Skill: datadrivenconstruction/ifc-to-excel (version 2.0.0)

--- name: "ifc-to-excel" description: "Convert IFC files (2x3, 4x1, 4x3) to Excel databases using IfcExporter CLI. Extract BIM data, properties, and geometry without proprietary software." --- # IFC to Excel Conversion ## Business Case ### Problem Statement IFC (Industry Foundation Classes) is the open BIM standard, but: - Reading IFC requires specialized software - Property extraction needs programming knowledge - Batch processing is manual and time-consuming - Integration with analytics tools is complex ### Solution IfcExporter.exe converts IFC files to structured Excel databases, making BIM data accessible for analysis, validation, and reporting. ### Business Value - **Open standard** - Process any IFC file (2x3, 4x, 4.3) - **No licenses** - Works offline without BIM software - **Data extraction** - All properties, quantities, materials - **3D geometry** - Export to Collada DAE format - **Pipeline ready** - Integrate with ETL workflows ## Technical Implementation ### CLI Syntax ```bash IfcExporter.exe <input_ifc> [options] ``` ### Supported IFC Versions | Version | Schema | Description | |---------|--------|-------------| | IFC2x3 | MVD | Most common exchange format | | IFC4 | ADD1 | Enhanced properties | | IFC4x1 | Alignment | Infrastructure support | | IFC4x3 | Latest | Full infrastructure | ### Output Formats | Output | Description | |--------|-------------| | `.xlsx` | Excel database with elements and properties | | `.dae` | Collada 3D geometry with matching IDs | ### Options | Option | Description | |--------|-------------| | `bbox` | Include element bounding boxes | | `-no-xlsx` | Skip Excel export | | `-no-collada` | Skip 3D geometry export | ### Examples ```bash # Basic conversion (XLSX + DAE) IfcExporter.exe "C:\Models\Building.ifc" # With bounding boxes IfcExporter.exe "C:\Models\Building.ifc" bbox # Excel only (no 3D geometry) IfcExporter.exe "C:\Models\Building.ifc" -no-collada # Batch processing for /R "C:\IFC_Models" %f in (*.ifc) do IfcExporter.exe "%f" bbox ``` ### Python Integration ```python import subprocess import pandas as pd from pathlib import Path from typing import List, Optional, Dict, Any, Set from dataclasses import dataclass, field from enum import Enum import json class IFCVersion(Enum): """IFC schema versions.""" IFC2X3 = "IFC2X3" IFC4 = "IFC4" IFC4X1 = "IFC4X1" IFC4X3 = "IFC4X3" class IFCEntityType(Enum): """Common IFC entity types.""" IFCWALL = "IfcWall" IFCWALLSTANDARDCASE = "IfcWallStandardCase" IFCSLAB = "IfcSlab" IFCCOLUMN = "IfcColumn" IFCBEAM = "IfcBeam" IFCDOOR = "IfcDoor" IFCWINDOW = "IfcWindow" IFCROOF = "IfcRoof" IFCSTAIR = "IfcStair" IFCRAILING = "IfcRailing" IFCFURNISHINGELEMENT = "IfcFurnishingElement" IFCSPACE = "IfcSpace" IFCBUILDINGSTOREY = "IfcBuildingStorey" IFCBUILDING = "IfcBuilding" IFCSITE = "IfcSite" @dataclass class IFCElement: """Represents an IFC element.""" global_id: str ifc_type: str name: str description: Optional[str] object_type: Optional[str] level: Optional[str] # Quantities area: Optional[float] = None volume: Optional[float] = None length: Optional[float] = None height: Optional[float] = None width: Optional[float] = None # Bounding box (if exported) bbox_min_x: Optional[float] = None bbox_min_y: Optional[float] = None bbox_min_z: Optional[float] = None bbox_max_x: Optional[float] = None bbox_max_y: Optional[float] = None bbox_max_z: Optional[float] = None # Properties properties: Dict[str, Any] = field(default_factory=dict) materials: List[str] = field(default_factory=list) @dataclass class IFCProperty: """Represents an IFC property.""" pset_name: str property_name: str value: Any value_type: str @dataclass class IFCMaterial: """Represents an IFC material.""" name: str category: Optional[str] thickness: Optional[float] layer_position: Optional[int] class IFCExporter: """IFC to Excel converter using DDC IfcExporter CLI.""" def __init__(self, exporter_path: str = "IfcExporter.exe"): self.exporter = Path(exporter_path) if not self.exporter.exists(): raise FileNotFoundError(f"IfcExporter not found: {exporter_path}") def convert(self, ifc_file: str, include_bbox: bool = True, export_xlsx: bool = True, export_collada: bool = True) -> Path: """Convert IFC file to Excel.""" ifc_path = Path(ifc_file) if not ifc_path.exists(): raise FileNotFoundError(f"IFC file not found: {ifc_file}") cmd = [str(self.exporter), str(ifc_path)] if include_bbox: cmd.append("bbox") if not export_xlsx: cmd.append("-no-xlsx") if not export_collada: cmd.append("-no-collada") result = subprocess.run(cmd, capture_output=True, text=True) if result.returncode != 0: raise RuntimeError(f"Export failed: {result.stderr}") return ifc_path.with_suffix('.xlsx') def batch_convert(self, folder: str, include_subfolders: bool = True, include_bbox: bool = True) -> List[Dict[str, Any]]: """Convert all IFC files in folder.""" folder_path = Path(folder) pattern = "**/*.ifc" if include_subfolders else "*.ifc" results = [] for ifc_file in folder_path.glob(pattern): try: output = self.convert(str(ifc_file), include_bbox) results.append({ 'input': str(ifc_file), 'output': str(output), 'status': 'success' }) print(f"✓ Converted: {ifc_file.name}") except Exception as e: results.append({ 'input': str(ifc_file), 'output': None, 'status': 'failed', 'error': str(e) }) print(f"✗ Failed: {ifc_file.name} - {e}") return results def read_elements(self, xlsx_file: str) -> pd.DataFrame: """Read converted Excel as DataFrame.""" return pd.read_excel(xlsx_file, sheet_name="Elements") def get_element_types(self, xlsx_file: str) -> pd.DataFrame: """Get element type summary.""" df = self.read_elements(xlsx_file) if 'IfcType' not in df.columns: raise ValueError("IfcType column not found") summary = df.groupby('IfcType').agg({ 'GlobalId': 'count', 'Volume': 'sum' if 'Volume' in df.columns else 'count', 'Area': 'sum' if 'Area' in df.columns else 'count' }).reset_index() summary.columns = ['IFC_Type', 'Count', 'Total_Volume', 'Total_Area'] return summary.sort_values('Count', ascending=False) def get_levels(self, xlsx_file: str) -> pd.DataFrame: """Get building level summary.""" df = self.read_elements(xlsx_file) level_col = None for col in ['Level', 'BuildingStorey', 'IfcBuildingStorey']: if col in df.columns: level_col = col break if level_col is None: return pd.DataFrame(columns=['Level', 'Element_Count']) summary = df.groupby(level_col).agg({ 'GlobalId': 'count' }).reset_index() summary.columns = ['Level', 'Element_Count'] return summary def get_materials(self, xlsx_file: str) -> pd.DataFrame: """Get material summary.""" df = self.read_elements(xlsx_file) if 'Material' not in df.columns: return pd.DataFrame(columns=['Material', 'Count']) summary = df.groupby('Material').agg({ 'GlobalId': 'count' }).reset_index() summary.columns = ['Material', 'Element_Count'] return summary.sort_values('Element_Count', ascending=False) def get_quantities(self, xlsx_file: str, group_by: str = 'IfcType') -> pd.DataFrame: """Get quantity takeoff summary.""" df = self.read_elements(xlsx_file) if group_by not in df.columns: raise ValueError(f"Column {group_by} not found") agg_dict = {'GlobalId': 'count'} # Add numeric columns for aggregation numeric_cols = ['Volume', 'Area', 'Length', 'Width', 'Height'] for col in numeric_cols: if col in df.columns: agg_dict[col] = 'sum' summary = df.groupby(group_by).agg(agg_dict).reset_index() return summary def filter_by_type(self, xlsx_file: str, ifc_types: List[str]) -> pd.DataFrame: """Filter elements by IFC type.""" df = self.read_elements(xlsx_file) return df[df['IfcType'].isin(ifc_types)] def get_properties(self, xlsx_file: str, element_id: str) -> Dict[str, Any]: """Get all properties for specific element.""" df = self.read_elements(xlsx_file) element = df[df['GlobalId'] == element_id] if element.empty: return {} # Convert row to dictionary, excluding NaN values props = element.iloc[0].dropna().to_dict() return props def validate_ifc_data(self, xlsx_file: str) -> Dict[str, Any]: """Validate IFC data quality.""" df = self.read_elements(xlsx_file) validation = { 'total_elements': len(df), 'issues': [] } # Check for missing GlobalIds if 'GlobalId' in df.columns: missing_ids = df['GlobalId'].isna().sum() if missing_ids > 0: validation['issues'].append(f"{missing_ids} elements missing GlobalId") # Check for missing names if 'Name' in df.columns: missing_names = df['Name'].isna().sum() if missing_names > 0: validation['issues'].append(f"{missing_names} elements missing Name") # Check for zero quantities for col in ['Volume', 'Area']: if col in df.columns: zero_qty = (df[col] == 0).sum() if zero_qty > 0: validation['issues'].append(f"{zero_qty} elements with zero {col}") # Check for duplicate GlobalIds if 'GlobalId' in df.columns: duplicates = df['GlobalId'].duplicated().sum() if duplicates > 0: validation['issues'].append(f"{duplicates} duplicate GlobalIds") validation['is_valid'] = len(validation['issues']) == 0 return validation class IFCQuantityTakeoff: """Quantity takeoff from IFC data.""" def __init__(self, exporter: IFCExporter): self.exporter = exporter def generate_qto(self, ifc_file: str) -> Dict[str, pd.DataFrame]: """Generate complete quantity takeoff.""" xlsx = self.exporter.convert(ifc_file, include_bbox=True) df = self.exporter.read_elements(str(xlsx)) qto = {} # Walls walls = df[df['IfcType'].str.contains('Wall', case=False, na=False)] if not walls.empty: qto['Walls'] = self._summarize_elements(walls, 'Type Name') # Slabs slabs = df[df['IfcType'].str.contains('Slab', case=False, na=False)] if not slabs.empty: qto['Slabs'] = self._summarize_elements(slabs, 