Execution VsPyRevit

RevitDevTool And pyRevit

RevitDevTool and pyRevit overlap, but they optimize for different workflows.

pyRevit is strongest as a Revit automation and team deployment platform. RevitDevTool is strongest as a developer/research workflow for running, debugging, testing, and inspecting code inside Revit.

Quick Decision

I want to...	Better fit
give non-programmers ribbon buttons	pyRevit
maintain an existing pyRevit extension	pyRevit
run modern package-heavy Python	RevitDevTool
debug Python with VSCode breakpoints	RevitDevTool
quickly test Revit API scripts	RevitDevTool
visualize temporary geometry from script output	RevitDevTool
build repeatable team automation tools	pyRevit or compiled add-in
prototype data/AI/research workflows	RevitDevTool

Workflow Difference

Area	pyRevit	RevitDevTool
Main workflow	install extension, click ribbon button	write script, run, inspect, iterate
Audience	end users and automation teams	developers, researchers, power users
UI model	ribbon buttons and extension bundles	dockable panel, command tree, command browser
Python focus	pyRevit runtime choices, strong IronPython heritage	CPython package workflows plus first-class IronPython
Debugging	mostly print/pdb-style workflows	VSCode/debugpy attach workflow
Dependencies	extension/runtime dependent	script metadata with environment preparation
Visualization	script/tool specific	trace geometry can route to Revit visualization

How They Can Work Together

1. Prototype and debug a script in RevitDevTool.
2. Use Python packages or visualization while developing.
3. Stabilize the workflow.
4. Package the final tool as pyRevit, compiled .NET, or another deployment target if end users need a button.

RevitDevTool also has first-class IronPython execution. For IronPython scripts, pyRevit runtime support is a first-class path when available; when pyRevit is not available, RevitDevTool falls back to IronPython 3.4.2.

When To Choose RevitDevTool

• you are still exploring the algorithm;
• you need to inspect live Revit API objects in VSCode;
• package installation and dependency isolation matter;
• you need temporary geometry visualization during development;
• you are building/testing MCP or pytest bridge workflows.

When To Choose pyRevit

• the goal is polished team deployment;
• users only need a button and should not see development tooling;
• your automation is already a mature pyRevit extension;
• IT deployment is built around pyRevit extension folders;
• the script does not need modern Python packages or debugging.

Related

• Python Ecosystems For Revit
• Python Debugging With VSCode
• Modern Python Scripting
• Examples Overview