Collaborative CAD in JupyterLab
We are thrilled to introduce JupyterCAD, a tool that integrates Computer-Aided Design (CAD) capabilities into JupyterLab. With its JupyterLab extension, dedicated JupyterCAD application, and Python API for CAD operations, JupyterCAD allows users to effortlessly create, edit and share 3D designs without leaving the Jupyter ecosystem.
This blog post provides an overview of JupyterCAD’s features and highlights its collaborative editing capabilities which enable teamwork in the realm of CAD.
Everything that is shown below can be tested by installing JupyterCAD from PyPI:
# From PyPI
pip install jupytercadOne extension, three interfaces
Built using the latest JupyterLab 4 release, JupyterCAD combines CAD functionalities with the enhanced performance and accessibility improvements introduced in JupyterLab 4. The flexibility of JupyterLab allows us to create the extension once but deploy it in multiple ways to target three groups of audiences: users who prefer working in the JupyterLab environment, users who favor dedicated applications, and those advanced users who do everything programmatically.
JupyterLab Extension
Experience CAD features directly within JupyterLab with the JupyterCAD extension. Open and edit FreeCAD files, perform CAD operations, including creating 3D primitives, applying boolean operators, and exploding the view. JupyterCAD’s extension integrates seamlessly into JupyterLab, providing an intuitive environment for CAD enthusiasts and data scientists alike.
JupyterCAD Application
For a streamlined CAD experience, JupyterCAD offers a dedicated application that eliminates distractions and emphasizes CAD features.
Starting the dedicated JupyterCAD application is as simple as starting JupyterLab or Jupyter Notebook:
jupyter cadThis dedicated application has been built in a similar way to the coming Jupyter Notebook 7. It’s a JupyterLab “remix” built from the ground up using JupyterLab core components and custom extensions. Much like JupyterLab, it offers theming and localization support, and more planned features on the horizon.
Python API for CAD Operations
Advanced users can unlock the full potential of CAD operations with JupyterCAD’s Python API. JupyterCAD allows users to programmatically visualize, create, and manipulate the shapes from a Jupyter Notebook. For example, one can open a FreeCAD file and start modifying it from the notebook with:
from jupytercad import CadDocument
doc = CadDocument('example.FCStd')
# Create a cone, a sphere then cut the cone with the sphere.
doc.add_cone().add_sphere(radius=0.8).cut()
display(doc)
JupyterCAD API also integrates nicely with the OpenCascade Python API, providing expanded capabilities for working with shapes.
from jupytercad import CadDocument
...
# Create a prism shape with OpenCascade
prism = BRepPrimAPI_MakePrism(profile, vec).Shape()
doc = CadDocument()
doc.add_occ_shape(prism)
display(doc)
Unlocking teamwork with real-time collaboration
Collaborative Editing
One of the standout features of JupyterCAD is its shared editing functionality, which seamlessly connects users across different interfaces within the JupyterCAD ecosystem. Whether collaborators are using the dedicated JupyterCAD application, the JupyterLab extension, or working with the Python API in a Notebook, any changes made to a shared document are instantly reflected for all users.
Real-time collaboration allows individuals working in the Python API to make modifications to the CAD document, while simultaneously providing a synchronized view for collaborators using the JupyterLab extension or the JupyterCAD application. This ensures that all participants have access to the most up-to-date version of the design, fostering efficient communication and eliminating the need for manual synchronization or file exchange.
Follow Mode
With JupyterCAD’s follow-mode feature, collaboration becomes even more fluid. You can follow another user’s camera movements and view adjustments in real-time. This mode allows you to gain insights into the design process, and enhance communication among team members.
Annotations System
The annotations system in JupyterCAD adds an interactive layer to 3D designs. Now you can add annotations to specific shapes within a CAD file, give context, provide feedback, or write instructions.
What goes on under the hood?
All the above features are made possible thanks to two major open-source components: OpenCascade.js, the WebAssembly build of OpenCascade, and jupyter_collaboration, the real-time collaboration framework of JupyterLab.
In-browser geometric modeling kernel
To execute all geometric operations, JupyterCAD uses a custom build of OpenCascade.js, which is a port of the OpenCascade library to JavaScript and WebAssembly via Emscripten. Running on a separate thread, the CAD Kernel of JupyterCAD allows users to perform complex operations at near-native speed. It also helps to lower the load of the server while serving JupyterCAD to many users.
JupyterLab Real-Time Collaboration framework
In JupyterLab 4, Real-Time Collaboration (RTC) is not only about editing notebooks but it has become a framework for building collaborative applications. Using the components of jupyter_collaboration helps us accelerate the development of the RTC features in JupyterCAD. Collaborative Editing is built upon a shared data model where jupyter_collaboration handles all the transportation and conflict resolution, while Follow Mode makes use of Awareness, a lightweight notification system provided by the library.
Future work
The current state of JupyterCAD illustrates the capabilities of JupyterLab as a foundation to build complex applications, not just for scientific computing but also for more general technical computing applications.
We will continue to improve JupyterCAD on two axes:
- Enhancing the 3D viewer with features to help users interact with the objects
- Enriching the Python API to improve interoperability with other CAD libraries
We plan on upstreaming some of the features of JupyterCAD, like the annotations system and the Follow Mode, to jupyter_collaboration to enable it in other file contexts in JupyterLab (Notebooks, text files, etc).
User feedback from the community also plays a big role in the project roadmap. Try JupyterCAD and share your feedback with us using the project’s GitHub issues!
About the Authors
Le Duc Trung is a Scientific Software Developer at QuantStack. He works on several projects within the Jupyter ecosystem, from the main projects like JupyterLab, Voilà, and ipywidgets to various JupyterLab extensions and widgets.
Martin Renou is a Technical Director at QuantStack and a maintainer of Project Jupyter. Among other projects Martin is a core team member of the ipywidgets project and maintains many Jupyter widget packages such as ipyleaflet, ipydatagrid, ipygany, ipycanvas, and bqplot. He is a co-creator of the Voilà dashboarding system, and the xeus-python kernel.