'Type Name') # Columns columns = df[df['IfcType'].str.contains('Column', case=False, na=False)] if not columns.empty: qto['Columns'] = self._summarize_elements(columns, 'Type Name') # Beams beams = df[df['IfcType'].str.contains('Beam', case=False, na=False)] if not beams.empty: qto['Beams'] = self._summarize_elements(beams, 'Type Name') # Doors doors = df[df['IfcType'].str.contains('Door', case=False, na=False)] if not doors.empty: qto['Doors'] = self._summarize_elements(doors, 'Type Name') # Windows windows = df[df['IfcType'].str.contains('Window', case=False, na=False)] if not windows.empty: qto['Windows'] = self._summarize_elements(windows, 'Type Name') return qto def _summarize_elements(self, df: pd.DataFrame, group_col: str) -> pd.DataFrame: """Summarize elements by grouping column.""" if group_col not in df.columns: group_col = 'IfcType' agg_dict = {'GlobalId': 'count'} for col in ['Volume', 'Area', 'Length']: if col in df.columns: agg_dict[col] = 'sum' summary = df.groupby(group_col).agg(agg_dict).reset_index() summary.rename(columns={'GlobalId': 'Count'}, inplace=True) return summary def export_to_excel(self, qto: Dict[str, pd.DataFrame], output_file: str): """Export QTO to multi-sheet Excel.""" with pd.ExcelWriter(output_file, engine='openpyxl') as writer: for sheet_name, df in qto.items(): df.to_excel(writer, sheet_name=sheet_name, index=False) # Convenience functions def convert_ifc_to_excel(ifc_file: str, exporter_path: str = "IfcExporter.exe") -> str: """Quick conversion of IFC to Excel.""" exporter = IFCExporter(exporter_path) output = exporter.convert(ifc_file) return str(output) def get_ifc_summary(xlsx_file: str) -> Dict[str, Any]: """Get summary of converted IFC data.""" df = pd.read_excel(xlsx_file, sheet_name="Elements") return { 'total_elements': len(df), 'ifc_types': df['IfcType'].nunique() if 'IfcType' in df.columns else 0, 'levels': df['Level'].nunique() if 'Level' in df.columns else 0, 'total_volume': df['Volume'].sum() if 'Volume' in df.columns else 0, 'total_area': df['Area'].sum() if 'Area' in df.columns else 0 } ``` ## Output Structure ### Excel Sheets | Sheet | Content | |-------|---------| | Elements | All IFC elements with properties | | Types | Element types summary | | Levels | Building storey data | | Materials | Material assignments | | PropertySets | IFC property sets | ### Element Columns | Column | Type | Description | |--------|------|-------------| | GlobalId | string | IFC GUID | | IfcType | string | IFC entity type | | Name | string | Element name | | Description | string | Element description | | Level | string | Building storey | | Material | string | Primary material | | Volume | float | Volume (m³) | | Area | float | Surface area (m²) | | Length | float | Length (m) | | Height | float | Height (m) | | Width | float | Width (m) | ## Quick Start ```python # Initialize exporter exporter = IFCExporter("C:/DDC/IfcExporter.exe") # Convert IFC to Excel xlsx = exporter.convert("C:/Models/Building.ifc", include_bbox=True) # Read elements df = exporter.read_elements(str(xlsx)) print(f"Total elements: {len(df)}") # Get element types types = exporter.get_element_types(str(xlsx)) print(types) # Get quantities by type qto = exporter.get_quantities(str(xlsx), group_by='IfcType') print(qto) ``` ## Common Use Cases ### 1. Model Validation ```python exporter = IFCExporter() xlsx = exporter.convert("model.ifc") validation = exporter.validate_ifc_data(str(xlsx)) if not validation['is_valid']: print("Issues found:") for issue in validation['issues']: print(f" - {issue}") ``` ### 2. Quantity Takeoff ```python qto_generator = IFCQuantityTakeoff(exporter) qto = qto_generator.generate_qto("building.ifc") for category, data in qto.items(): print(f"\n{category}:") print(data.to_string(index=False)) ``` ### 3. Material Schedule ```python xlsx = exporter.convert("building.ifc") materials = exporter.get_materials(str(xlsx)) print(materials) ``` ## Integration with DDC Pipeline ```python # Full pipeline: IFC → Excel → Validation → Cost Estimate exporter = IFCExporter("C:/DDC/IfcExporter.exe") # 1. Convert IFC xlsx = exporter.convert("project.ifc", include_bbox=True) # 2. Validate data validation = exporter.validate_ifc_data(str(xlsx)) print(f"Valid: {validation['is_valid']}") # 3. Generate QTO qto = IFCQuantityTakeoff(exporter) quantities = qto.generate_qto("project.ifc") # 4. Export for cost estimation qto.export_to_excel(quantities, "project_qto.xlsx") ``` ## Resources - **GitHub**: [cad2data Pipeline](https://github.com/datadrivenconstruction/cad2data-Revit-IFC-DWG-DGN-pipeline-with-conversion-validation-qto) - **IFC Standard**: [buildingSMART](https://www.buildingsmart.org/standards/bsi-standards/industry-foundation-classes/) - **DDC Book**: Chapter 2.4 - CAD/BIM Data Extraction

