tegwick
ccbca967c8
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Major Features: - Implement comprehensive validation error reporting system (Issue #8) - Add direct CLI access with 'markitect' command - Create extensive makefile targets for CLI usage - Enhance schema validation with detailed error collection Components Added: - markitect/validation_error.py: ValidationError system with 8 error types - Enhanced markitect/schema_validator.py: Detailed error reporting methods - markitect/cli.py: Enhanced with --detailed-errors and --error-format options - visualize_schema.py: Schema visualization with ASCII and colorful modes - Comprehensive test suite for validation error reporting CLI Enhancements: - Direct 'markitect' command access for all operations - Makefile targets for typical CLI usage (cli-help, cli-ingest, etc.) - Support for text, JSON, and markdown error output formats - Backward compatibility with existing validation functionality Testing: - 11 comprehensive tests for Issue #8 validation error reporting - Tests for schema validation, visualization, and CLI integration - 100% test coverage for validation error scenarios 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
27 lines
1.1 KiB
Python
27 lines
1.1 KiB
Python
from markdown_it import MarkdownIt
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def parse_markdown_to_ast(md_content: str):
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# Enable table parsing and other common plugins
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md = MarkdownIt("commonmark", {"tables": True}).enable(['table'])
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tokens = md.parse(md_content)
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# Convert to a JSON-serializable list of dicts (tokens are objects, so we dict-ify them recursively)
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def token_to_dict(token):
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d = {
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'type': token.type,
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'tag': token.tag,
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'attrs': token.attrs,
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'map': token.map,
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'nesting': token.nesting,
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'level': token.level,
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'children': [token_to_dict(child) if child else None for child in token.children] if token.children else None,
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'content': token.content,
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'markup': token.markup,
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'info': token.info,
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'meta': token.meta,
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'block': token.block,
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'hidden': token.hidden
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}
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return {k: v for k, v in d.items() if v is not None} # Remove None values for cleanliness
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return [token_to_dict(token) for token in tokens]
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