excel-to-bim

After extracting BIM data to Excel and enriching it (cost codes, classifications, custom data):

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Install skill "excel-to-bim" with this command: npx skills add datadrivenconstruction/ddc_skills_for_ai_agents_in_construction/datadrivenconstruction-ddc-skills-for-ai-agents-in-construction-excel-to-bim

Excel to BIM Update

Business Case

Problem Statement

After extracting BIM data to Excel and enriching it (cost codes, classifications, custom data):

  • Changes need to flow back to the BIM model

  • Manual re-entry is error-prone

  • Updates must match by element ID

Solution

Push Excel data back to BIM models, updating element parameters and properties from spreadsheet changes.

Business Value

  • Bi-directional workflow - BIM → Excel → BIM

  • Bulk updates - Change thousands of parameters

  • Data enrichment - Add classifications, codes, costs

  • Consistency - Spreadsheet as single source of truth

Technical Implementation

Workflow

BIM Model (Revit/IFC) → Excel Export → Data Enrichment → Excel Update → BIM Model

Python Implementation

import pandas as pd from pathlib import Path from typing import Dict, Any, List, Optional, Tuple from dataclasses import dataclass, field from enum import Enum import json

class UpdateType(Enum): """Type of BIM parameter update.""" TEXT = "text" NUMBER = "number" BOOLEAN = "boolean" ELEMENT_ID = "element_id"

@dataclass class ParameterMapping: """Mapping between Excel column and BIM parameter.""" excel_column: str bim_parameter: str update_type: UpdateType transform: Optional[str] = None # Optional transformation

@dataclass class UpdateResult: """Result of single element update.""" element_id: str parameters_updated: List[str] success: bool error: Optional[str] = None

@dataclass class BatchUpdateResult: """Result of batch update operation.""" total_elements: int updated: int failed: int skipped: int results: List[UpdateResult]

class ExcelToBIMUpdater: """Update BIM models from Excel data."""

# Standard ID column names
ID_COLUMNS = ['ElementId', 'GlobalId', 'GUID', 'Id', 'UniqueId']

def __init__(self):
    self.mappings: List[ParameterMapping] = []

def add_mapping(self, excel_col: str, bim_param: str,
                update_type: UpdateType = UpdateType.TEXT):
    """Add column to parameter mapping."""
    self.mappings.append(ParameterMapping(
        excel_column=excel_col,
        bim_parameter=bim_param,
        update_type=update_type
    ))

def load_excel(self, file_path: str,
               sheet_name: str = None) -> pd.DataFrame:
    """Load Excel data for update."""
    if sheet_name:
        return pd.read_excel(file_path, sheet_name=sheet_name)
    return pd.read_excel(file_path)

def detect_id_column(self, df: pd.DataFrame) -> Optional[str]:
    """Detect element ID column in DataFrame."""
    for col in self.ID_COLUMNS:
        if col in df.columns:
            return col
        # Case-insensitive check
        for df_col in df.columns:
            if df_col.lower() == col.lower():
                return df_col
    return None

def prepare_updates(self, df: pd.DataFrame,
                    id_column: str = None) -> List[Dict[str, Any]]:
    """Prepare update instructions from DataFrame."""

    if id_column is None:
        id_column = self.detect_id_column(df)
        if id_column is None:
            raise ValueError("Cannot detect ID column")

    updates = []

    for _, row in df.iterrows():
        element_id = str(row[id_column])

        params = {}
        for mapping in self.mappings:
            if mapping.excel_column in df.columns:
                value = row[mapping.excel_column]

                # Convert value based on type
                if mapping.update_type == UpdateType.NUMBER:
                    value = float(value) if pd.notna(value) else 0
                elif mapping.update_type == UpdateType.BOOLEAN:
                    value = bool(value) if pd.notna(value) else False
                elif mapping.update_type == UpdateType.TEXT:
                    value = str(value) if pd.notna(value) else ""

                params[mapping.bim_parameter] = value

        if params:
            updates.append({
                'element_id': element_id,
                'parameters': params
            })

    return updates

def generate_dynamo_script(self, updates: List[Dict],
                           output_path: str) -> str:
    """Generate Dynamo script for Revit updates."""

    # Generate Python code for Dynamo
    script = '''

Dynamo Python Script for Revit Parameter Updates

Generated by DDC Excel-to-BIM

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

Update data

updates = ''' script += json.dumps(updates, indent=2) script += '''

Apply updates

TransactionManager.Instance.EnsureInTransaction(doc)

results = [] for update in updates: try: element_id = int(update['element_id']) element = doc.GetElement(ElementId(element_id))

    if element:
        for param_name, value in update['parameters'].items():
            param = element.LookupParameter(param_name)
            if param and not param.IsReadOnly:
                if isinstance(value, (int, float)):
                    param.Set(float(value))
                elif isinstance(value, bool):
                    param.Set(1 if value else 0)
                else:
                    param.Set(str(value))
        results.append({'id': element_id, 'status': 'success'})
    else:
        results.append({'id': element_id, 'status': 'not found'})
except Exception as e:
    results.append({'id': update['element_id'], 'status': str(e)})

