Convert CAD/BIM files to structured data. Extract element data from Revit, IFC, DWG, DGN files.
npx skills add https://github.com/datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction --skill cad-to-data
Based on DDC methodology (Chapter 2.4), this skill converts CAD and BIM files to structured data, extracting element properties, quantities, and relationships from Revit, IFC, DWG, and DGN files.
Book Reference: "Преобразование данных в структурированную форму" / "Data Transformation to Structured Form"
from dataclasses import dataclass, field
from enum import Enum
from typing import List, Dict, Optional, Any, Tuple, Generator
from datetime import datetime
import json
class CADFormat(Enum):
"""Supported CAD/BIM formats"""
IFC = "ifc"
RVT = "rvt"
DWG = "dwg"
DXF = "dxf"
DGN = "dgn"
NWD = "nwd"
STEP = "step"
class ElementCategory(Enum):
"""BIM element categories"""
WALL = "wall"
FLOOR = "floor"
ROOF = "roof"
CEILING = "ceiling"
DOOR = "door"
WINDOW = "window"
COLUMN = "column"
BEAM = "beam"
STAIR = "stair"
RAMP = "ramp"
FURNITURE = "furniture"
EQUIPMENT = "equipment"
PIPE = "pipe"
DUCT = "duct"
CABLE_TRAY = "cable_tray"
SPACE = "space"
GENERIC = "generic"
@dataclass
class Point3D:
"""3D point"""
x: float
y: float
z: float
@dataclass
class BoundingBox3D:
"""3D bounding box"""
min_point: Point3D
max_point: Point3D
@property
def width(self) -> float:
return abs(self.max_point.x - self.min_point.x)
@property
def depth(self) -> float:
return abs(self.max_point.y - self.min_point.y)
@property
def height(self) -> float:
return abs(self.max_point.z - self.min_point.z)
@property
def volume(self) -> float:
return self.width * self.depth * self.height
@dataclass
class MaterialInfo:
"""Material information"""
name: str
category: str
color: Optional[str] = None
area: float = 0.0
volume: float = 0.0
properties: Dict[str, Any] = field(default_factory=dict)
@dataclass
class CADElement:
"""Extracted CAD/BIM element"""
id: str
guid: str
name: str
category: ElementCategory
type_name: str
level: Optional[str] = None
bounding_box: Optional[BoundingBox3D] = None
properties: Dict[str, Any] = field(default_factory=dict)
quantities: Dict[str, float] = field(default_factory=dict)
materials: List[MaterialInfo] = field(default_factory=list)
relationships: Dict[str, List[str]] = field(default_factory=dict)
@dataclass
class CADLayer:
"""CAD layer information"""
name: str
color: Optional[str] = None
line_type: Optional[str] = None
visible: bool = True
element_count: int = 0
@dataclass
class CADExtractionResult:
"""Result of CAD extraction"""
file_path: str
file_format: CADFormat
elements: List[CADElement]
layers: List[CADLayer]
levels: List[str]
total_elements: int
categories: Dict[str, int]
extraction_time: float
metadata: Dict[str, Any] = field(default_factory=dict)
class IFCExtractor:
"""Extract data from IFC files"""
def __init__(self):
self.schema_version = "IFC4"
self.element_mapping = self._build_element_mapping()
def _build_element_mapping(self) -> Dict[str, ElementCategory]:
"""Map IFC types to categories"""
return {
"IfcWall": ElementCategory.WALL,
"IfcWallStandardCase": ElementCategory.WALL,
"IfcSlab": ElementCategory.FLOOR,
"IfcRoof": ElementCategory.ROOF,
"IfcCeiling": ElementCategory.CEILING,
"IfcDoor": ElementCategory.DOOR,
"IfcWindow": ElementCategory.WINDOW,
"IfcColumn": ElementCategory.COLUMN,
"IfcBeam": ElementCategory.BEAM,
"IfcStair": ElementCategory.STAIR,
"IfcRamp": ElementCategory.RAMP,
"IfcFurnishingElement": ElementCategory.FURNITURE,
"IfcPipeSegment": ElementCategory.PIPE,
"IfcDuctSegment": ElementCategory.DUCT,
"IfcCableCarrierSegment": ElementCategory.CABLE_TRAY,
"IfcSpace": ElementCategory.SPACE,
}
def extract(
self,
file_path: str,
categories: Optional[List[ElementCategory]] = None
) -> CADExtractionResult:
"""
Extract data from IFC file.
