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rvt-to-excel

@datadrivenconstruction · 收录于 1 周前

Convert RVT/RFA files to Excel databases. Extract BIM element data, properties, and quantities.

适合你,如果经常需要从Revit模型中提取数据到Excel进行分析

/ 下载安装
rvt-to-excel.skill双击,或拖进 Claude 桌面版 / Cowork,即完成安装↓ .skill↓ .zip
用别的 agent?下载 .zip 解压,把文件夹放进它的技能目录
Claude Code~/.claude/skills/(项目级 .claude/skills/)
Codex CLI~/.codex/skills/
Cursor自动读取上面两处目录
其他工具见其文档的「skills」目录;两个下载是同一份文件,只是名字不同
/ 通过 npx 安装 校验哈希
npx oh-my-skill add datadrivenconstruction/ddc_skills_for_ai_agents_in_construction/rvt-to-excel
/ 通过 bash 安装
curl -fsSL https://oh-my-skill.com/install.sh | bash -s -- datadrivenconstruction/ddc_skills_for_ai_agents_in_construction/rvt-to-excel
/ 已经装过?验证本机副本,不用重装
npx oh-my-skill verify datadrivenconstruction/ddc_skills_for_ai_agents_in_construction/rvt-to-excel
安装目标可用 --agent / --scope 或 --to 明确指定;省略时只会在唯一已存在的 agent 目录上自动选择,零命中或多命中会停止并提示。content_hash 缺失或不一致均拒装。
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怎么用

技能原文 SKILL.md作者撰写 · MIT · 34e0d78

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

| 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
  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
按 MIT 许可原样转载,未经改动 · 在 GitHub 查看 →

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