rvt-to-excel
npx machina-cli add skill datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction/rvt-to-excel --openclawRVT to Excel Conversion
Business Case
Problem Statement
BIM data inside RVT files needs to be extracted for:
- Processing multiple projects in batch
- Integrating BIM data with analytics pipelines
- Sharing structured data with stakeholders
- Generating reports and quantity takeoffs
Solution
Convert RVT files to structured Excel databases for analysis and reporting.
Business Value
- Batch processing - Convert multiple projects
- Data accessibility - Excel format for universal access
- Pipeline integration - Feed data to BI tools, ML models
- Structured output - Organized element data and properties
Technical Implementation
CLI Syntax
RvtExporter.exe <input_path> [export_mode] [options]
Export Modes
| Mode | Categories | Description |
|---|---|---|
basic | 309 | Essential structural elements |
standard | 724 | Standard BIM categories |
complete | 1209 | All Revit categories |
custom | User-defined | Specific categories only |
Options
| Option | Description |
|---|---|
bbox | Include bounding box coordinates |
rooms | Include room associations |
schedules | Export all schedules to sheets |
sheets | Export sheets to PDF |
Examples
# Basic export
RvtExporter.exe "C:\Projects\Building.rvt" basic
# Complete with bounding boxes
RvtExporter.exe "C:\Projects\Building.rvt" complete bbox
# Full export with all options
RvtExporter.exe "C:\Projects\Building.rvt" complete bbox rooms schedules sheets
# Batch processing
for /R "C:\Projects" %f in (*.rvt) do RvtExporter.exe "%f" standard bbox
Python Integration
import subprocess
import pandas as pd
from pathlib import Path
from typing import List, Optional
class RevitExporter:
def __init__(self, exporter_path: str = "RvtExporter.exe"):
self.exporter = Path(exporter_path)
if not self.exporter.exists():
raise FileNotFoundError(f"RvtExporter not found: {exporter_path}")
def convert(self, rvt_file: str, mode: str = "complete",
options: List[str] = None) -> Path:
"""Convert Revit file to Excel."""
rvt_path = Path(rvt_file)
if not rvt_path.exists():
raise FileNotFoundError(f"Revit file not found: {rvt_file}")
cmd = [str(self.exporter), str(rvt_path), mode]
if options:
cmd.extend(options)
result = subprocess.run(cmd, capture_output=True, text=True)
if result.returncode != 0:
raise RuntimeError(f"Export failed: {result.stderr}")
# Output file is same name with .xlsx extension
output_file = rvt_path.with_suffix('.xlsx')
return output_file
def batch_convert(self, folder: str, mode: str = "standard",
pattern: str = "*.rvt") -> List[Path]:
"""Convert all Revit files in folder."""
folder_path = Path(folder)
converted = []
for rvt_file in folder_path.glob(pattern):
try:
output = self.convert(str(rvt_file), mode)
converted.append(output)
print(f"Converted: {rvt_file.name}")
except Exception as e:
print(f"Failed: {rvt_file.name} - {e}")
return converted
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_quantities(self, xlsx_file: str,
group_by: str = "Category") -> pd.DataFrame:
"""Get quantity summary grouped by category."""
