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excel-to-rvt

excel-to-rvt

github.com/datadrivenconstruction数据与数据库375107 次安装1 周前更新
代码仓库

关于 excel-to-rvt

将 Excel 数据导入 Revit 模型的工作流,可通过 DDC ImportExcelToRevit 工具、Dynamo 或 Revit API 实现。支持参数更新及导入前验证。

主要功能

  1. 01将 Excel 数据导入 Revit
  2. 02映射表格列与参数
  3. 03导入前验证数据
  4. 04使用 CLI、Dynamo 或 Revit API

适用场景

  1. 01为模型元素分配分类代码
  2. 02从表格填充自定义参数
  3. 03用成本数据更新模型元素

安装

复制下面的命令,在终端中运行。

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

安装后在 Claude Code 中输入/excel-to-rvt确认已加载。

附带文件claw.jsoninstructions.md

详细介绍

Excel 导入 RVT

**注意:**RVT 是文件格式。示例可能会引用 Autodesk® Revit® API。Autodesk 和 Revit 是 Autodesk, Inc. 的注册商标。

业务案例

问题陈述

外部数据(成本、规格、分类)存储在 Excel 中,但需要更新到 Revit 中:

  • 需要将成本估算关联到模型元素
  • 需要分配分类代码
  • 需要填充自定义参数
  • 手动录入速度慢且容易出错
解决方案

使用 DDC ImportExcelToRevit 工具和 Dynamo 工作流,将 Excel 数据自动导入 Revit。

业务价值
  • 自动化 - 批量更新数千个参数
  • 准确性 - 消除手动数据录入错误
  • 同步 - 使外部数据与模型保持同步
  • 灵活性 - 更新任何可写参数

技术实现

方法
  1. ImportExcelToRevit CLI - 直接通过命令行更新
  2. Dynamo 脚本 - 可视化编程方法
  3. Revit API - 完全的编程控制
ImportExcelToRevit CLI
ImportExcelToRevit.exe <model.rvt> <data.xlsx> [options]
选项描述
-sheetExcel 工作表名称
-idcol元素 ID 列
-mapping参数映射文件
Python 实现
import subprocess
import pandas as pd
from pathlib import Path
from typing import Dict, Any, List, Optional, Tuple
from dataclasses import dataclass
import json


@dataclass
class ImportResult:
    """Result of Excel import to Revit."""
    elements_processed: int
    elements_updated: int
    elements_failed: int
    parameters_updated: int
    errors: List[str]


class ExcelToRevitImporter:
    """Import Excel data into Revit models."""

    def __init__(self, tool_path: str = "ImportExcelToRevit.exe"):
        self.tool_path = Path(tool_path)

    def import_data(self, revit_file: str,
                    excel_file: str,
                    sheet_name: str = "Elements",
                    id_column: str = "ElementId",
                    parameter_mapping: Dict[str, str] = None) -> ImportResult:
        """Import Excel data into Revit."""

        # Build command
        cmd = [
            str(self.tool_path),
            revit_file,
            excel_file,
            "-sheet", sheet_name,
            "-idcol", id_column
        ]

        # Add mapping file if provided
        if parameter_mapping:
            mapping_file = self._create_mapping_file(parameter_mapping)
            cmd.extend(["-mapping", mapping_file])

        # Execute
        result = subprocess.run(cmd, capture_output=True, text=True)

        # Parse result (format depends on tool)
        return self._parse_result(result)

    def _create_mapping_file(self, mapping: Dict[str, str]) -> str:
        """Create temporary mapping file."""
        mapping_path = Path("temp_mapping.json")
        with open(mapping_path, 'w') as f:
            json.dump(mapping, f)
        return str(mapping_path)

    def _parse_result(self, result: subprocess.CompletedProcess) -> ImportResult:
        """Parse CLI result."""
        # This is placeholder - actual parsing depends on tool output
        if result.returncode == 0:
            return ImportResult(
                elements_processed=0,
                elements_updated=0,
                elements_failed=0,
                parameters_updated=0,
                errors=[]
            )
        else:
            return ImportResult(
                elements_processed=0,
                elements_updated=0,
                elements_failed=0,
                parameters_updated=0,
                errors=[result.stderr]
            )


class DynamoScriptGenerator:
    """Generate Dynamo scripts for Revit data import."""

    def generate_parameter_update_script(self,
                                         mappings: Dict[str, str],
                                         excel_path: str,
                                         output_path: str) -> str:
        """Generate Dynamo Python script for parameter updates."""

        mappings_json = json.dumps(mappings)

        script = f'''
# Dynamo Python Script - Excel to Revit Parameter Update
# Generated by DDC

import clr
import sys
sys.path.append(r'C:\\Program Files (x86)\\IronPython 2.7\\Lib')

clr.AddReference('RevitAPI')
clr.AddReference('RevitServices')
clr.AddReference('Microsoft.Office.Interop.Excel')

from RevitServices.Persistence import DocumentManager
from RevitServices.Transactions import TransactionManager
from Autodesk.Revit.DB import *
import Microsoft.Office.Interop.Excel as Excel

# Configuration
excel_path = r'{excel_path}'
mappings = {mappings_json}

# Open Excel
excel_app = Excel.ApplicationClass()
excel_app.Visible = False
workbook = excel_app.Workbooks.Open(excel_path)
worksheet = workbook.Worksheets[1]

# Get Revit document
doc = DocumentManager.Instance.CurrentDBDocument

# Read Excel data
used_range = worksheet.UsedRange
rows = used_range.Rows.Count
cols = used_range.Columns.Count

# Find column indices
headers = {{}}
for col in range(1, cols + 1):
    header = str(worksheet.Cells[1, col].Value2 or '')
    headers[header] = col

