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dwg-to-excel — Claude Code skill: what it does, how to install

Converts AutoCAD DWG files into structured Excel databases and PDFs using the DwgExporter CLI. Useful for extracting layers, blocks, and geometry data without an Autodesk license.

Install into Claude Code · Skills CLI (Vercel) All methods and platforms ↓
npx skills add datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction --skill dwg-to-excel -a claude-code
Open on GitHub

What dwg-to-excel does

This skill guides coding agents through exporting drawing data from AutoCAD DWG files across versions from 1983 to 2026. The extraction captures layer hierarchies, block references with attributes, text annotations, dimensions, and geometric entities. Passing the sheets2pdf argument also generates PDF files directly from drawing layouts.

The tool relies on the DwgExporter.exe command-line utility paired with a Python script powered by pandas. The script opens the Elements sheet, summarizes entity counts, and groups block definitions. All operations run offline on your machine.

Running this requires a Windows operating system, python3, and the DwgExporter.exe executable present in your environment. Attempting to use this on Linux or macOS will fail immediately because of the win32 binary requirement.

What it helps with

  • extract layers, block attributes, and geometry from DWG files into Excel
  • export AutoCAD drawing layouts to PDF files without AutoCAD
  • batch process folders of legacy and modern DWG files
  • inspect CAD drawing metadata without purchasing Autodesk licenses

Example prompts for the agent

  • Convert C:\Projects\FloorPlan.dwg to Excel and export sheets to PDF
  • Batch convert all DWG files in C:\Projects using DwgExporter
  • Parse layers and block attributes from FloorPlan.xlsx using Python

How to install dwg-to-excel

1Skills CLI (Vercel)

npx skills add datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction --skill dwg-to-excel -a claude-code

2Manually: put the files in place

~/.claude/skills/dwg-to-excel/SKILL.md

Copy the whole skill folder; for one project use .claude/skills/dwg-to-excel/

Step by step, with commands for each platform: How to install skills in Claude Code: five ways

Questions about dwg-to-excel

How to install dwg-to-excel in Claude Code?

Run npx skills add datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction --skill dwg-to-excel -a claude-code in your terminal. This registers the skill commands and instructions with Claude Code.

What does dwg-to-excel do?

It uses the DwgExporter CLI to export DWG files from 1983 to 2026 into .xlsx spreadsheets and layout PDFs. It parses geometry, annotations, layers, and block data without CAD software.

What are the requirements for dwg-to-excel?

It requires a Windows environment, Python 3, and the DwgExporter.exe binary. No Autodesk license or installation is needed.

Source text

SKILL.md · MIT
---
name: "dwg-to-excel"
description: "Convert AutoCAD DWG files (1983-2026) to Excel databases using DwgExporter CLI. Extract layers, blocks, attributes, and geometry data without Autodesk licenses."
homepage: "https://datadrivenconstruction.io"
metadata: {"openclaw":{"emoji":"📄","os":["win32"],"homepage":"https://datadrivenconstruction.io","requires":{"bins":["python3","DwgExporter"]}}}
---

# DWG to Excel Conversion

## Business Case

### Problem Statement
AutoCAD DWG files contain valuable project data locked in proprietary format:
- Layer structures with drawing organization
- Block references with attribute data
- Text annotations and dimensions
- Geometric entities (lines, polylines, arcs)
- External references (xrefs)

Extracting this data typically requires AutoCAD licenses or complex programming.

### Solution
DwgExporter.exe converts DWG files to structured Excel databases offline, without Autodesk licenses.

### Business Value
- **Zero license cost** - No AutoCAD license required
- **Legacy support** - Reads DWG files from 1983 to 2026
- **Data extraction** - Layers, blocks, attributes, text, geometry
- **PDF export** - Generate drawings from DWG layouts
- **Batch processing** - Convert thousands of DWG files

## Technical Implementation

### CLI Syntax
```bash
DwgExporter.exe <input_dwg> [options]
```

### Output Formats
| Output | Description |
|--------|-------------|
| `.xlsx` | Excel database with all entities |
| `.pdf` | PDF drawings from layouts |

### Supported Versions
| Version Range | Description |
|---------------|-------------|
| R12 (1992) | Legacy DWG |
| R14 (1997) | AutoCAD 14 |
| 2000-2002 | DWG 2000 format |
| 2004-2006 | DWG 2004 format |
| 2007-2009 | DWG 2007 format |
| 2010-2012 | DWG 2010 format |
| 2013-2017 | DWG 2013 format |
| 2018-2026 | DWG 2018 format |

