Skill 详情
ifc-data-extraction
Extracts BIM data from IFC construction models.
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SKILL.md
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---
name: "ifc-data-extraction"
description: "Extract structured data from IFC (Industry Foundation Classes) files using IfcOpenShell. Parse BIM models, extract quantities, properties, spatial relationships, and export to various formats."
homepage: "https://datadrivenconstruction.io"
metadata: {"openclaw":{"emoji":"🏢","os":["darwin","linux","win32"],"homepage":"https://datadrivenconstruction.io","requires":{"bins":["python3"],"anyBins":["ifcopenshell","IfcConvert"]}}}
---
# IFC Data Extraction
## Overview
This skill provides comprehensive IFC file parsing and data extraction using IfcOpenShell. Extract element data, quantities, properties, and relationships from BIM models for analysis and reporting.
**Based on Open BIM Standards** - Working with vendor-neutral IFC format for maximum interoperability.
> "IFC является открытым стандартом для обмена BIM-данными, позволяющим извлекать информацию независимо от программного обеспечения."
> — DDC Methodology
## Quick Start
```python
import ifcopenshell
import ifcopenshell.util.element as element_util
import pandas as pd
# Open IFC file
ifc = ifcopenshell.open("model.ifc")
# Get project info
project = ifc.by_type("IfcProject")[0]
print(f"Project: {project.Name}")
# Extract all walls
walls = ifc.by_type("IfcWall")
print(f"Total walls: {len(walls)}")
# Get wall data
wall_data = []
for wall in walls:
psets = element_util.get_psets(wall)
wall_data.append({
'GlobalId': wall.GlobalId,
'Name': wall.Name,
'Type': wall.is_a(),
'Level': get_level(wall),
'Properties': psets
})
df = pd.DataFrame(wall_data)
print(df.head())
```
## Core Extraction Functions
### Element Extractor Class
```python
import ifcopenshell
import ifcopenshell.util.element as element_util
import ifcopenshell.util.placement as placement_util
import ifcopenshell.geom
import pandas as pd
from typing import List, Dict, Optional, Any
class IFCExtractor:
"""Extract data from IFC files"""
def __init__(self, ifc_path: str):
self.model = ifcopenshell.open(ifc_path)
self.settings = ifcopenshell.geom.settings()
def get_project_info(self) -> Dict:
"""Extract project metadata"""
project = self.model.by_type("IfcProject")[0]
site = self.model.by_type("IfcSite")
building = self.model.by_type("IfcBuilding")
return {
'project_id': project.GlobalId,
'project_name': project.Name,
'description': project.Description,
'site_count': len(site),
'building_count': len(building),
'schema': self.model.schema
}
def get_all_elements(self, element_types: List[str] = None) -> pd.DataFrame:
"""Extract all elements of specified types"""
if element_types is None:
element_types = [
'IfcWall', 'IfcSlab', 'IfcColumn', 'IfcBeam',
'IfcDoor', 'IfcWindow', 'IfcStair', 'IfcRoof'
]
all_elements = []
for ifc_type in element_types:
elements = self.model.by_type(ifc_type)
for elem in elements:
data = self._extract_element_data(elem)
data['IFC_Type'] = ifc_type
all_elements.append(data)
return pd.DataFrame(all_elements)
def _extract_element_data(self, element) -> Dict:
"""Extract data from single element"""
# Basic info
data = {
'GlobalId': element.GlobalId,
'Name': element.Name,
'Description': element.Description,
'ObjectType': element.ObjectType if hasattr(element, 'ObjectType') else None
}
# Get level/storey
data['Level'] = self._get_element_level(element)
# Get material
data['Material'] = self._get_element_material(element)
# Get type
data['TypeName'] = self._get_element_type(element)
# Get all property sets
psets = element_ut在 GitHub 阅读完整来源 (打开外部页面)