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markitect-main/markitect/database.py

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feat: Implement Issue #1 - Database initialization and front matter parsing Complete TDD implementation of core MarkiTect functionality: **Database Module (markitect/database.py):** - DatabaseManager class with SQLite database initialization - markdown_files table with proper schema (id, filename, front_matter, content, created_at) - Front matter storage as JSON with content separation - File storage, retrieval, and listing methods - Comprehensive error handling **Front Matter Module (markitect/frontmatter.py):** - FrontMatterParser class with YAML front matter parsing - Clean separation of metadata from markdown content - Graceful handling of invalid YAML and missing front matter - Regex-based parsing with proper delimiter handling **Dependencies:** - Added PyYAML for front matter parsing - Updated pyproject.toml with new dependency **Test Coverage:** - 9 comprehensive tests covering all functionality - Database initialization and schema validation - Front matter parsing with Issue #1 example content - Integrated workflow testing (storage/retrieval) - Error handling for edge cases **TDD Process:** - RED phase: 8 failing tests defining requirements - GREEN phase: Minimal implementation making all tests pass - Validation: Complete workflow verified with example content This implementation provides the foundation for all subsequent MarkiTect features, handling the exact example from Issue #1 specification. Issue #1: Initialize Database and Store Example Markdown File https://gitea.coulomb.social/coulomb/markitect_project/issues/1 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-09-23 04:28:29 +02:00
"""
feat(spaces): implement Phase 0-1 of Information Space Service Phase 0 - Project Organization: - Create docs/PROJECT_STRUCTURE.md documenting codebase layout - Create markitect/core/ with parser, serializer, document_manager, workspace - Create markitect/schema/ consolidating 6 schema_*.py modules - Create markitect/storage/ with database module - Maintain backward compatibility via re-exports from original locations - Add docs/roadmap/information-space-service/ with README and WORKPLAN Phase 1 - Foundation (Weeks 1-3): - Week 1: Core domain models (InformationSpace, SpaceDocument, SpaceConfig, SpaceMetadata, SpaceVariable, TransclusionReference, SpaceStatus) - Week 2: Repository layer with interfaces (ISpaceRepository, IDocumentAssociationRepository, IVariableRepository, IReferenceRepository) and SQLite implementations with foreign key cascade deletes - Week 3: SpaceService orchestration layer with full CRUD, document, variable, and reference tracking operations Test coverage: 124 tests (25 model + 63 repository + 36 integration) Capabilities delivered: - CAP-001: InformationSpace entity with lifecycle management - CAP-002: SpaceRepository CRUD with SQLite backing - CAP-003: Document-Space associations with path-based organization - CAP-004: Space metadata and configuration schemas - CAP-005: Database schema with migrations Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-02-08 02:02:46 +01:00
Database management - Backward Compatibility Module.
feat: Implement Issue #1 - Database initialization and front matter parsing Complete TDD implementation of core MarkiTect functionality: **Database Module (markitect/database.py):** - DatabaseManager class with SQLite database initialization - markdown_files table with proper schema (id, filename, front_matter, content, created_at) - Front matter storage as JSON with content separation - File storage, retrieval, and listing methods - Comprehensive error handling **Front Matter Module (markitect/frontmatter.py):** - FrontMatterParser class with YAML front matter parsing - Clean separation of metadata from markdown content - Graceful handling of invalid YAML and missing front matter - Regex-based parsing with proper delimiter handling **Dependencies:** - Added PyYAML for front matter parsing - Updated pyproject.toml with new dependency **Test Coverage:** - 9 comprehensive tests covering all functionality - Database initialization and schema validation - Front matter parsing with Issue #1 example content - Integrated workflow testing (storage/retrieval) - Error handling for edge cases **TDD Process:** - RED phase: 8 failing tests defining requirements - GREEN phase: Minimal implementation making all tests pass - Validation: Complete workflow verified with example content This implementation provides the foundation for all subsequent MarkiTect features, handling the exact example from Issue #1 specification. Issue #1: Initialize Database and Store Example Markdown File https://gitea.coulomb.social/coulomb/markitect_project/issues/1 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-09-23 04:28:29 +02:00
feat(spaces): implement Phase 0-1 of Information Space Service Phase 0 - Project Organization: - Create docs/PROJECT_STRUCTURE.md documenting codebase layout - Create markitect/core/ with parser, serializer, document_manager, workspace - Create markitect/schema/ consolidating 6 schema_*.py modules - Create markitect/storage/ with database module - Maintain backward compatibility via re-exports from original locations - Add docs/roadmap/information-space-service/ with README and WORKPLAN Phase 1 - Foundation (Weeks 1-3): - Week 1: Core domain models (InformationSpace, SpaceDocument, SpaceConfig, SpaceMetadata, SpaceVariable, TransclusionReference, SpaceStatus) - Week 2: Repository layer with interfaces (ISpaceRepository, IDocumentAssociationRepository, IVariableRepository, IReferenceRepository) and SQLite implementations with foreign key cascade deletes - Week 3: SpaceService orchestration layer with full CRUD, document, variable, and reference tracking operations Test coverage: 124 tests (25 model + 63 repository + 36 integration) Capabilities delivered: - CAP-001: InformationSpace entity with lifecycle management - CAP-002: SpaceRepository CRUD with SQLite backing - CAP-003: Document-Space associations with path-based organization - CAP-004: Space metadata and configuration schemas - CAP-005: Database schema with migrations Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-02-08 02:02:46 +01:00
This module re-exports from markitect.storage.database for backward compatibility.