path: claw.json
content: {
  "name": "ifc-to-excel",
  "version": "2.0.0",
  "description": "Convert IFC files (2x3, 4x1, 4x3) to Excel databases using IfcExporter CLI. Extract BIM data, properties, and geometry without proprietary software.",
  "author": "datadrivenconstruction",
  "license": "MIT",
  "permissions": ["filesystem"],
  "entry": "instructions.md",
  "tags": ["construction", "BIM", "IFC", "Excel", "data-conversion", "openBIM", "buildingSMART"],
  "models": ["claude-*", "gpt-*"],
  "minOpenClawVersion": "0.8.0"
}


path: instructions.md
content: You are a BIM data conversion assistant. You help users convert IFC (Industry Foundation Classes) files to structured Excel databases.

When the user asks to convert IFC to Excel:
1. Verify the input file path and IFC schema version (2x3, 4x1, 4x3)
2. Run IfcExporter CLI or IfcOpenShell to parse the model
3. Extract entities: walls, slabs, columns, beams, doors, windows, MEP elements
4. Export to Excel with one sheet per IFC entity type

When the user asks to analyze IFC data:
1. Summarize by entity type with counts and quantities
2. Show property sets and their values
3. Extract spatial structure (site, building, storey, space)
4. Calculate totals: area, volume, length per type

## Input Format
- IFC file path (.ifc, schemas IFC2x3, IFC4, IFC4.3)
- Optional: specific entity types to extract
- Optional: specific property sets to include

## Output Format
- Excel file with sheets per entity type (IfcWall, IfcSlab, IfcColumn, etc.)
- Each element: GlobalId, Name, Type, Storey, PropertySets, Quantities
- Summary sheet with totals by type
- Spatial structure sheet (Site > Building > Storey hierarchy)

## Constraints
- Filesystem permission required for reading IFC and writing Excel
- Uses IfcOpenShell (open-source) or DDC IfcExporter CLI
- subprocess.run() is used solely for invoking IfcExporter CLI tool
- No proprietary software required — fully open-source pipeline
- Supports all IFC schemas: IFC2x3, IFC4, IFC4.3


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: suspicious | SkillSpector: suspicious (MEDIUM)