jupyterlab-trame-manager (previously known as jupyter-viz-extension or JuViz) is an extension for JupyterLab that enables the usage of ParaView trame within JupyterLab. It bridges Cloud and interactive Visualization, allowing users to run and control their customized visualization and analysis apps, written in trame, from inside the JupyterLab. It was written with Cloud-Computing and HPC in mind and is designed to be platform-independant.
For the extension, you only need 2 Components:
- JupyterLab >= 3.0
- JupyterServerProxy >= 3
The extension itself is not linked to any trame dependencies, as these are loaded at runtime when the app is launched.
To install the extension, execute:
pip install jupyterlab_trame_manager
The extension can be configured with different Configuration
classes. These contain the platform/architecture specific code
and can be used to configure how ParaView and trame Instances are launched, where trame app configs are stored, etc.
The Configuration
class is selected at runtime via the TRAME_MANAGER_CONFIGURATION
environment variable.
Existing Configuration
s can be found in the configurations sub-package
To start correctly, set the TRAME_MANAGER_CONFIGURATION
environment variable before starting JupyterLab:
export TRAME_MANAGER_CONFIGURATION=desktop
To add a trame app to the Extension that can be configured and executed in JupyterLab, you need to:
- Copy the App and all its Assets and required Files, to the Cluster.
- By default, it will look at all locations in the
JUPYTER_PATH
environment variable and try to detect apps that are in thetrame
subdirectory. - In most cases,
~/.local/share/jupyter/trame
is a valid location for alls - Put your trame app in a new subdirectory in the
trame
forder. For example:~/.local/share/jupyter/trame/my-app
- By default, it will look at all locations in the
- You now need to tell the Extension some details about your app and how it should be launched:
- Create a file called
app.yml
with the following values:- name: Display name of the App that is used in the UI
- working_directory: The working directory of a launched instance, i.e., from where the launch command should be executed
- command: The launch command to execute. This should: load all dependencies, prepare the environment and launch the app.
- The launch command will be passed some arguments for trame, which are generated by the extension before the launch (authentication key, etc.)
in the
TRAME_INSTANCE_ARGS
variable. These must be forwarded to trame when the app is started:python my-app/__init__.py $TRAME_INSTANCE_ARGS
- Create a file called
Thats it! Now your app should be available and launchable in the UI.
ToDo
To create a new Configuration
for a new system, create a new Python file in the configurations sub-package and
create a new class that inherits from jupyterlab_trame_manager.configurations.Configuration
(or any other Configuration
if desired).
Here you can override exiting methods of the class and customize, how things are executed. Take a look at the doc-strings
of the base Configuration
class for a more detailed explanation.
Note: You will need NodeJS to build the extension package.
The jlpm
command is JupyterLab's pinned version of yarn that is installed with JupyterLab. You may use yarn
or npm
in lieu of jlpm
below.
pip install -e "."
jupyter labextension develop . --overwrite
jupyter server extension enable jupyterlab_trame_manager
jlpm build
You can watch the source directory and run JupyterLab at the same time in different terminals to watch for changes in the extension's source and automatically rebuild the extension.
jlpm watch
# Run JupyterLab in another terminal
jupyter lab
With the watch command running, every saved change will immediately be built locally and available in your running JupyterLab. Refresh JupyterLab to load the change in your browser (you may need to wait several seconds for the extension to be rebuilt).