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rvt-to-excel

rvt-to-excel

github.com/datadrivenconstructionData & databases375118 installsUpdated 1w ago
Repository

About rvt-to-excel

rvt-to-excel converts Revit RVT files into structured Excel workbooks for BIM analysis and reporting. Its CLI offers configurable export modes and options for element properties, schedules, rooms, and sheets.

Key features

  1. 01Export RVT data to Excel
  2. 02Choose basic, standard, complete, or custom modes
  3. 03Include bounding boxes and room associations
  4. 04Export schedules and sheets
  5. 05Organize elements, levels, and materials into sheets

Use cases

  1. 01Extract BIM data from multiple projects
  2. 02Prepare structured data for analytics
  3. 03Share element properties in Excel
  4. 04Generate quantity takeoffs and reports

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/datadrivenconstruction/ddc_skills_for_ai_agents_in_construction --skill rvt-to-excel

After installing, type/rvt-to-excelin Claude Code to confirm it loaded.

Bundled filesclaw.jsoninstructions.md

Details

From the project README

RVT 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
ModeCategoriesDescription
basic309Essential structural elements
standard724Standard BIM categories
complete1209All Revit categories
customUser-definedSpecific categories only
Options
OptionDescription
bboxInclude bounding box coordinates
roomsInclude room associations
schedulesExport all schedules to sheets
sheetsExport 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
SheetContent
ElementsAll BIM elements with properties
CategoriesElement categories summary
LevelsBuilding levels
MaterialsMaterial definitions
ParametersShared parameters
Element Columns
ColumnTypeDescription
ElementIdintUnique Revit ID
CategorystringElement category
FamilystringFamily name
TypestringType name
LevelstringAssociated level
AreafloatSurface area (m²)
VolumefloatVolume (m³)
BBox_MinX/Y/ZfloatBounding box min
BBox_MaxX/Y/ZfloatBounding 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

  1. Use appropriate mode - basic for quick analysis, complete for full data
  2. Include bbox - Required for spatial analysis and visualization
  3. Batch carefully - Large files may take time; process overnight
  4. Validate output - Check element counts against Revit schedules

Resources

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