Python in BIM: Automating Door and Window Tagging in Township Projects

sdcstudio
5 days ago
2 min read

This blog is part of the SDC Knowledge Series – Episode 11, where we explore how Python scripting improves BIM efficiency in large-scale residential developments. This episode focuses on a townhome project and demonstrates how automation simplified door and window tagging across multiple repeating units.

The Challenge of Repetition in Township Projects

Township and townhome developments often involve multiple identical housing units repeated across several plots. While repetition helps standardize design, it also introduces a major BIM challenge—manual tagging.

In this project, every unit contained numerous doors and windows. Tagging each element manually across all units was:

Extremely time-consuming
Highly repetitive
Prone to inconsistencies and human error

As the number of units increased, maintaining accuracy became increasingly difficult using conventional workflows.

Why Manual Tagging Is Not Scalable

Manual tagging may work for small projects, but in large residential townships, it quickly becomes inefficient. Any design change required rechecking tags across multiple units, increasing the risk of:

Incorrect tag numbering
Missing or duplicated tags
Inconsistent documentation

To overcome these limitations, the team adopted Python scripting within Revit using pyRevit.

How Python Automated the Tagging Process

A custom Python script was developed to automatically tag doors and windows across all units. Instead of placing tags manually, the script:

Read element data directly from the BIM model
Applied consistent tags based on predefined rules
Ensured uniformity across all repeating units

This automated approach completed in minutes what previously took hours, while maintaining 100% consistency throughout the project.

Accuracy, Speed, and Consistency

Automation brought immediate improvements:

Significant time savings during documentation
Reduced human error by eliminating manual input
Standardized data across all units
Faster updates when design changes occurred

Because the script relied on model data rather than manual placement, the tagging remained accurate even as layouts evolved.

Scalability for Future Residential Projects

One of the biggest advantages of Python scripting is scalability.Whether the project includes 10 units or 100 units, the same script performs efficiently without additional effort.

This approach ensures:

Consistent BIM standards
Faster project turnaround
Improved quality control
More time for designers to focus on design and coordination

For large residential developments, automation becomes not just helpful—but essential.

Conclusion

Episode 11 of the SDC Knowledge Series demonstrates how SDC’s approach to BIM focuses on smart automation, consistency, and scalability. By leveraging Python scripting to automate door and window tagging in a township project, SDC transformed a repetitive and error-prone task into a streamlined, reliable workflow.

Rather than relying on manual effort, SDC prioritizes data-driven processes and custom automation that adapt easily to project scale and future design changes. This methodology not only improves accuracy and efficiency but also ensures that BIM standards remain consistent across large residential developments.