TransactionManager.Instance.TransactionTaskDone()

OUT = results '''

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

    return output_path

def generate_ifc_updates(self, updates: List[Dict],
                         original_ifc: str,
                         output_ifc: str) -> str:
    """Generate updated IFC file (requires IfcOpenShell)."""

    try:
        import ifcopenshell
    except ImportError:
        raise ImportError("IfcOpenShell required for IFC updates")

    ifc = ifcopenshell.open(original_ifc)

    for update in updates:
        guid = update['element_id']

        # Find element by GUID
        element = ifc.by_guid(guid)
        if not element:
            continue

        # Update properties
        for param_name, value in update['parameters'].items():
            # This is simplified - actual IFC property handling is more complex
            # Would need to find/create property sets and properties
            pass

    ifc.write(output_ifc)
    return output_ifc

def generate_update_report(self, original_df: pd.DataFrame,
                           updates: List[Dict],
                           output_path: str) -> str:
    """Generate report of planned updates."""

    report_data = []
    for update in updates:
        for param, value in update['parameters'].items():
            report_data.append({
                'element_id': update['element_id'],
                'parameter': param,
                'new_value': value
            })

    report_df = pd.DataFrame(report_data)
    report_df.to_excel(output_path, index=False)
    return output_path

class RevitExcelUpdater(ExcelToBIMUpdater): """Specialized updater for Revit via ImportExcelToRevit."""

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

def update_revit(self, excel_file: str,
                 rvt_file: str,
                 sheet_name: str = "Elements") -> BatchUpdateResult:
    """Update Revit file from Excel using CLI tool."""

    import subprocess

    # This assumes ImportExcelToRevit CLI tool
    cmd = [
        str(self.tool_path),
        rvt_file,
        excel_file,
        sheet_name
    ]

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

    # Parse results (format depends on tool output)
    if result.returncode == 0:
        return BatchUpdateResult(
            total_elements=0,  # Would parse from output
            updated=0,
            failed=0,
            skipped=0,
            results=[]
        )
    else:
        raise RuntimeError(f"Update failed: {result.stderr}")

class DataEnrichmentWorkflow: """Complete workflow for data enrichment and update."""

def __init__(self):
    self.updater = ExcelToBIMUpdater()

def enrich_and_update(self, original_excel: str,
                      enrichment_excel: str,
                      merge_column: str) -> pd.DataFrame:
    """Merge enrichment data with original export."""

    original = pd.read_excel(original_excel)
    enrichment = pd.read_excel(enrichment_excel)

    # Merge on specified column
    merged = original.merge(enrichment, on=merge_column, how='left',
                            suffixes=('', '_enriched'))

    return merged

def create_classification_mapping(self, df: pd.DataFrame,
                                  type_column: str,
                                  classification_file: str) -> pd.DataFrame:
    """Map BIM types to classification codes."""

    classifications = pd.read_excel(classification_file)

    # Fuzzy matching could be added here
    merged = df.merge(classifications,
                      left_on=type_column,
                      right_on='type_description',
                      how='left')

    return merged

Quick Start

Initialize updater

updater = ExcelToBIMUpdater()

Define mappings

updater.add_mapping('Classification_Code', 'OmniClassCode', UpdateType.TEXT) updater.add_mapping('Unit_Cost', 'Cost', UpdateType.NUMBER)

Load enriched Excel

df = updater.load_excel("enriched_model.xlsx")

Prepare updates

updates = updater.prepare_updates(df) print(f"Prepared {len(updates)} updates")

Generate Dynamo script for Revit

updater.generate_dynamo_script(updates, "update_parameters.py")

Common Use Cases

  1. Add Classification Codes

updater = ExcelToBIMUpdater() updater.add_mapping('Omniclass', 'OmniClass_Number', UpdateType.TEXT) updater.add_mapping('Uniclass', 'Uniclass_Code', UpdateType.TEXT)

df = updater.load_excel("classified_elements.xlsx") updates = updater.prepare_updates(df)

  1. Cost Data Integration

updater.add_mapping('Material_Cost', 'Pset_MaterialCost', UpdateType.NUMBER) updater.add_mapping('Labor_Cost', 'Pset_LaborCost', UpdateType.NUMBER)

  1. Generate Update Report

report = updater.generate_update_report(df, updates, "planned_updates.xlsx")

Integration with DDC Pipeline

Full round-trip: Revit → Excel → Enrich → Update → Revit

1. Export from Revit

RvtExporter.exe model.rvt complete

2. Enrich in Python/Excel

df = pd.read_excel("model.xlsx")

Add classifications, costs, etc.

df['OmniClass'] = df['Type Name'].map(classification_dict) df.to_excel("enriched_model.xlsx")

3. Generate update script

updater = ExcelToBIMUpdater() updater.add_mapping('OmniClass', 'OmniClass_Number') updates = updater.prepare_updates(df) updater.generate_dynamo_script(updates, "apply_updates.py")

4. Run in Dynamo to update Revit

Resources

  • GitHub: DDC Update Revit from Excel

  • DDC Book: Chapter 2.4 - Bidirectional Data Flow

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