Development Workflow¶
This section describes the steps necessary to build Elyra in a development environment.
Requirements¶
Setting up your development environment¶
Install Miniconda Download and install a Python 3 version of Miniconda according to your Operating System
Create a new Python environment
conda create -n <env-name> python
The python version of your environment will match the miniconda version you installed. You can override the default by explicitly setting
python=3.7
, for example.Activate the new environment
conda activate <env-name>
Verify your miniconda environment
python --version which python # Displays current python path pip --version which pip
Python path must be under miniconda envs folder. Confirm pip location matches where miniconda is installed.
Install NodeJS
conda install -y -c conda-forge/label/main nodejs
Setting up your Elyra Github repository¶
Fork the Elyra Github repository (if you haven’t already)
Make a local copy of Elyra fork
git clone https://github.com/<your-github-id>/elyra.git cd elyra
Set
upstream
as described in the GitHub documentation
Building¶
Elyra is divided in two parts, a collection of Jupyter Notebook backend extensions,
and their respective JupyterLab UI extensions. Our JupyterLab extensions are located in our packages
directory.
Build & Installation¶
Elyra uses make
to automate some of the development workflow tasks.
Issuing a make
command with no task specified will provide a list of the currently supported tasks.
$ make
build-server Build backend
build-ui Build packages
clean Make a clean source tree and uninstall extensions
docker-image Build docker image
docs Build docs
install-server Install backend
install Build and install
lint Run linters
release Build wheel file for release
test-server Run unit tests
test-ui Run frontend tests
test Run all tests
validate-runtime-images Validates delivered runtime-images meet minimum criteria
watch Watch packages. For use alongside jupyter lab --watch
You can build and install all Elyra packages with:
make clean install
You can check that the notebook server extension was successful installed with:
jupyter serverextension list
You can check that the JupyterLab extension was successful installed with:
jupyter labextension list
NOTE: When switching between Elyra major versions, it is recommended to clean your JupyterLab environment before a build. Theclean-jupyterlab
removes your JupyterLab packages and completely deletes your Jupyter workspace. Make sure to backup any important data in your environment before running the script. To clean your environment and install the latest JupyterLab:etc/scripts/clean-jupyterlab.sh
To specify a JupyterLab version to be installed:etc/scripts/clean-jupyterlab.sh --version 2.2.9
Incremental Development¶
Elyra supports incremental development using --watch
. This allows you to make code changes to
front-end packages and see them without running make install
again.
After installation run the following to watch for code changes and rebuild automatically:
make watch
Then in a separate terminal, using the same Python environment, start JupyterLab in watch mode:
jupyter lab --watch
When in watch mode JupyterLab will watch for changes in the build of each package and rebuild. To see your changes just refresh JupyterLab in your browser.
NOTE: JupyterLab watch mode will not pick up changes in package dependencies likeservices
. So when making changes to services you will need to stop and restartjupyter lab --watch
and not just refresh your browser.
Building the Elyra Container Image¶
Elyra’s container image can be built using:
make container-image
Official container images are published on Docker Hub and quay.io.