Args:
file_path: Path to IFC file
categories: Optional filter for categories
Returns:
Extraction result
"""
start_time = datetime.now()
# In production, use ifcopenshell:
# import ifcopenshell
# ifc_file = ifcopenshell.open(file_path)
# Simulated extraction
elements = self._simulate_ifc_elements()
# Filter by category if specified
if categories:
elements = [e for e in elements if e.category in categories]
# Build category counts
category_counts = {}
for element in elements:
cat = element.category.value
category_counts[cat] = category_counts.get(cat, 0) + 1
# Extract levels
levels = list(set(e.level for e in elements if e.level))
extraction_time = (datetime.now() - start_time).total_seconds()
return CADExtractionResult(
file_path=file_path,
file_format=CADFormat.IFC,
elements=elements,
layers=[], # IFC doesn't use layers in traditional sense
levels=levels,
total_elements=len(elements),
categories=category_counts,
extraction_time=extraction_time,
metadata={
"schema": self.schema_version,
"project_name": "Sample Project"
}
)
def _simulate_ifc_elements(self) -> List[CADElement]:
"""Simulate IFC element extraction"""
elements = []
# Sample walls
for i in range(10):
elements.append(CADElement(
id=f"wall_{i}",
guid=f"1234567890ABCDEF{i:04d}",
name=f"Basic Wall {i}",
category=ElementCategory.WALL,
type_name="Basic Wall:200mm Concrete",
level="Level 1",
bounding_box=BoundingBox3D(
min_point=Point3D(i * 5, 0, 0),
max_point=Point3D(i * 5 + 5, 0.2, 3)
),
properties={
"IsExternal": True,
"FireRating": "1 HR",
"LoadBearing": True
},
quantities={
"Length": 5.0,
"Height": 3.0,
"Width": 0.2,
"Area": 15.0,
"Volume": 3.0
},
materials=[
MaterialInfo(
name="Concrete",
category="Concrete",
area=15.0,
volume=3.0
)
]
))
# Sample doors
for i in range(5):
elements.append(CADElement(
id=f"door_{i}",
guid=f"DOOR0000000000{i:04d}",
name=f"Single Door {i}",
category=ElementCategory.DOOR,
type_name="Single Flush:900x2100",
level="Level 1",
properties={
"FireRating": "None",
"IsExternal": False
},
quantities={
"Width": 0.9,
"Height": 2.1,
"Area": 1.89
},
relationships={
"host_wall": [f"wall_{i}"]
}
))
# Sample spaces
for i in range(3):
elements.append(CADElement(
id=f"space_{i}",
guid=f"SPACE000000000{i:04d}",
name=f"Room {i+101}",
category=ElementCategory.SPACE,
type_name="Office",
level="Level 1",
quantities={
"Area": 25.0 + i * 5,
"Volume": 75.0 + i * 15,
"Perimeter": 20.0 + i * 2
},
properties={
"OccupancyType": "Office",
"DesignOccupancy": 4
}
))
return elements
def get_quantities(
self,
elements: List[CADElement],
quantity_type: str = "all"
) -> Dict[str, float]:
"""Aggregate quantities from elements"""
totals = {}
for element in elements:
for qty_name, qty_value in element.quantities.items():
if quantity_type == "all" or qty_name.lower() == quantity_type.lower():
key = f"{element.category.value}_{qty_name}"
totals[key] = totals.get(key, 0) + qty_value
return totals
class DWGExtractor:
"""Extract data from DWG/DXF files"""
def __init__(self):
self.supported_entities = ["LINE", "POLYLINE", "CIRCLE", "ARC", "TEXT", "MTEXT", "INSERT", "HATCH"]
def extract(
self,
file_path: str,
layers: Optional[List[str]] = None
) -> CADExtractionResult:
"""Extract data from DWG file"""
start_time = datetime.now()
# In production, use ezdxf:
# import ezdxf
# doc = ezdxf.readfile(file_path)
# Simulated extraction
elements, cad_layers = self._simulate_dwg_extraction()
# Filter by layers if specified
if layers:
elements = [e for e in elements if e.properties.get("layer") in layers]
extraction_time = (datetime.now() - start_time).total_seconds()
return CADExtractionResult(
file_path=file_path,
file_format=CADFormat.DWG,
elements=elements,
layers=cad_layers,
levels=[],
total_elements=len(elements),
categories={"generic": len(elements)},
extraction_time=extraction_time,
metadata={"units": "millimeters"}
)
def _simulate_dwg_extraction(self) -> Tuple[List[CADElement], List[CADLayer]]:
"""Simulate DWG extraction"""
elements = []
layers = [
CADLayer("Walls", "Red", "Continuous", True, 15),
CADLayer("Doors", "Blue", "Continuous", True, 8),
CADLayer("Windows", "Cyan", "Continuous", True, 12),
CADLayer("Dimensions", "Green", "Continuous", True, 50),
CADLayer("Text", "White", "Continuous", True, 25),
]
# Simulate polylines (walls)
for i in range(15):
elements.append(CADElement(
id=f"polyline_{i}",
guid=f"PL{i:08d}",
name=f"Polyline {i}",
category=ElementCategory.GENERIC,
type_name="POLYLINE",
properties={
"layer": "Walls",
"color": "Red",
"closed": True
},
quantities={
"Length": 10.5 + i * 0.5
}
))
return elements, layers
class CADDataConverter:
"""
Convert CAD/BIM files to structured data.
