Extract Model Properties Recipe

Complete guide to extracting metadata, properties, and geometry data from CAD models without viewing them

Goal

Extract structured data from CAD models (BIM properties, geometry info, material data, etc.) for analysis, reporting, or integration with other systems.

What you’ll achieve:

Extract element properties (doors, windows, walls, etc.)
Get model metadata (units, coordinate systems, etc.)
Export structured data to JSON, CSV, or database
Filter and search properties programmatically

Prerequisites

Required Tools

✅ RAPS CLI v4.2.0+ installed
✅ Autodesk Developer Account with app credentials
✅ CAD file uploaded to APS (any supported format)

Required Scopes

# Authentication scopes needed
data:read viewables:read

Understanding Property Extraction

APS Model Derivative API extracts properties in these formats:

Metadata - High-level model information
Properties - Element-by-element detailed properties
Hierarchy - Model structure and relationships

🔍 Click to see manual property extraction (40+ API calls)

```javascript const axios = require('axios'); // 1. Get model manifest async function getManifest(token, urn) { const response = await axios.get( `https://developer.api.autodesk.com/modelderivative/v2/designdata/${urn}/manifest`, { headers: { Authorization: `Bearer ${token}` }} ); return response.data; } // 2. Find metadata viewable function findMetadataViewable(manifest) { for (const derivative of manifest.derivatives) { for (const child of derivative.children || []) { if (child.role === 'Autodesk.CloudPlatform.PropertyDatabase') { return child.guid; } } } throw new Error('No metadata viewable found'); } // 3. Get model metadata async function getMetadata(token, urn, guid) { const response = await axios.get( `https://developer.api.autodesk.com/modelderivative/v2/designdata/${urn}/metadata/${guid}`, { headers: { Authorization: `Bearer ${token}` }} ); return response.data; } // 4. Get object tree async function getObjectTree(token, urn, guid) { const response = await axios.get( `https://developer.api.autodesk.com/modelderivative/v2/designdata/${urn}/metadata/${guid}/objects`, { headers: { Authorization: `Bearer ${token}` }} ); return response.data; } // 5. Get properties for each object (paginated) async function getAllProperties(token, urn, guid) { let allProperties = []; let hasMore = true; let offset = 0; const pageSize = 1000; while (hasMore) { const response = await axios.get( `https://developer.api.autodesk.com/modelderivative/v2/designdata/${urn}/metadata/${guid}/properties`, { headers: { Authorization: `Bearer ${token}` }, params: { offset, limit: pageSize } } ); allProperties = allProperties.concat(response.data.collection); hasMore = response.data.collection.length === pageSize; offset += pageSize; } return allProperties; } // 6. Process and structure data function processProperties(properties, metadata) { const structured = { modelInfo: metadata, elements: [], summary: { totalElements: 0, elementTypes: {}, materials: new Set(), levels: new Set() } }; for (const prop of properties) { const element = { dbId: prop.objectid, properties: {} }; // Process property groups for (const group of prop.properties) { for (const [key, value] of Object.entries(group.properties)) { element.properties[key] = value; // Track materials and levels if (key.toLowerCase().includes('material')) { structured.summary.materials.add(value); } if (key.toLowerCase().includes('level')) { structured.summary.levels.add(value); } } } structured.elements.push(element); // Track element types const category = element.properties.Category || 'Unknown'; structured.summary.elementTypes[category] = (structured.summary.elementTypes[category] || 0) + 1; } structured.summary.totalElements = structured.elements.length; structured.summary.materials = Array.from(structured.summary.materials); structured.summary.levels = Array.from(structured.summary.levels); return structured; } // Main workflow async function extractProperties(token, urn) { console.log('Getting manifest...'); const manifest = await getManifest(token, urn); console.log('Finding metadata viewable...'); const metadataGuid = findMetadataViewable(manifest); console.log('Getting model metadata...'); const metadata = await getMetadata(token, urn, metadataGuid); console.log('Getting object tree...'); const objectTree = await getObjectTree(token, urn, metadataGuid); console.log('Extracting all properties...'); const properties = await getAllProperties(token, urn, metadataGuid); console.log('Processing data...'); const structured = processProperties(properties, metadata); return structured; } ``` **That's complex pagination, GUID navigation, and data processing!**

