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Copy file name to clipboardExpand all lines: doc/internal/architecture.md
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- Maintains full API compatibility
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- Can track upstream improvements
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While this required significant effort to create the compatibility layer, it provides the best balance between compatibility, maintainability, and usability.
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The compatibility layer took real effort to build, but it keeps the package compatible, maintainable, and easy to use.
Copy file name to clipboardExpand all lines: doc/internal/async-design.md
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# Async API Design Analysis for @photostructure/sqlite
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## Executive Summary
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## Summary
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This document analyzes options for adding asynchronous API support to the @photostructure/sqlitelibrary, which currently provides a synchronous SQLite interface matching Node.js's built-in sqlite module. After careful analysis, we recommend creating a separate package for the async API rather than integrating it into the existing library.
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This document analyzes options for adding asynchronous API support to @photostructure/sqlite(currently sync-only, matching Node.js's built-in sqlite module). We recommend a separate package for the async API rather than integrating it into the existing library.
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## Current State
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## Conclusion
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Creating a separate async package is the recommended approach. It provides the clearest path forward, aligns with Node.js's design philosophy, and minimizes risk to existing users. The AsyncWorker pattern from node-addon-api provides a solid foundation for implementation.
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A separate async package is the recommended approach. It follows Node.js's own design philosophy and avoids any risk to existing sync users. The AsyncWorker pattern from node-addon-api is the right building block.
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Information about the development of @photostructure/sqlite.
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## Project Timeline
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## Project overview
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This project demonstrates modern software development practices with AI assistance:
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- Full API compliance running in both ESM and CJS modes
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- Multi-platform CI/CD with dedicated ARM64 and x64 build jobs across all platforms
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- Security scanning and memory leak detection
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- Automated sync from Node.js and SQLite upstream
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-[Benchmarking suite](../../benchmark/README.md) covering popular Node.js SQLite libraries
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-**900+ lines of C++** - Core SQLite binding implementation
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-**17,000+ lines of TypeScript tests** - Comprehensive test coverage
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-**400+ tests** with full API compliance running in both ESM and CJS modes
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-**Multi-platform CI/CD** with dedicated ARM64 and x64 build jobs across all platforms
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-**Security scanning** and memory leak detection
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-**Automated sync** from Node.js and SQLite upstream
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-**Robust [benchmarking suite](../../benchmark/README.md)** including all popular Node.js SQLite libraries
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## AI-Assisted Development
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## AI-assisted development
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This project was built with substantial assistance from [Claude Code](https://claude.ai/referral/gM3vgw7pfA), an AI coding assistant.
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### Development Cost
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-**API usage**: ~$1400 in Claude API tokens
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-**Actual cost**: $200/month MAX 20x plan subscription
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-**Time saved**: At least a month of setup, analysis, porting and testing
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### Development process
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### Development Process
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1.**Initial Analysis**: Claude analyzed the Node.js SQLite source code and architecture
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2.**Shim Layer Design**: Developed compatibility layer for Node.js internals
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1.**Analysis**: Claude analyzed the Node.js SQLite source code and architecture
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2.**Shim layer**: Developed compatibility layer for Node.js internals
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3.**Implementation**: Ported C++ code with N-API adaptations
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4.**Testing**: Created comprehensive test suite with 400+ tests
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4.**Testing**: Created test suite
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5.**Documentation**: Generated user and API documentation
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6.**CI/CD**: Set up multi-platform build and release pipeline
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### Quality Assurance
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### Quality assurance
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While AI significantly accelerated development, all code underwent:
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All code was reviewed by a human and validated by automated tests before merging:
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- Human review before merging
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- Comprehensive automated testing
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- Automated testing across platforms
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- Memory leak detection (Valgrind, ASAN)
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- Security scanning (npm audit, OSV, CodeQL)
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- Performance benchmarking
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This approach demonstrates how AI-assisted development can accelerate complex system programming while maintaining high code quality through comprehensive testing and human oversight.
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## Building from Source
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## Building from source
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### Prerequisites
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-**macOS**: Xcode Command Line Tools
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-**Windows**: Visual Studio 2019+
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### Build Commands
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### Build commands
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```bash
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# Install dependencies
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npm run benchmark
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```
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### Development Workflow
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### Development workflow
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```bash
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# Watch mode for TypeScript
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5. Ensure all tests pass
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6. Submit a pull request
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### Code Style
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### Code style
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- TypeScript/JavaScript: Prettier with project config
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- C++: clang-format with project style
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- Commit messages: Conventional Commits format
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### Testing Requirements
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### Testing requirements
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- New features must include tests
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- Tests must pass on all platforms
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- Memory leak tests for native code
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- Benchmark comparisons for performance changes
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## Release Process
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## Release process
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See [Release Process](./release-process.md) for detailed release instructions.
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## Upstream Synchronization
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## Upstream synchronization
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The project maintains synchronization with:
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- Node.js SQLite implementation
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- SQLite amalgamation source
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### GitHub API Authentication
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### GitHub API authentication
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To avoid rate limiting when syncing from GitHub (60 requests/hour for unauthenticated requests), set up authentication:
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The token only needs public repository read access.
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