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How to convert a Dynamo script to a Revit plugin

To convert a Dynamo script to a Revit plugin, you rewrite its logic against the Revit API, in Python with pyRevit or in C# as a full add-in, and give it a button, a dialog and a way to install. First, decide whether it needs converting at all.

When a Dynamo script is enough

  • You run it yourself, or a colleague who knows Dynamo does.
  • It runs now and then, not every day.
  • The logic still changes often. Dynamo is the fastest place to try ideas.
  • Colleagues only need to press run. Dynamo Player covers that with simple inputs.

Wondering whether AI has made Dynamo obsolete? Our take: Is Dynamo still relevant in the age of AI?

Signs it has outgrown Dynamo

  • People who never open Dynamo need to use it.
  • A Revit or Dynamo upgrade breaks it, often through a package it depends on.
  • It slows down or times out on large models.
  • It needs a proper dialog, input checks or a preview before it changes the model.
  • Running it again should update its earlier results, not duplicate them.
  • You want to hand it to a whole office, or sell it.

Two routes: pyRevit or a C# add-in

A pyRevit script is the shortest step. Dynamo nodes wrap the same Revit API that Python can call directly, so the logic carries over. The script becomes a ribbon button and is shared as a pyRevit extension; our free Biminent Tools are built this way. Every machine needs pyRevit installed, anyone with access can edit the scripts, and each new Revit version depends on the pyRevit project keeping up.

A C# add-in is the route for tools a team depends on. It gets its own ribbon panel, proper dialogs, an installer and updates, and it is the fastest option on large models. It needs a build for each group of Revit versions: Revit 2025 and later run on .NET 8, earlier versions on .NET Framework 4.8.

What converting involves

  • Mapping each group of nodes to Revit API calls, including anything a package did for you.
  • Managing transactions yourself. Dynamo opened them for you.
  • Selection and filtering the user can control, with sensible defaults.
  • Error handling, so one bad element does not stop the run or leave a half-finished result.
  • Testing on real project models, not only the one the script was written on.
  • Packaging, installing and updating it across the team.