The RAPS Way (3 Commands)

Step 1: Get Model Metadata

# Extract high-level model information
raps translate metadata <urn>

Output example:

{
  "metadata": {
    "name": "Office Building",
    "guid": "12345678-1234-5678-9abc-123456789012",
    "role": "3D",
    "units": "feet",
    "up_vector": [0, 0, 1],
    "front_vector": [0, 1, 0],
    "world_bounding_box": {
      "min": [-50, -30, 0],
      "max": [50, 30, 20]
    }
  }
}

Step 2: Extract All Properties

# Extract detailed element properties to JSON file
raps translate properties <urn> --output properties.json --format detailed

What happens:

Finds metadata viewable automatically
Downloads all properties with pagination handling
Structures data by element type
Saves to structured JSON format

Step 3: Generate Summary Report

# Create human-readable summary
raps translate properties <urn> --summary --output summary.csv

Output example (CSV):

Element_Type,Count,Average_Area,Total_Volume,Common_Materials
Wall,45,120.5,2850.0,"Concrete, Gypsum Board"
Door,12,21.0,0.0,"Wood, Steel"
Window,18,15.5,0.0,"Glass, Aluminum"

Extraction Workflows by File Type

BIM Models (Revit, ArchiCAD, IFC)

# Extract BIM-specific data
raps translate properties <rvt_urn> --filter-type "Walls,Doors,Windows,Floors" --include-materials --include-levels

Typical BIM Properties:

Element categories (Walls, Doors, Windows, etc.)
Material assignments
Level/Floor associations
Room/Space assignments
Phasing information
Type vs Instance parameters

Mechanical CAD (Inventor, SolidWorks)

# Extract mechanical properties
raps translate properties <ipt_urn> --filter-type "Parts,Assemblies" --include-mass --include-materials

Typical Mechanical Properties:

Part mass and volume
Material specifications
Assembly relationships
Custom iProperties/parameters
Manufacturing data

Civil/Infrastructure (Civil 3D, InfraWorks)

# Extract civil engineering data
raps translate properties <dwg_urn> --filter-type "Alignments,Surfaces,Corridors" --include-elevation

Typical Civil Properties:

Survey points and elevations
Alignment parameters
Surface definitions
Corridor assemblies
Pipe networks

Filtering and Searching Properties

Filter by Element Type

# Only extract doors and windows
raps translate properties <urn> --filter-category "Doors,Windows"

# Exclude structural elements
raps translate properties <urn> --exclude-category "Structural Framing,Structural Columns"

Filter by Property Values

# Only elements with specific material
raps translate properties <urn> --filter-property "Material=Concrete"

# Elements above certain level
raps translate properties <urn> --filter-property "Level=Level 2,Level 3"

Custom Property Queries

# Advanced filtering with queries
raps translate properties <urn> --query "Area > 100 AND Material CONTAINS 'Steel'"

Output Formats

1. Detailed JSON (Default)

raps translate properties <urn> --output model_data.json

Structure:

{
  "modelInfo": { ... },
  "elements": [
    {
      "dbId": 123,
      "category": "Walls",
      "properties": {
        "Name": "Interior Wall - Generic",
        "Area": 120.5,
        "Volume": 15.2,
        "Material": "Gypsum Board",
        "Level": "Level 1"
      }
    }
  ],
  "summary": { ... }
}

2. Flat CSV

raps translate properties <urn> --format csv --output elements.csv

Structure:

dbId,Category,Name,Area,Volume,Material,Level
123,Walls,Interior Wall - Generic,120.5,15.2,Gypsum Board,Level 1
124,Doors,Door - Single,21.0,0.0,Wood,Level 1

3. Excel Workbook

raps translate properties <urn> --format xlsx --output model_data.xlsx --include-charts