### Examples

```bash
# Basic conversion
DwgExporter.exe "C:\Projects\FloorPlan.dwg"

# Export with PDF drawings
DwgExporter.exe "C:\Projects\FloorPlan.dwg" sheets2pdf

# Batch processing all DWG in folder
for /R "C:\Projects" %f in (*.dwg) do DwgExporter.exe "%f"

# PowerShell batch conversion
Get-ChildItem "C:\Projects\*.dwg" -Recurse | ForEach-Object {
    & "C:\DDC\DwgExporter.exe" $_.FullName
}
```

### Python Integration

```python
import subprocess
import pandas as pd
from pathlib import Path
from typing import List, Optional, Dict, Any
from dataclasses import dataclass
from enum import Enum


class DWGEntityType(Enum):
    """DWG entity types."""
    LINE = "LINE"
    POLYLINE = "POLYLINE"
    LWPOLYLINE = "LWPOLYLINE"
    CIRCLE = "CIRCLE"
    ARC = "ARC"
    ELLIPSE = "ELLIPSE"
    SPLINE = "SPLINE"
    TEXT = "TEXT"
    MTEXT = "MTEXT"
    DIMENSION = "DIMENSION"
    INSERT = "INSERT"  # Block reference
    HATCH = "HATCH"
    SOLID = "SOLID"
    POINT = "POINT"
    ATTRIB = "ATTRIB"
    ATTDEF = "ATTDEF"


@dataclass
class DWGEntity:
    """Represents a DWG entity."""
    handle: str
    entity_type: str
    layer: str
    color: int
    linetype: str
    lineweight: float

    # Geometry (depends on entity type)
    start_x: Optional[float] = None
    start_y: Optional[float] = None
    end_x: Optional[float] = None
    end_y: Optional[float] = None

    # Block reference data
    block_name: Optional[str] = None
    rotation: Optional[float] = None
    scale_x: Optional[float] = None
    scale_y: Optional[float] = None

    # Text data
    text_content: Optional[str] = None
    text_height: Optional[float] = None


@dataclass
class DWGBlock:
    """Represents a DWG block definition."""
    name: str
    base_point_x: float
    base_point_y: float
    entity_count: int
    is_dynamic: bool
    attributes: List[str]


@dataclass
class DWGLayer:
    """Represents a DWG layer."""
    name: str
    color: int
    linetype: str
    is_on: bool
    is_frozen: bool
    is_locked: bool
    lineweight: float
    entity_count: int


class DWGExporter:
    """DWG to Excel converter using DDC DwgExporter CLI."""

    def __init__(self, exporter_path: str = "DwgExporter.exe"):
        self.exporter = Path(exporter_path)
        if not self.exporter.exists():
            raise FileNotFoundError(f"DwgExporter not found: {exporter_path}")

    def convert(self, dwg_file: str,
                export_pdf: bool = False) -> Path:
        """Convert DWG file to Excel."""
        dwg_path = Path(dwg_file)
        if not dwg_path.exists():
            raise FileNotFoundError(f"DWG file not found: {dwg_file}")

        cmd = [str(self.exporter), str(dwg_path)]
        if export_pdf:
            cmd.append("sheets2pdf")

        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
        return dwg_path.with_suffix('.xlsx')

    def batch_convert(self, folder: str,
                      include_subfolders: bool = True,
                      export_pdf: bool = False) -> List[Dict[str, Any]]:
        """Convert all DWG files in folder."""
        folder_path = Path(folder)
        pattern = "**/*.dwg" if include_subfolders else "*.dwg"

        results = []
        for dwg_file in folder_path.glob(pattern):
            try:
                output = self.convert(str(dwg_file), export_pdf)
                results.append({
                    'input': str(dwg_file),
                    'output': str(output),
                    'status': 'success'
                })
                print(f"✓ Converted: {dwg_file.name}")
            except Exception as e:
                results.append({
                    'input': str(dwg_file),
                    'output': None,
                    'status': 'failed',
                    'error': str(e)
                })
                print(f"✗ Failed: {dwg_file.name} - {e}")

        return results

    def read_entities(self, xlsx_file: str) -> pd.DataFrame:
        """Read converted Excel as DataFrame."""
        xlsx_path = Path(xlsx_file)
        if not xlsx_path.exists():
            raise FileNotFoundError(f"Excel file not found: {xlsx_file}")

        return pd.read_excel(xlsx_file, sheet_name="Elements")

    def get_layers(self, xlsx_file: str) -> pd.DataFrame:
        """Get layer summary from converted file."""
        df = self.read_entities(xlsx_file)

        if 'Layer' not in df.columns:
            raise ValueError("Layer column not found in data")

        summary = df.groupby('Layer').agg({
            'Handle': 'count'
        }).reset_index()
        summary.columns = ['Layer', 'Entity_Count']
        return summary.sort_values('Entity_Count', ascending=False)

    def get_blocks(self, xlsx_file: str) -> pd.DataFrame:
        """Get block reference summary."""
        df = self.read_entities(xlsx_file)

        # Filter to INSERT entities (block references)
        blocks = df[df['EntityType'] == 'INSERT']

        if blocks.empty:
            return pd.DataFrame(columns=['Block_Name', 'Count'])

        summary = blocks.groupby('BlockName').agg({
            'Handle': 'count'
        }).reset_index()
