A JupyterLab Code Assistant
Project description
trelis
A JupyterLab Code Assistant
Requirements
- JupyterLab >= 4.0.0
- Node >= 22.6
- Yarn
Install
To install the extension, execute:
pip install trelis
to install with node and yarn (for example, in a remote GPU server like RunPod), first run:
import os
import subprocess
def check_node_yarn():
# Check if Node.js is installed
try:
node_version = subprocess.check_output(["node", "--version"]).decode().strip()
print(f"Node.js is installed: {node_version}")
except FileNotFoundError:
print("Node.js is not installed.")
install_node()
# Check if Yarn is installed
try:
yarn_version = subprocess.check_output(["yarn", "--version"]).decode().strip()
print(f"Yarn is installed: {yarn_version}")
except FileNotFoundError:
print("Yarn is not installed.")
install_yarn()
def install_node():
print("Installing Node.js...")
# Download Node.js binary (you can change the version if needed)
os.system("curl -O https://nodejs.org/dist/v22.6.0/node-v22.6.0-linux-x64.tar.xz --silent")
# Extract Node.js
os.system("tar -xf node-v22.6.0-linux-x64.tar.xz --no-same-owner")
# Add Node.js to the PATH for the current notebook session
node_bin_path = os.path.abspath("node-v22.6.0-linux-x64/bin")
os.environ['PATH'] = node_bin_path + ":" + os.environ['PATH']
print(f"Node.js installed to {node_bin_path}")
# Verify installation
node_version = subprocess.check_output(["node", "--version"]).decode().strip()
print(f"Node.js version: {node_version}")
def install_yarn():
print("Installing Yarn...")
# Install Yarn via script
os.system("curl -o- -L https://yarnpkg.com/install.sh | bash")
# Add Yarn to the PATH for the current notebook session
yarn_bin_path = os.path.expanduser("~/.yarn/bin")
os.environ['PATH'] = yarn_bin_path + ":" + os.environ['PATH']
print(f"Yarn installed to {yarn_bin_path}")
# Verify installation
yarn_version = subprocess.check_output(["yarn", "--version"]).decode().strip()
print(f"Yarn version: {yarn_version}")
# Run the check and installation process
check_node_yarn()
Uninstall
To remove the extension, execute:
pip uninstall trelis
Contributing (Private)
Development install
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.
First:
conda create -n jupyterlab-ext --override-channels --strict-channel-priority -c conda-forge -c nodefaults jupyterlab=4 nodejs=20 git copier=9 jinja2-time
then:
conda activate jupyterlab-ext
Or just:
cd trelis-jupyter-assistant
python -m venv jupyterlab-ext
source jupyterlab-ext/bin/activate
Then:
Then, run:
npm install -g yarn yarn install pip install -ve . jupyter labextension develop --overwrite . pip install jupyterlab jlpm jlpm build jlpm watch
This will watch the source directory and allow you to run JupyterLab at the same time in different terminals to watch for changes in the extension's source and automatically rebuild the extension.
```bash
# Watch the source directory in one terminal, automatically rebuilding when needed
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).
By default, the jlpm build command generates the source maps for this extension to make it easier to debug using the browser dev tools. To also generate source maps for the JupyterLab core extensions, you can run the following command:
jupyter lab build --minimize=False
Development uninstall
pip uninstall trelis
In development mode, you will also need to remove the symlink created by jupyter labextension develop
command. To find its location, you can run jupyter labextension list to figure out where the labextensions
folder is located. Then you can remove the symlink named trelis-jupyter-assistant within that folder.
Testing the extension
Frontend tests
This extension is using Jest for JavaScript code testing.
To execute them, execute:
jlpm
jlpm test
Integration tests
This extension uses Playwright for the integration tests (aka user level tests). More precisely, the JupyterLab helper Galata is used to handle testing the extension in JupyterLab.
More information are provided within the ui-tests README.
Packaging the extension
See RELEASE
Project details
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