Creates workbook with:

Elements sheet - All property data
Summary sheet - Counts and totals by category
Materials sheet - Material usage analysis
Charts sheet - Visual summaries

4. Database Integration

# Insert directly into PostgreSQL
raps translate properties <urn> --to-database "postgresql://user:pass@localhost:5432/models"

# Insert into SQLite for local analysis
raps translate properties <urn> --to-database "sqlite:///models.db"

Advanced Property Analysis

Material Quantity Takeoff

# Generate material quantities report
raps translate properties <urn> --analyze materials --group-by "Material,Level" --calc "sum(Volume),sum(Area)"

Output:

{
  "materialAnalysis": [
    {
      "material": "Concrete",
      "level": "Level 1",
      "totalVolume": 1250.5,
      "totalArea": 2850.0,
      "elementCount": 25
    }
  ]
}

Cost Estimation Integration

# Extract data with cost parameters
raps translate properties <urn> --include-cost-params --apply-rates "rates.json"

Where rates.json contains:

{
  "materialRates": {
    "Concrete": { "unit": "cubic_foot", "rate": 0.12 },
    "Steel": { "unit": "pound", "rate": 0.85 }
  }
}

Space and Room Analysis

# Extract room/space data for space planning
raps translate properties <urn> --extract-spaces --include-boundaries --calc-adjacencies

Property Comparison and Change Detection

Compare Model Versions

# Compare properties between model versions
raps translate compare-properties <urn1> <urn2> --output changes.json

Output identifies:

Added elements
Deleted elements
Modified properties
Moved elements

Track Changes Over Time

# Store properties in version-controlled format
raps translate properties <urn> --output "properties_v$(date +%Y%m%d).json" --git-commit

Integration Examples

Python Data Analysis

import json
import pandas as pd

# Load RAPS extracted properties
with open('properties.json', 'r') as f:
    data = json.load(f)

# Convert to pandas DataFrame for analysis
elements_df = pd.json_normalize(data['elements'])

# Analyze by category
category_summary = elements_df.groupby('category').agg({
    'properties.Area': ['count', 'sum', 'mean'],
    'properties.Volume': ['sum', 'mean']
}).round(2)

print(category_summary)

# Find largest elements by area
largest_elements = elements_df.nlargest(10, 'properties.Area')[
    ['category', 'properties.Name', 'properties.Area']
]

print(largest_elements)

Power BI Integration

# Generate Power BI compatible format
raps translate properties <urn> --format powerbi --output model_data.pbix --include-relationships

Excel Analysis Template

# Create Excel template with formulas
raps translate properties <urn> --format xlsx --template analysis --output model_analysis.xlsx

The template includes:

Pivot tables for category analysis
Charts for material distribution
Formulas for cost calculations
Conditional formatting for outliers

Automation and Scheduling

Batch Property Extraction

# Extract properties from multiple models
raps translate properties-batch --bucket my-models --output-dir ./extracted_data/ --parallel 3

Scheduled Extraction

# Set up daily extraction for active projects
raps schedule properties-extraction --models @active_models.list --time "02:00" --output-format csv

CI/CD Integration

# GitHub Actions workflow
name: Extract Model Properties
on:
  push:
    paths: ['models/*.rvt']

jobs:
  extract:
    runs-on: ubuntu-latest
    steps:
      - name: Extract Properties
        run: |
          raps translate properties $ --output properties.json
          # Upload to data warehouse, trigger analysis pipeline, etc.

Performance Tips

1. Use Filters to Reduce Data Volume

# Extract only what you need
raps translate properties <urn> --filter-category "Walls,Doors" --exclude-properties "History,Constraints"

2. Parallelize Multiple Models

# Process multiple models simultaneously
raps translate properties-batch --models urn1,urn2,urn3 --parallel 3

3. Cache Expensive Operations

# Enable caching for repeated extractions
raps config set cache.properties-extraction true
raps config set cache.retention-days 7

4. Stream Large Datasets