        summary.columns = ['Block_Name', 'Count']
        return summary.sort_values('Count', ascending=False)

    def get_text_content(self, xlsx_file: str) -> pd.DataFrame:
        """Extract all text content from DWG."""
        df = self.read_entities(xlsx_file)

        # Filter to text entities
        text_types = ['TEXT', 'MTEXT', 'ATTRIB']
        texts = df[df['EntityType'].isin(text_types)]

        if 'TextContent' in texts.columns:
            return texts[['Handle', 'EntityType', 'Layer', 'TextContent']].copy()
        return texts[['Handle', 'EntityType', 'Layer']].copy()

    def get_entity_statistics(self, xlsx_file: str) -> Dict[str, int]:
        """Get entity type statistics."""
        df = self.read_entities(xlsx_file)

        if 'EntityType' not in df.columns:
            return {}

        return df['EntityType'].value_counts().to_dict()

    def extract_block_attributes(self, xlsx_file: str,
                                  block_name: str) -> pd.DataFrame:
        """Extract attributes from specific block type."""
        df = self.read_entities(xlsx_file)

        # Find block references
        blocks = df[(df['EntityType'] == 'INSERT') &
                    (df['BlockName'] == block_name)]

        # Find associated attributes
        # Attributes typically follow their parent INSERT in handle order
        result_data = []

        for _, block in blocks.iterrows():
            block_handle = block['Handle']
            block_data = {
                'Block_Handle': block_handle,
                'X': block.get('InsertX', 0),
                'Y': block.get('InsertY', 0),
                'Rotation': block.get('Rotation', 0)
            }

            # Add any attribute columns
            for col in df.columns:
                if col.startswith('Attr_'):
                    block_data[col] = block.get(col)

            result_data.append(block_data)

        return pd.DataFrame(result_data)


class DWGAnalyzer:
    """Advanced DWG analysis tools."""

    def __init__(self, exporter: DWGExporter):
        self.exporter = exporter

    def analyze_drawing_structure(self, dwg_file: str) -> Dict[str, Any]:
        """Analyze complete drawing structure."""
        xlsx = self.exporter.convert(dwg_file)
        df = self.exporter.read_entities(str(xlsx))

        analysis = {
            'file': dwg_file,
            'total_entities': len(df),
            'layers': self.exporter.get_layers(str(xlsx)).to_dict('records'),
            'entity_types': self.exporter.get_entity_statistics(str(xlsx)),
            'blocks': self.exporter.get_blocks(str(xlsx)).to_dict('records')
        }

        # Calculate extents if coordinates available
        if 'X' in df.columns and 'Y' in df.columns:
            analysis['extents'] = {
                'min_x': df['X'].min(),
                'max_x': df['X'].max(),
                'min_y': df['Y'].min(),
                'max_y': df['Y'].max()
            }

        return analysis

    def compare_drawings(self, dwg1: str, dwg2: str) -> Dict[str, Any]:
        """Compare two DWG files."""
        xlsx1 = self.exporter.convert(dwg1)
        xlsx2 = self.exporter.convert(dwg2)

        df1 = self.exporter.read_entities(str(xlsx1))
        df2 = self.exporter.read_entities(str(xlsx2))

        layers1 = set(df1['Layer'].unique()) if 'Layer' in df1.columns else set()
        layers2 = set(df2['Layer'].unique()) if 'Layer' in df2.columns else set()

        return {
            'file1': dwg1,
            'file2': dwg2,
            'entity_count_diff': len(df2) - len(df1),
            'layers_added': list(layers2 - layers1),
            'layers_removed': list(layers1 - layers2),
            'common_layers': list(layers1 & layers2)
        }

    def find_duplicates(self, xlsx_file: str,
                        tolerance: float = 0.001) -> pd.DataFrame:
        """Find duplicate entities at same location."""
        df = self.exporter.read_entities(xlsx_file)

        if 'X' not in df.columns or 'Y' not in df.columns:
            return pd.DataFrame()

        # Round coordinates for grouping
        df['X_rounded'] = (df['X'] / tolerance).round() * tolerance
        df['Y_rounded'] = (df['Y'] / tolerance).round() * tolerance

        # Find duplicates
        duplicates = df[df.duplicated(
            subset=['EntityType', 'Layer', 'X_rounded', 'Y_rounded'],
            keep=False
        )]

        return duplicates.sort_values(['X_rounded', 'Y_rounded'])


# Convenience functions
def convert_dwg_to_excel(dwg_file: str,
                         exporter_path: str = "DwgExporter.exe") -> str:
    """Quick conversion of DWG to Excel."""
    exporter = DWGExporter(exporter_path)
    output = exporter.convert(dwg_file)
    return str(output)


def batch_convert_dwg(folder: str,
                      exporter_path: str = "DwgExporter.exe",
                      include_subfolders: bool = True) -> List[str]:
    """Batch convert all DWG files in folder."""
    exporter = DWGExporter(exporter_path)
    results = exporter.batch_convert(folder, include_subfolders)
    return [r['output'] for r in results if r['status'] == 'success']
```

