Feature/schema soft validation

CHANGELOG.md

@@ -23,6 +23,17 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 - feat(schema): Add ResultMerger class for combining phase results while maintaining output format consistency
 - feat(schema): Comprehensive logging system for debugging two-phase execution with timing and rule counts
 - feat(schema): Intelligent rule separation - automatically separate SCHEMA rules from other rule types for phased execution
+- **feat(schema): Implement desired_type soft validation with compatibility analysis and rule generation**
+- feat(schema): Add desired_type parsing support with extended TypeParser for complex type definitions
+- feat(schema): Implement CompatibilityAnalyzer for intelligent type conversion analysis (COMPATIBLE/INCOMPATIBLE/CONFLICTING)
+- feat(schema): Add DesiredTypeRuleGenerator for automatic validation rule creation based on compatibility analysis
+- feat(schema): Generate LENGTH rules for precision/length reduction scenarios in type conversions
+- feat(schema): Generate REGEX rules for string-to-numeric type conversion validation
+- feat(schema): Generate DATE_FORMAT rules for date validation (MySQL support)
+- feat(schema): Enhanced result merging with desired_type validation results integration
+- feat(schema): Updated JSON and table output formats to display desired_type validation status
+- feat(schema): Comprehensive error handling with clear distinction between schema vs desired_type failures
+- feat(tests): Complete test coverage for desired_type validation including compatibility analysis and rule generation
 
 ### Changed
 - enhance(cli): Updated schema command to support both syntactic sugar and detailed JSON type definitions
@@ -32,23 +43,40 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 - refactor(schema): Added `_decompose_schema_payload_atomic()` for backward compatibility with single-list return format
 - refactor(tests): Updated all schema-related test mocks to handle new tuple return format from rule decomposition
 - improve(architecture): All validation maintains identical output format and behavior - no user-visible changes
+- **enhance(schema): Extended two-phase execution framework with actual desired_type validation implementation**
+- enhance(schema): DesiredTypePhaseExecutor now performs actual compatibility analysis and rule generation (no longer skip-only)
+- enhance(schema): Enhanced type parser with full desired_type syntax support including complex type definitions
+- enhance(validation): Intelligent compatibility matrix ensures optimal validation performance by skipping unnecessary checks
+- enhance(output): Merged validation results clearly distinguish between schema structure validation and desired_type compatibility validation
 
 ### Fixed
 - **fix(async): Resolved RuntimeError event loop management issue in two-phase execution**
 - fix(async): Consolidated both validation phases into single event loop to prevent database connection pool conflicts
 - fix(async): Eliminated multiple `asyncio.run()` calls that caused "Event loop is closed" errors in production
 - fix(tests): Updated test contracts and mocks to work with new two-phase execution architecture
+- **fix(sqlite): Implemented custom functions to solve SQLite regex compatibility limitations**
+- fix(sqlite): Created comprehensive SQLite custom validation functions for precision and length validation
+- fix(sqlite): Added `DETECT_INVALID_INTEGER_DIGITS`, `DETECT_INVALID_STRING_LENGTH`, `DETECT_INVALID_FLOAT_PRECISION` functions
+- fix(sqlite): Automatic registration of custom functions via SQLAlchemy event listeners on connection establishment
+- fix(database): Enhanced database dialect to intelligently use custom functions for SQLite regex replacement
+- fix(validation): Seamless fallback from regex patterns to custom function calls for incompatible databases
 
 ### Removed
 - None
 
 ### Architecture Notes
-- **Two-Phase Execution Framework**: Implemented foundation for future desired_type compatibility analysis
+- **Two-Phase Execution Framework**: Complete implementation with desired_type soft validation capabilities
 - **Phase 1**: Schema rules execute first to collect native type information and validate table/column existence
-- **Phase 2**: Additional rules execute with intelligent filtering based on schema analysis results (skip semantics)
+- **Phase 2**: Desired_type compatibility analysis with automatic rule generation for incompatible type conversions
+- **Compatibility Analysis**: Intelligent type conversion analysis (COMPATIBLE/INCOMPATIBLE/CONFLICTING) optimizes validation performance
+- **Rule Generation**: Automatic LENGTH, REGEX, and DATE_FORMAT rule creation based on compatibility analysis results
 - **Skip Logic**: Rules targeting missing tables/columns are automatically skipped to prevent cascading failures
-- **Result Merging**: Synthetic results created for skipped rules to maintain consistent output format
+- **Result Merging**: Unified results combining schema validation and desired_type validation with clear error distinction
 - **Performance**: Current implementation optimizes for stability over concurrency - both phases execute serially within single event loop
+- **Database Support**: DATE_FORMAT validation currently supports MySQL with planned SQLite/PostgreSQL support in Phase 4
+- **SQLite Regex Compatibility**: Custom function implementation (`shared/database/sqlite_functions.py`) provides seamless regex replacement for SQLite databases that lack native regex support
+- **Custom Function Architecture**: Automatic registration of `DETECT_INVALID_INTEGER_DIGITS`, `DETECT_INVALID_STRING_LENGTH`, and `DETECT_INVALID_FLOAT_PRECISION` functions via SQLAlchemy event listeners
+- **Intelligent Fallback**: Database dialect automatically detects SQLite and converts regex patterns to equivalent custom function calls for precision/length validation
 
 ## [0.4.3] - 2025-09-06