# Process rows
TransactionManager.Instance.EnsureInTransaction(doc)

updated_count = 0
error_count = 0

for row in range(2, rows + 1):
    try:
        # Get element ID
        element_id_col = headers.get('ElementId', 1)
        element_id = int(worksheet.Cells[row, element_id_col].Value2 or 0)

        element = doc.GetElement(ElementId(element_id))
        if not element:
            continue

        # Update mapped parameters
        for excel_col, revit_param in mappings.items():
            if excel_col in headers:
                col_idx = headers[excel_col]
                value = worksheet.Cells[row, col_idx].Value2

                if value is not None:
                    param = element.LookupParameter(revit_param)
                    if param and not param.IsReadOnly:
                        if param.StorageType == StorageType.Double:
                            param.Set(float(value))
                        elif param.StorageType == StorageType.Integer:
                            param.Set(int(value))
                        elif param.StorageType == StorageType.String:
                            param.Set(str(value))

        updated_count += 1

    except Exception as e:
        error_count += 1

TransactionManager.Instance.TransactionTaskDone()

# Cleanup
workbook.Close(False)
excel_app.Quit()

OUT = f"Updated: {{updated_count}}, Errors: {{error_count}}"
'''

        with open(output_path, 'w') as f:
            f.write(script)

        return output_path

    def generate_schedule_creator(self,
                                  schedule_name: str,
                                  category: str,
                                  fields: List[str],
                                  output_path: str) -> str:
        """Generate script to create Revit schedule from Excel structure."""

        fields_json = json.dumps(fields)

        script = f'''
# Dynamo Python Script - Create Schedule
# Generated by DDC

import clr
clr.AddReference('RevitAPI')
clr.AddReference('RevitServices')

from RevitServices.Persistence import DocumentManager
from RevitServices.Transactions import TransactionManager
from Autodesk.Revit.DB import *

doc = DocumentManager.Instance.CurrentDBDocument
fields = {fields_json}

# Get category
category = Category.GetCategory(doc, BuiltInCategory.OST_{category})

TransactionManager.Instance.EnsureInTransaction(doc)

# Create schedule
schedule = ViewSchedule.CreateSchedule(doc, category.Id)
schedule.Name = "{schedule_name}"

# Add fields
definition = schedule.Definition

for field_name in fields:
    # Find schedulable field
    for sf in definition.GetSchedulableFields():
        if sf.GetName(doc) == field_name:
            definition.AddField(sf)
            break

TransactionManager.Instance.TransactionTaskDone()

OUT = schedule
'''

        with open(output_path, 'w') as f:
            f.write(script)

        return output_path


class ExcelDataValidator:
    """Validate Excel data before Revit import."""

    def __init__(self, revit_elements: pd.DataFrame):
        """Initialize with exported Revit elements."""
        self.revit_data = revit_elements
        self.valid_ids = set(revit_elements['ElementId'].astype(str).tolist())

    def validate_import_data(self, import_df: pd.DataFrame,
                             id_column: str = 'ElementId') -> Dict[str, Any]:
        """Validate import data against Revit export."""

        results = {
            'valid': True,
            'total_rows': len(import_df),
            'matching_ids': 0,
            'missing_ids': [],
            'invalid_ids': [],
            'warnings': []
        }

        import_ids = import_df[id_column].astype(str).tolist()

        for import_id in import_ids:
            if import_id in self.valid_ids:
                results['matching_ids'] += 1
            else:
                results['invalid_ids'].append(import_id)

        if results['invalid_ids']:
            results['valid'] = False
            results['warnings'].append(
                f"{len(results['invalid_ids'])} element IDs not found in Revit model"
            )

        results['match_rate'] = round(
            results['matching_ids'] / results['total_rows'] * 100, 1
        ) if results['total_rows'] > 0 else 0

        return results

    def check_parameter_types(self, import_df: pd.DataFrame,
                              type_definitions: Dict[str, str]) -> List[str]:
        """Check if values match expected parameter types."""

        errors = []

        for column, expected_type in type_definitions.items():
            if column not in import_df.columns:
                continue

            for idx, value in import_df[column].items():
                if pd.isna(value):
                    continue

                if expected_type == 'number':
                    try:
                        float(value)
                    except ValueError:
                        errors.append(f"Row {idx}: '{column}' should be number, got '{value}'")

                elif expected_type == 'integer':
                    try:
                        int(value)
                    except ValueError:
                        errors.append(f"Row {idx}: '{column}' should be integer, got '{value}'")

        return errors

快速开始

# Generate Dynamo script
generator = DynamoScriptGenerator()

mappings = {
    'OmniClass_Code': 'OmniClass Number',
    'Unit_Cost': 'Cost',
    'Material_Type': 'Material'
}

generator.generate_parameter_update_script(
    mappings=mappings,
    excel_path="enriched_data.xlsx",
    output_path="update_revit.py"
)

验证

# Validate before import
validator = ExcelDataValidator(revit_export_df)
validation = validator.validate_import_data(import_df)

if validation['valid']:
    print(f"Ready to import. Match rate: {validation['match_rate']}%")
else:
    print(f"Issues found: {validation['warnings']}")

完整工作流

# 1. Export from Revit
# RvtExporter.exe model.rvt complete

# 2. Load and validate
revit_df = pd.read_excel("model.xlsx")
validator = ExcelDataValidator(revit_df)

# 3. Prepare import data
import_df = pd.read_excel("enriched_data.xlsx")
validation = validator.validate_import_data(import_df)

# 4. Generate update script
if validation['valid']:
    generator = DynamoScriptGenerator()
    generator.generate_parameter_update_script(
        mappings={'Classification': 'OmniClass Number'},
        excel_path="enriched_data.xlsx",
        output_path="apply_updates.py"
    )
    print("Run apply_updates.py in Dynamo to update Revit")

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