Anto01
aa3dafbe4b
- Set up Python package structure with pyproject.toml - Created MCP server, optimization engine, and NX journals modules - Added configuration templates - Implemented pluggable result extractor architecture - Comprehensive README with architecture overview - Project ready for GitHub push 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
67 lines
1.8 KiB
Python
67 lines
1.8 KiB
Python
"""
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Pluggable Result Extractor System
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Base classes and implementations for extracting metrics from FEA results.
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"""
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from abc import ABC, abstractmethod
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from typing import Dict, Any, Optional
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from pathlib import Path
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class ResultExtractor(ABC):
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"""Base class for all result extractors."""
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@abstractmethod
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def extract(self, result_files: Dict[str, Path], config: Dict[str, Any]) -> Dict[str, float]:
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"""
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Extract metrics from FEA results.
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Args:
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result_files: Dictionary mapping file types to paths (e.g., {'op2': Path(...), 'f06': Path(...)})
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config: Extractor-specific configuration parameters
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Returns:
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Dictionary mapping metric names to values
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"""
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pass
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@property
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@abstractmethod
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def required_files(self) -> list[str]:
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"""List of required file types (e.g., ['op2'], ['f06'], etc.)."""
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pass
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@property
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def name(self) -> str:
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"""Extractor name for registration."""
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return self.__class__.__name__.replace("Extractor", "").lower()
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# Registry of available extractors
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_EXTRACTOR_REGISTRY: Dict[str, type[ResultExtractor]] = {}
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def register_extractor(extractor_class: type[ResultExtractor]) -> type[ResultExtractor]:
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"""Decorator to register an extractor."""
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_EXTRACTOR_REGISTRY[extractor_class().name] = extractor_class
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return extractor_class
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def get_extractor(name: str) -> Optional[type[ResultExtractor]]:
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"""Get extractor class by name."""
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return _EXTRACTOR_REGISTRY.get(name)
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def list_extractors() -> list[str]:
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"""List all registered extractor names."""
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return list(_EXTRACTOR_REGISTRY.keys())
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__all__ = [
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"ResultExtractor",
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"register_extractor",
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"get_extractor",
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"list_extractors",
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]
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