Detalle del Skill

excel-to-bim

Updates construction BIM properties from spreadsheet data.

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Fuentedatadrivenconstruction/ddc_skills_for_ai_agents_in_constructionFuente externa
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---
name: "excel-to-bim"
description: "Push Excel data back to BIM models. Update parameters, properties, and attributes from structured spreadsheets."
homepage: "https://datadrivenconstruction.io"
metadata: {"openclaw": {"emoji": "📄", "os": ["win32"], "homepage": "https://datadrivenconstruction.io", "requires": {"bins": ["python3"], "anyBins": ["ifcopenshell"]}}}
---
# 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

```python
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]

    
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