## Output Structure

### Excel Sheets
| Sheet | Content |
|-------|---------|
| Elements | All DWG entities with properties |
| Layers | Layer definitions |
| Blocks | Block definitions |
| Layouts | Drawing layouts/sheets |

### Entity Columns
| Column | Type | Description |
|--------|------|-------------|
| Handle | string | Unique entity handle |
| EntityType | string | LINE, CIRCLE, INSERT, etc. |
| Layer | string | Layer name |
| Color | int | Color index (0-256) |
| Linetype | string | Linetype name |
| Lineweight | float | Line weight in mm |
| X, Y, Z | float | Entity coordinates |
| BlockName | string | For INSERT entities |
| TextContent | string | For TEXT/MTEXT |

## Quick Start

```python
# Initialize exporter
exporter = DWGExporter("C:/DDC/DwgExporter.exe")

# Convert single file
xlsx = exporter.convert("C:/Projects/Plan.dwg")
print(f"Output: {xlsx}")

# Read and analyze
df = exporter.read_entities(str(xlsx))
print(f"Total entities: {len(df)}")

# Get layer statistics
layers = exporter.get_layers(str(xlsx))
print(layers)

# Get block usage
blocks = exporter.get_blocks(str(xlsx))
print(blocks)

# Extract text annotations
texts = exporter.get_text_content(str(xlsx))
for _, row in texts.iterrows():
    print(f"{row['Layer']}: {row.get('TextContent', 'N/A')}")
```

## Common Use Cases

### 1. Layer Audit
```python
exporter = DWGExporter()
xlsx = exporter.convert("drawing.dwg")
layers = exporter.get_layers(str(xlsx))

# Check for non-standard layers
standard_layers = ['0', 'WALLS', 'DOORS', 'WINDOWS', 'DIMENSIONS']
non_standard = layers[~layers['Layer'].isin(standard_layers)]
print("Non-standard layers:", non_standard['Layer'].tolist())
```

### 2. Block Schedule
```python
# Extract all door blocks with attributes
doors = exporter.extract_block_attributes(str(xlsx), "DOOR")
print(doors[['Block_Handle', 'Attr_DOOR_TYPE', 'Attr_DOOR_SIZE']])
```

### 3. Drawing Comparison
```python
analyzer = DWGAnalyzer(exporter)
diff = analyzer.compare_drawings("rev1.dwg", "rev2.dwg")
print(f"Entities added: {diff['entity_count_diff']}")
print(f"New layers: {diff['layers_added']}")
```

## Integration with DDC Pipeline

```python
# Full pipeline: DWG → Excel → Analysis → Report
from dwg_exporter import DWGExporter, DWGAnalyzer

# 1. Convert DWG
exporter = DWGExporter("C:/DDC/DwgExporter.exe")
xlsx = exporter.convert("project.dwg")

# 2. Analyze structure
analyzer = DWGAnalyzer(exporter)
analysis = analyzer.analyze_drawing_structure("project.dwg")

# 3. Generate report
print(f"Drawing: {analysis['file']}")
print(f"Entities: {analysis['total_entities']}")
print(f"Layers: {len(analysis['layers'])}")
print(f"Blocks: {len(analysis['blocks'])}")
```

## Best Practices

1. **Check DWG version** - Older files may have limited data
2. **Validate layer structure** - Clean up before processing
3. **Handle external references** - Bind xrefs if needed
4. **Batch overnight** - Large files take time
5. **Verify entity counts** - Compare with AutoCAD if possible

## Resources

- **GitHub**: [cad2data Pipeline](https://github.com/datadrivenconstruction/cad2data-Revit-IFC-DWG-DGN-pipeline-with-conversion-validation-qto)
- **Video Tutorial**: [DWG to Excel Pipeline](https://www.youtube.com/watch?v=jVU7vlMNTO0)
- **DDC Book**: Chapter 2.4 - CAD Data Extraction

© datadrivenconstruction · MIT · datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction

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