# Stream properties to database for large models
raps translate properties <urn> --stream-to-database --batch-size 1000

Troubleshooting Common Issues

Issue 1: “No Properties Found”

Cause: Model needs translation first
Solution:

# Ensure model is translated
raps translate <urn> --formats properties --wait
# Then extract properties
raps translate properties <urn>

Issue 2: “Missing Properties for Some Elements”

Cause: Some CAD elements don’t have extractable properties
Solution:

# Check which elements have properties
raps translate properties <urn> --validate-elements --report-missing

Issue 3: “Properties Extraction Times Out”

Cause: Very large model with millions of elements
Solution:

# Use chunked extraction for large models
raps translate properties <urn> --chunked --chunk-size 10000 --timeout 600

Issue 4: “Inconsistent Property Names”

Cause: Different CAD software uses different property names
Solution:

# Apply property name mapping
raps translate properties <urn> --normalize-names --mapping property_mappings.json

Where property_mappings.json:

{
  "nameMapping": {
    "Type Name": "ElementType",
    "Host": "Parent",
    "Base Constraint": "Level"
  }
}

Use Cases

1. Quantity Surveying

# Generate material takeoff report
raps translate properties <urn> --analyze materials --group-by Material --calc "sum(Volume),sum(Area)" --output takeoff.xlsx

2. Space Programming

# Extract room data for space planning
raps translate properties <urn> --filter-category "Rooms,Spaces" --include-area --include-occupancy --output spaces.csv

3. Asset Management

# Extract equipment data for maintenance planning  
raps translate properties <urn> --filter-category "Mechanical Equipment,Electrical Equipment" --include-specs --output assets.json

4. Code Compliance

# Extract data for building code analysis
raps translate properties <urn> --filter-properties "Fire Rating,Occupancy,Exit Width" --validate-codes building_codes.json

Next Steps

Advanced Property Analysis

🔗 Try other recipes:
📊 Explore analytics:
- Time-series property tracking
- Multi-model comparisons
- Predictive maintenance models
🔌 Integrate with your tools:
- Business intelligence platforms
- ERP systems
- IoT sensor data

💡 Pro Tip: Combine property extraction with other APS APIs:

# Extract properties + generate viewer for context
raps translate properties <urn> --output data.json && raps view <urn> --highlight-elements @large_elements.json

Last verified: January 2026 | RAPS v4.2.1 | Model Derivative API v2
Property extraction works with all major BIM and CAD formats. For format-specific property schemas, see the APS Property Guide.

Extract Model Properties Recipe

Goal

Prerequisites

Required Tools

Required Scopes

Understanding Property Extraction

The Manual Way (Complex API Navigation)

The RAPS Way (3 Commands)

Step 1: Get Model Metadata

Step 2: Extract All Properties

Step 3: Generate Summary Report

Extraction Workflows by File Type

BIM Models (Revit, ArchiCAD, IFC)

Mechanical CAD (Inventor, SolidWorks)

Civil/Infrastructure (Civil 3D, InfraWorks)

Filtering and Searching Properties

Filter by Element Type

Filter by Property Values

Custom Property Queries

Output Formats

1. Detailed JSON (Default)

2. Flat CSV

3. Excel Workbook

4. Database Integration

Advanced Property Analysis

Material Quantity Takeoff

Cost Estimation Integration

Space and Room Analysis

Property Comparison and Change Detection

Compare Model Versions

Track Changes Over Time

Integration Examples

Python Data Analysis

Power BI Integration

Excel Analysis Template

Automation and Scheduling

Batch Property Extraction

Scheduled Extraction

CI/CD Integration

Performance Tips

1. Use Filters to Reduce Data Volume

2. Parallelize Multiple Models

3. Cache Expensive Operations

4. Stream Large Datasets

Troubleshooting Common Issues

Issue 1: “No Properties Found”

Issue 2: “Missing Properties for Some Elements”

Issue 3: “Properties Extraction Times Out”

Issue 4: “Inconsistent Property Names”

Use Cases

1. Quantity Surveying

2. Space Programming

3. Asset Management

4. Code Compliance

Next Steps

Advanced Property Analysis