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DazzleLib Roadmap

Library roadmap and planned features

Current Status (2025)

✅ Stable Libraries

dazzle-filekit

Status: Stable, published on PyPI

Cross-platform file operations with verification and metadata preservation.

  • ✅ File copy/move with metadata preservation
  • ✅ Hash calculation (MD5, SHA1, SHA256, SHA512)
  • ✅ Directory comparison and synchronization
  • ✅ Cross-platform path handling
  • ✅ Windows UNC path support (optional)

Install: pip install dazzle-filekit

dazzle-tree-lib

Status: Stable, published on PyPI

Tree structure utilities for hierarchical data.

  • ✅ Generic tree data structures
  • ✅ Traversal algorithms (DFS, BFS, iterative)
  • ✅ Tree visualization and pretty-printing
  • ✅ Path operations on trees
  • ✅ Node manipulation and queries

Install: pip install dazzle-tree-lib

UNCtools

Status: Stable, published on PyPI

Windows UNC path handling and network drive utilities.

  • ✅ UNC path parsing and validation
  • ✅ Network drive detection
  • ✅ Drive letter to UNC conversion
  • ✅ Long path support (>260 characters)
  • ✅ Cross-platform safety (no-op on Unix)
  • ✅ Moving repository to DazzleLib organization
  • ✅ PyPI publication under DazzleLib

Planned Install: pip install unctools

🚧 In Progress

  • Dazzle-Tree-Lib is currently receiving more testing and development

Planned Libraries

New libraries are added based on common patterns identified across Dazzle tools. Each planned library addresses recurring needs in the ecosystem.

dazzle-config-lib

Configuration file handling (YAML, TOML, JSON)

Problem: Every tool needs to load/save configuration, but handling different formats with validation is repetitive.

Planned Features:

  • Unified API for YAML, TOML, JSON config files
  • Schema validation with helpful error messages
  • Environment variable interpolation
  • Configuration merging (defaults + user config)
  • Type-safe configuration classes
  • Migration utilities for config format changes

Use Cases:

  • Application settings files
  • Tool configuration
  • Project configuration
  • Environment-specific configs

Status: Research phase

dazzle-cli-lib

Command-line interface building blocks

Problem: Building robust CLIs requires argument parsing, help text, subcommands, and consistent error handling.

Planned Features:

  • Enhanced argument parsing (builds on argparse)
  • Automatic help generation from docstrings
  • Subcommand management
  • Progress bars and status updates
  • Interactive prompts with validation
  • Colorized output (with fallbacks)
  • Shell completion generation

Use Cases:

  • DazzleTools command-line applications
  • Script argument handling
  • Interactive utilities

Status: Research phase

dazzle-log-lib

Structured logging utilities

Problem: Consistent, structured logging across tools is helpful for debugging and monitoring.

Planned Features:

  • Structured logging (JSON/text formats)
  • Log level configuration
  • Contextual logging (request IDs, user context)
  • Log rotation and archival
  • Performance-optimized logging
  • Integration with monitoring tools

Use Cases:

  • Application logging
  • Debugging complex operations
  • Audit trails
  • Performance monitoring

Status: Research phase

dazzle-test-lib

Testing utilities and fixtures

Problem: Writing tests for file operations, CLI tools, and cross-platform code requires common test utilities.

Planned Features:

  • Temporary directory fixtures
  • Mock file systems
  • Test data generators
  • Cross-platform test helpers
  • Performance benchmarking utilities
  • Integration test helpers

Use Cases:

  • Testing DazzleTools
  • Testing file operations
  • Cross-platform test coverage
  • Regression testing

Status: Research phase

Feature Roadmap for Existing Libraries

dazzle-filekit

Near-term (2025 Q2-Q3)

  • Enhanced directory synchronization with conflict resolution strategies
  • Parallel file operations for large directories
  • Incremental backup support
  • File deduplication utilities

Long-term (2025 Q4+)

  • Cloud storage integration (S3, Azure Blob, GCS)
  • Compression utilities (zip, tar, 7z)
  • File watch/monitor capabilities
  • Advanced metadata preservation (extended attributes, ACLs)

dazzle-tree-lib

Near-term (2025 Q2-Q3)

  • Tree serialization formats (JSON, YAML)
  • Tree diffing and merging
  • Performance optimizations for large trees
  • Additional traversal strategies

Long-term (2025 Q4+)

  • Database-backed trees for very large hierarchies
  • Concurrent tree modifications
  • Tree visualization export (GraphViz, Mermaid)
  • Tree transformation utilities

UNCtools

Near-term (2025 Q2-Q3)

  • Complete migration to DazzleLib organization
  • PyPI publication
  • Enhanced network drive utilities
  • Share access permission queries

Long-term (2025 Q4+)

  • Network path availability checking
  • SMB protocol integration
  • Network drive mounting/unmounting utilities

How New Libraries Are Chosen

DazzleLib follows a needs-driven approach for new libraries:

1. Pattern Recognition

When we see the same code patterns across 3+ DazzleTools, we extract them into a library.

2. Community Requests

Feature requests and discussions help identify gaps in the ecosystem.

3. Architectural Fit

New libraries must fit DazzleLib's philosophy:

  • Composable and focused
  • Cross-platform by default
  • Minimal dependencies
  • MIT licensed

4. Maintenance Capacity

We only add libraries we can properly maintain and support.

Library Lifecycle

1. Research Phase

  • Identify common patterns
  • Design API
  • Review similar libraries
  • Validate use cases

2. Alpha Release

  • Initial implementation
  • Basic tests
  • Documentation
  • Private testing

3. Beta Release

  • Public testing
  • Gather feedback
  • API refinement
  • Documentation improvements

4. Stable Release

  • 1.0.0 release on PyPI
  • Full documentation
  • Comprehensive tests (80%+ coverage)
  • Commitment to semantic versioning

5. Maintenance

  • Bug fixes
  • Performance improvements
  • Feature additions (minor versions)
  • Security updates

Contributing to the Roadmap

Have ideas for new libraries or features? We'd love to hear them!

How to Suggest a Library

  1. Check existing discussions: Search GitHub Discussions
  2. Describe the problem: What problem does this library solve?
  3. Show examples: Provide code examples of how it would be used
  4. Identify patterns: Where do you see this pattern repeating?
  5. Consider alternatives: Why not use an existing library?

Feature Requests for Existing Libraries

  1. Use repository-specific issues: File issues in the library's repository
  2. Describe the use case: What are you trying to accomplish?
  3. Provide examples: Show what the API might look like
  4. Consider cross-platform impact: Will this work on all platforms?

Roadmap Updates

This roadmap is updated quarterly based on:

  • Community feedback
  • DazzleTools development needs
  • Industry trends
  • Available maintenance capacity

Last Updated: November 2025

Next Review: Jan 2026

Sponsorship Impact on Roadmap

Sponsorship directly influences development priorities:

  • $25/month: Vote on library priorities
  • $100/month: Influence feature roadmap
  • $500/month: Priority support for requested features
  • $1000/month: Dedicated development time for custom libraries

Sponsor DazzleProj on GitHub

Part of DazzleProj - The Dazzle Ecosystem