Based on DDC methodology Chapter 2.4.
"""
def __init__(self):
self.ifc_extractor = IFCExtractor()
self.dwg_extractor = DWGExtractor()
def convert(
self,
file_path: str,
output_format: str = "json"
) -> Dict[str, Any]:
"""
Convert CAD file to structured data.
Args:
file_path: Path to CAD file
output_format: Output format (json, csv, dataframe)
Returns:
Structured data
"""
# Detect file format
file_format = self._detect_format(file_path)
# Extract based on format
if file_format == CADFormat.IFC:
result = self.ifc_extractor.extract(file_path)
elif file_format in [CADFormat.DWG, CADFormat.DXF]:
result = self.dwg_extractor.extract(file_path)
else:
raise ValueError(f"Unsupported format: {file_format}")
# Convert to output format
return self._format_output(result, output_format)
def _detect_format(self, file_path: str) -> CADFormat:
"""Detect CAD file format"""
extension = file_path.lower().split(".")[-1]
format_map = {
"ifc": CADFormat.IFC,
"rvt": CADFormat.RVT,
"dwg": CADFormat.DWG,
"dxf": CADFormat.DXF,
"dgn": CADFormat.DGN,
"nwd": CADFormat.NWD,
}
return format_map.get(extension, CADFormat.IFC)
def _format_output(
self,
result: CADExtractionResult,
format: str
) -> Dict[str, Any]:
"""Format extraction result"""
output = {
"file": result.file_path,
"format": result.file_format.value,
"total_elements": result.total_elements,
"categories": result.categories,
"levels": result.levels,
"extraction_time": result.extraction_time,
"elements": []
}
for element in result.elements:
output["elements"].append({
"id": element.id,
"guid": element.guid,
"name": element.name,
"category": element.category.value,
"type": element.type_name,
"level": element.level,
"properties": element.properties,
"quantities": element.quantities,
"materials": [
{"name": m.name, "area": m.area, "volume": m.volume}
for m in element.materials
]
})
return output
def extract_quantities(
self,
file_path: str,
categories: Optional[List[ElementCategory]] = None
) -> Dict[str, Any]:
"""Extract quantity takeoff from CAD file"""
file_format = self._detect_format(file_path)
if file_format == CADFormat.IFC:
result = self.ifc_extractor.extract(file_path, categories)
else:
result = self.dwg_extractor.extract(file_path)
# Aggregate quantities by category
quantities = {}
for element in result.elements:
cat = element.category.value
if cat not in quantities:
quantities[cat] = {
"count": 0,
"totals": {}
}
quantities[cat]["count"] += 1
for qty_name, qty_value in element.quantities.items():
if qty_name not in quantities[cat]["totals"]:
quantities[cat]["totals"][qty_name] = 0
quantities[cat]["totals"][qty_name] += qty_value
return {
"file": file_path,
"quantities": quantities,
"summary": {
"total_elements": result.total_elements,
"categories": list(quantities.keys())
}
}
def extract_schedule(
self,
file_path: str,
category: ElementCategory,
fields: List[str]
) -> List[Dict]:
"""Extract schedule data for specific category"""
file_format = self._detect_format(file_path)
if file_format == CADFormat.IFC:
result = self.ifc_extractor.extract(file_path, [category])
else:
result = self.dwg_extractor.extract(file_path)
schedule = []
for element in result.elements:
if element.category == category:
row = {"id": element.id, "name": element.name, "type": element.type_name}
for field in fields:
if field in element.properties:
row[field] = element.properties[field]
elif field in element.quantities:
row[field] = element.quantities[field]
schedule.append(row)
return schedule
def export_to_json(
self,
result: CADExtractionResult,
output_path: str
):
"""Export extraction result to JSON file"""
output = self._format_output(result, "json")
with open(output_path, 'w') as f:
json.dump(output, f, indent=2)
def generate_report(self, result: CADExtractionResult) -> str:
"""Generate extraction report"""
report = f"""
