABLE workout_templates (
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event_id TEXT PRIMARY KEY,
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title TEXT NOT NULL,
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type TEXT NOT NULL,
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category TEXT NOT NULL,
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description TEXT,
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rounds INTEGER,
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duration INTEGER,
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interval_time INTEGER,
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rest_between_rounds INTEGER,
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created_at INTEGER NOT NULL,
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FOREIGN KEY(event_id) REFERENCES nostr_events(id)
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);
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```
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### Core Components
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### Core Components
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```typescript
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```typescript
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interface DbService {
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// Key interfaces/types
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// Core database operations
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interface ComponentName {
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executeSql(sql: string, params?: any[]): Promise<SQLiteResult>;
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// Critical fields
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withTransaction<T>(operation: () => Promise<T>): Promise<T>;
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// Migration handling
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getCurrentVersion(): Promise<number>;
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migrate(targetVersion?: number): Promise<void>;
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}
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}
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interface CacheManager {
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// Core functionality
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// Cache configuration
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function mainOperation() {
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maxExercises: number;
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// Key logic
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maxTemplates: number;
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writeBufferSize: number;
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// Cache operations
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get<T>(key: string): Promise<T | undefined>;
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set<T>(key: string, value: T): Promise<void>;
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invalidate(key: string): Promise<void>;
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}
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}
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```
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```
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### Integration Points
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- [System interfaces]
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- [External dependencies]
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- [API definitions]
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## Implementation Plan
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## Implementation Plan
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### Phase 1: Core Infrastructure (Week 1-2)
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### Phase 1: [Initial Phase]
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1. Set up base schema and migrations
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1. [Step 1]
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2. Implement DbService class
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2. [Step 2]
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3. Add basic CRUD operations
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3. [Step 3]
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4. Create test infrastructure
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### Phase 2: Cache Layer (Week 2-3)
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### Phase 2: [Next Phase]
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1. Implement CacheManager
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1. [Step 1]
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2. Add LRU caching
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2. [Step 2]
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3. Configure write buffering
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3. [Step 3]
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4. Add cache invalidation
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### Phase 3: Query Layer (Week 3-4)
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1. Build query builders
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2. Implement common queries
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3. Add search functionality
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4. Optimize performance
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### Phase 4: Nostr Integration (Week 4-5)
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1. Add event processing
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2. Implement sync logic
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3. Handle dependencies
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4. Add relay management
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## Testing Strategy
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## Testing Strategy
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### Unit Tests
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### Unit Tests
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- Schema creation and migrations
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- [Key test areas]
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- CRUD operations for all entities
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- [Critical test cases]
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- Cache operations and invalidation
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- [Test tooling]
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- Query builder functions
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### Integration Tests
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### Integration Tests
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- End-to-end workflow testing
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- [End-to-end scenarios]
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- Template dependency handling
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- [Cross-component tests]
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- Sync operations
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- [Test environments]
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- Performance benchmarks
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### Performance Tests
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- Query response times
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- Cache hit rates
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- Write operation latency
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- Memory usage patterns
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## Observability
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## Observability
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### Logging
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### Logging
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- Schema migrations
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- [Key log points]
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- Cache operations
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- [Log levels]
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- Query performance
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- [Critical events]
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- Error conditions
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### Metrics
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### Metrics
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- Query response times
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- [Performance metrics]
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- Cache hit/miss rates
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- [Business metrics]
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- Database size
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- [System health metrics]
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- Operation counts
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## Future Considerations
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## Future Considerations
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### Potential Enhancements
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### Potential Enhancements
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- Advanced caching strategies
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- [Future feature ideas]
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- Full-text search
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- [Scalability improvements]
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- Data compression
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- [Technical debt items]
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- Cloud backup options
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### Known Limitations
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### Known Limitations
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- SQLite concurrent access
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- [Current constraints]
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- Initial sync performance
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- [Technical restrictions]
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- Cache memory constraints
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- [Scope boundaries]
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- Platform-specific issues
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## Dependencies
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## Dependencies
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### Runtime Dependencies
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### Runtime Dependencies
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- expo-sqlite
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- [External services]
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- @react-native-async-storage/async-storage
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- [Libraries]
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- NDK (future)
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- [System requirements]
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### Development Dependencies
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### Development Dependencies
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- Jest
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- [Build tools]
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- TypeScript
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- [Test frameworks]
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- SQLite development tools
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- [Development utilities]
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## Security Considerations
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## Security Considerations
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- Input validation
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- [Security measures]
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- Query parameterization
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- [Privacy concerns]
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- Event signature verification
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- [Data protection]
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- Access control
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## Rollout Strategy
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### Development Phase
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1. [Development steps]
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2. [Testing approach]
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3. [Documentation needs]
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### Production Deployment
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1. [Deployment steps]
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2. [Migration plan]
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3. [Monitoring setup]
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## References
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## References
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- NDK SQLite Implementation
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- [Related documents]
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- Nostr NIP-01 Specification
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- [External resources]
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- POWR Exercise NIP Draft
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- [Research materials]
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- React Native SQLite Documentation
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