New code should import from markitect.storage.database directly.
feat: Implement Issue #1 - Database initialization and front matter parsing Complete TDD implementation of core MarkiTect functionality: **Database Module (markitect/database.py):** - DatabaseManager class with SQLite database initialization - markdown_files table with proper schema (id, filename, front_matter, content, created_at) - Front matter storage as JSON with content separation - File storage, retrieval, and listing methods - Comprehensive error handling **Front Matter Module (markitect/frontmatter.py):** - FrontMatterParser class with YAML front matter parsing - Clean separation of metadata from markdown content - Graceful handling of invalid YAML and missing front matter - Regex-based parsing with proper delimiter handling **Dependencies:** - Added PyYAML for front matter parsing - Updated pyproject.toml with new dependency **Test Coverage:** - 9 comprehensive tests covering all functionality - Database initialization and schema validation - Front matter parsing with Issue #1 example content - Integrated workflow testing (storage/retrieval) - Error handling for edge cases **TDD Process:** - RED phase: 8 failing tests defining requirements - GREEN phase: Minimal implementation making all tests pass - Validation: Complete workflow verified with example content This implementation provides the foundation for all subsequent MarkiTect features, handling the exact example from Issue #1 specification. Issue #1: Initialize Database and Store Example Markdown File https://gitea.coulomb.social/coulomb/markitect_project/issues/1 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-09-23 04:28:29 +02:00
"""
feat(spaces): implement Phase 0-1 of Information Space Service Phase 0 - Project Organization: - Create docs/PROJECT_STRUCTURE.md documenting codebase layout - Create markitect/core/ with parser, serializer, document_manager, workspace - Create markitect/schema/ consolidating 6 schema_*.py modules - Create markitect/storage/ with database module - Maintain backward compatibility via re-exports from original locations - Add docs/roadmap/information-space-service/ with README and WORKPLAN Phase 1 - Foundation (Weeks 1-3): - Week 1: Core domain models (InformationSpace, SpaceDocument, SpaceConfig, SpaceMetadata, SpaceVariable, TransclusionReference, SpaceStatus) - Week 2: Repository layer with interfaces (ISpaceRepository, IDocumentAssociationRepository, IVariableRepository, IReferenceRepository) and SQLite implementations with foreign key cascade deletes - Week 3: SpaceService orchestration layer with full CRUD, document, variable, and reference tracking operations Test coverage: 124 tests (25 model + 63 repository + 36 integration) Capabilities delivered: - CAP-001: InformationSpace entity with lifecycle management - CAP-002: SpaceRepository CRUD with SQLite backing - CAP-003: Document-Space associations with path-based organization - CAP-004: Space metadata and configuration schemas - CAP-005: Database schema with migrations Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-02-08 02:02:46 +01:00
# Re-export from storage package for backward compatibility
from markitect.storage.database import DatabaseManager
feat: Implement Issue #1 - Database initialization and front matter parsing Complete TDD implementation of core MarkiTect functionality: **Database Module (markitect/database.py):** - DatabaseManager class with SQLite database initialization - markdown_files table with proper schema (id, filename, front_matter, content, created_at) - Front matter storage as JSON with content separation - File storage, retrieval, and listing methods - Comprehensive error handling **Front Matter Module (markitect/frontmatter.py):** - FrontMatterParser class with YAML front matter parsing - Clean separation of metadata from markdown content - Graceful handling of invalid YAML and missing front matter - Regex-based parsing with proper delimiter handling **Dependencies:** - Added PyYAML for front matter parsing - Updated pyproject.toml with new dependency **Test Coverage:** - 9 comprehensive tests covering all functionality - Database initialization and schema validation - Front matter parsing with Issue #1 example content - Integrated workflow testing (storage/retrieval) - Error handling for edge cases **TDD Process:** - RED phase: 8 failing tests defining requirements - GREEN phase: Minimal implementation making all tests pass - Validation: Complete workflow verified with example content This implementation provides the foundation for all subsequent MarkiTect features, handling the exact example from Issue #1 specification. Issue #1: Initialize Database and Store Example Markdown File https://gitea.coulomb.social/coulomb/markitect_project/issues/1 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-09-23 04:28:29 +02:00
feat(spaces): implement Phase 0-1 of Information Space Service Phase 0 - Project Organization: - Create docs/PROJECT_STRUCTURE.md documenting codebase layout - Create markitect/core/ with parser, serializer, document_manager, workspace - Create markitect/schema/ consolidating 6 schema_*.py modules - Create markitect/storage/ with database module - Maintain backward compatibility via re-exports from original locations - Add docs/roadmap/information-space-service/ with README and WORKPLAN Phase 1 - Foundation (Weeks 1-3): - Week 1: Core domain models (InformationSpace, SpaceDocument, SpaceConfig, SpaceMetadata, SpaceVariable, TransclusionReference, SpaceStatus) - Week 2: Repository layer with interfaces (ISpaceRepository, IDocumentAssociationRepository, IVariableRepository, IReferenceRepository) and SQLite implementations with foreign key cascade deletes - Week 3: SpaceService orchestration layer with full CRUD, document, variable, and reference tracking operations Test coverage: 124 tests (25 model + 63 repository + 36 integration) Capabilities delivered: - CAP-001: InformationSpace entity with lifecycle management - CAP-002: SpaceRepository CRUD with SQLite backing - CAP-003: Document-Space associations with path-based organization - CAP-004: Space metadata and configuration schemas - CAP-005: Database schema with migrations Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-02-08 02:02:46 +01:00
__all__ = ['DatabaseManager']
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