# CAD Extraction Report
**File:** {result.file_path}
**Format:** {result.file_format.value}
**Total Elements:** {result.total_elements}
**Extraction Time:** {result.extraction_time:.2f}s
## Elements by Category
"""
for cat, count in result.categories.items():
report += f"- **{cat.title()}:** {count}\n"
if result.levels:
report += "\n## Levels\n"
for level in result.levels:
report += f"- {level}\n"
if result.layers:
report += "\n## Layers\n"
for layer in result.layers:
report += f"- {layer.name}: {layer.element_count} elements\n"
return report
converter = CADDataConverter()
# Convert IFC to structured data
data = converter.convert("building.ifc", output_format="json")
print(f"Total elements: {data['total_elements']}")
print(f"Categories: {data['categories']}")
# Access elements
for element in data['elements'][:5]:
print(f" {element['name']}: {element['type']}")
quantities = converter.extract_quantities(
"building.ifc",
categories=[ElementCategory.WALL, ElementCategory.FLOOR]
)
print(f"Wall count: {quantities['quantities']['wall']['count']}")
print(f"Total wall area: {quantities['quantities']['wall']['totals']['Area']}")
door_schedule = converter.extract_schedule(
"building.ifc",
category=ElementCategory.DOOR,
fields=["Width", "Height", "FireRating", "IsExternal"]
)
for door in door_schedule:
print(f"{door['name']}: {door.get('Width')}x{door.get('Height')}")
ifc_extractor = IFCExtractor()
result = ifc_extractor.extract("building.ifc")
report = converter.generate_report(result)
print(report)
| Component | Purpose |
|-----------|---------|
| CADDataConverter | Main conversion engine |
| IFCExtractor | IFC file extraction |
| DWGExtractor | DWG/DXF extraction |
| CADElement | Extracted element data |
| CADExtractionResult | Complete extraction result |
| ElementCategory | BIM element categories |
Integration with protocols.io API for managing scientific protocols. This skill should be used when working with protocols.io to search, create, update, or publish protocols; manage protocol steps and materials; handle discussions and comments; organize workspaces; upload and manage files; or integrate protocols.io functionality into workflows. Applicable for protocol discovery, collaborative protocol development, experiment tracking, lab protocol management, and scientific documentation.
Analyzes job descriptions and generates tailored resumes that highlight relevant experience, skills, and achievements to maximize interview chances
Generate Excalidraw diagrams from natural language descriptions. Use when asked to "create a diagram", "make a flowchart", "visualize a process", "draw a system architecture", "create a mind map", or "generate an Excalidraw file". Supports flowcharts, relationship diagrams, mind maps, and system architecture diagrams. Outputs .excalidraw JSON files that can be opened directly in Excalidraw.
Build and distribute Expo development clients locally or via TestFlight
Use when you have a written implementation plan to execute in a separate session with review checkpoints
Data structure for annotated matrices in single-cell analysis. Use when working with .h5ad files or integrating with the scverse ecosystem. This is the data format skill—for analysis workflows use scanpy; for probabilistic models use scvi-tools; for population-scale queries use cellxgene-census.
Benchling R&D platform integration. Access registry (DNA, proteins), inventory, ELN entries, workflows via API, build Benchling Apps, query Data Warehouse, for lab data management automation.
Comprehensive molecular biology toolkit. Use for sequence manipulation, file parsing (FASTA/GenBank/PDB), phylogenetics, and programmatic NCBI/PubMed access (Bio.Entrez). Best for batch processing, custom bioinformatics pipelines, BLAST automation. For quick lookups use gget; for multi-service integration use bioservices.
Take datadrivenconstruction/cad-to-data from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.