df = self.read_elements(xlsx_file)
# Group and count
summary = df.groupby(group_by).agg({
'ElementId': 'count',
'Area': 'sum',
'Volume': 'sum'
}).reset_index()
summary.columns = [group_by, 'Count', 'Total_Area', 'Total_Volume']
return summary
Output Structure
Excel Sheets
| Sheet | Content |
|---|---|
| Elements | All BIM elements with properties |
| Categories | Element categories summary |
| Levels | Building levels |
| Materials | Material definitions |
| Parameters | Shared parameters |
Element Columns
| Column | Type | Description |
|---|---|---|
| ElementId | int | Unique Revit ID |
| Category | string | Element category |
| Family | string | Family name |
| Type | string | Type name |
| Level | string | Associated level |
| Area | float | Surface area (m²) |
| Volume | float | Volume (m³) |
| BBox_MinX/Y/Z | float | Bounding box min |
| BBox_MaxX/Y/Z | float | Bounding box max |
Usage Example
# Initialize exporter
exporter = RevitExporter("C:/Tools/RvtExporter.exe")
# Convert single file
xlsx = exporter.convert("C:/Projects/Office.rvt", "complete", ["bbox", "rooms"])
# Read and analyze
df = exporter.read_elements(str(xlsx))
print(f"Total elements: {len(df)}")
# Quantity summary
quantities = exporter.get_quantities(str(xlsx))
print(quantities)
# Export to CSV for further processing
df.to_csv("elements.csv", index=False)
Integration with DDC Pipeline
# Full pipeline: Revit → Excel → Cost Estimate
from semantic_search import CWICRSemanticSearch
# 1. Convert Revit
exporter = RevitExporter()
xlsx = exporter.convert("project.rvt", "complete", ["bbox"])
# 2. Extract quantities
df = exporter.read_elements(str(xlsx))
quantities = df.groupby('Category')['Volume'].sum().to_dict()
# 3. Search CWICR for pricing
search = CWICRSemanticSearch()
costs = {}
for category, volume in quantities.items():
results = search.search_work_items(category, limit=5)
if not results.empty:
avg_price = results['unit_price'].mean()
costs[category] = volume * avg_price
print(f"Total estimate: ${sum(costs.values()):,.2f}")
Best Practices
- Use appropriate mode -
basicfor quick analysis,completefor full data - Include bbox - Required for spatial analysis and visualization
- Batch carefully - Large files may take time; process overnight
- Validate output - Check element counts against Revit schedules
Resources
- GitHub: cad2data Pipeline
- Download: See repository releases for RvtExporter.exe
Source
git clone https://github.com/datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction/blob/main/1_DDC_Toolkit/CAD-Converters/rvt-to-excel/SKILL.mdView on GitHub Overview
Converts RVT/RFA BIM data into structured Excel databases for analysis and reporting. It extracts element data, properties, and quantities and supports batch processing across multiple projects.
How This Skill Works
Run the RvtExporter.exe CLI with an input path, an export_mode (basic, standard, complete, or custom), and optional flags (bbox, rooms, schedules, sheets). The tool outputs a .xlsx workbook, with an Elements sheet and organized data by category, enabling downstream analytics. The included Python integration demonstrates programmatic conversion, batch processing, and simple read/summary utilities.
When to Use It
- Batch convert multiple RVT/RFA projects to Excel for analytics
- Integrate BIM data into BI dashboards or ML pipelines with structured Elements data
- Share structured element data and quantities with stakeholders in Excel
- Export specific BIM categories or complete datasets using basic/standard/complete/custom modes
- Automate batch exports via Python to fit into existing workflows
Quick Start
- Step 1: Install RvtExporter and prerequisites (Python3, RvtExporter).
- Step 2: Run a CLI export, e.g. RvtExporter.exe 'C:/Projects/Building.rvt' complete bbox
- Step 3: In Python, use RevitExporter to batch_convert, then read_elements and get_quantities
Best Practices
- Select export_mode to match data completeness: basic, standard, complete, or custom
- Use bbox and rooms only if geometry and associations are required for your use case
- Validate outputs by reading Elements with read_elements and verifying essential fields
- Leverage batch_convert for scalable project-wide exports
- Automate end-to-end with Python to fit into analytics or reporting pipelines
Example Use Cases
- Export complete BIM data for a multi-building portfolio to .xlsx for analytics
- Extract basic structural elements from several RVTs for quick reports
- Batch export with bounding boxes and room associations for cost modeling
- Export schedules to separate sheets for documentation alongside the Elements sheet
- Automate conversion of a folder of RVTs and summarize by Category using get_quantities