121 lines
3.5 KiB
Python
Executable File
121 lines
3.5 KiB
Python
Executable File
#!/usr/bin/env python3
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"""
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data.transform - Transform data between different formats (JSON, YAML, XML, CSV) with validation and error handling
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Generated by meta.skill
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"""
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import os
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import sys
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import json
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import yaml
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from pathlib import Path
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from typing import Dict, List, Any, Optional
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from betty.config import BASE_DIR
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from betty.logging_utils import setup_logger
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logger = setup_logger(__name__)
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class DataTransform:
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"""
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Transform data between different formats (JSON, YAML, XML, CSV) with validation and error handling
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"""
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def __init__(self, base_dir: str = BASE_DIR):
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"""Initialize skill"""
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self.base_dir = Path(base_dir)
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def execute(self, input_file_path: Optional[str] = None, source_format: Optional[str] = None, target_format: Optional[str] = None, schema_path_optional: Optional[str] = None) -> Dict[str, Any]:
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"""
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Execute the skill
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Returns:
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Dict with execution results
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"""
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try:
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logger.info("Executing data.transform...")
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# TODO: Implement skill logic here
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# Implementation notes:
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# Support transformations between: - JSON ↔ YAML - JSON ↔ XML - JSON ↔ CSV - YAML ↔ XML - XML ↔ CSV Features: - Validate input against schema before transformation - Preserve data types during conversion - Handle nested structures appropriately - Report data loss warnings (e.g., CSV can't represent nesting) - Support custom transformation rules - Provide detailed error messages Output report should include: - Transformation success status - Source and target formats - Data validation results - Warnings about potential data loss - Transformation time and file sizes
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# Placeholder implementation
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result = {
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"ok": True,
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"status": "success",
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"message": "Skill executed successfully"
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}
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logger.info("Skill completed successfully")
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return result
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except Exception as e:
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logger.error(f"Error executing skill: {e}")
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return {
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"ok": False,
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"status": "failed",
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"error": str(e)
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}
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def main():
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"""CLI entry point"""
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import argparse
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parser = argparse.ArgumentParser(
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description="Transform data between different formats (JSON, YAML, XML, CSV) with validation and error handling"
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)
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parser.add_argument(
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"--input-file-path",
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help="input_file_path"
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)
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parser.add_argument(
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"--source-format",
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help="source_format"
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)
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parser.add_argument(
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"--target-format",
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help="target_format"
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)
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parser.add_argument(
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"--schema-path-optional",
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help="schema_path (optional)"
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)
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parser.add_argument(
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"--output-format",
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choices=["json", "yaml"],
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default="json",
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help="Output format"
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)
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args = parser.parse_args()
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# Create skill instance
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skill = DataTransform()
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# Execute skill
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result = skill.execute(
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input_file_path=args.input_file_path,
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source_format=args.source_format,
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target_format=args.target_format,
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schema_path_optional=args.schema_path_optional,
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)
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# Output result
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if args.output_format == "json":
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print(json.dumps(result, indent=2))
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else:
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print(yaml.dump(result, default_flow_style=False))
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# Exit with appropriate code
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sys.exit(0 if result.get("ok") else 1)
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if __name__ == "__main__":
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main()
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