Package: gquantlab
gquantlabgQuant jupyterlab extensionThe gQuant Juyterlab extension provides the user interface to build the dataframe flow TaskGraph easily. It takes advantage of the open sources projects likejupyterlab,ipywidget,ReactandD3. It features:Takes full advantage of the JupyterLab project that the extension adds commands to Jupyterlab context menu, command palette and bind them with keyboard shortcuts to speed up the productivity.Define a new TaskGraph file format.gq.yamlthat can be edited in the Jupyterlab.Visually presents the TaskGraph as a DAG graph. Users can zoom in and out, freely move the nodes around, and make connections between nodes.Use the specialOuput Collectorto gather the results and organize them in a tab widget. The IPythonrich displayis fully supported.Visually shows the progress of graph evaluation and computation dependence.Automatically generate the UI elements to edit and validate the Node configuration given the configuration JSON schema. It exposes the function API in a user-friendly way. User can change the configuration and re-run the computation to test out the hyperparameters easily.Dynamically compute the input-output ports compatibility, dataframe columns names and types, ports types to prevent connection errors.Nodes can have multiple output ports that can be used to generate different output types. E.g. some data loader Node provides bothcudfanddask_cudfoutput ports. The multiple GPUs distributed computation computation is automatically enabled by switching to thedask_cudfoutput port.Provides the standard API to extend your computation Nodes.The composite node can encapsulate the TaskGraph into a single node for easy reuse. The composite node can be exported as a regular gQuant node without any coding.This extension is composed of a Python package namedgquantlabfor the server extension and a NPM package namedgquantlabfor the frontend extension.Build the dev containerIn the gQuant root directionbashdocker/build.shLaunch your development container, make sure mounting your gQuant directory
to the container and open8888ports.Set the gQuant path as the folder to start the development or you can open theworkspace.code-workspacefile.RequirementsJupyterLab >= 2.0InstallNote: You will need NodeJS of version 12^14^15 to install the extension.pipinstallgquantlabTroubleshootIf you are seeing the frontend extension but it is not working, check
that the server extension is enabled:jupyterserverextensionlistIf the server extension is installed and enabled but you are not seeing
the frontend, check the frontend is installed:jupyterlabextensionlistIf it is installed, try:jupyterlabclean
jupyterlabbuildContributingInstallThejlpmcommand is JupyterLab's pinned version ofyarnthat is installed with JupyterLab. You may useyarnornpmin lieu ofjlpmbelow.# Clone the repo to your local environment# Move to gquantlab directory# Install server extensionpipinstall-e.# Register server extensionjupyterserverextensionenable--pygquantlab--sys-prefix# Install dependenciesjlpm# Build Typescript sourcejlpmbuild# Link your development version of the extension with JupyterLabjupyterlabextensioninstall.# Rebuild Typescript source after making changesjlpmbuild# Rebuild JupyterLab after making any changesjupyterlabbuildYou can watch the source directory and run JupyterLab in watch mode to watch for changes in the extension's source and automatically rebuild the extension and application.# Watch the source directory in another terminal tabjlpmwatch# Run jupyterlab in watch mode in one terminal tabjupyterlab--watchNow every change will be built locally and bundled into JupyterLab. Be sure to refresh your browser page after saving file changes to reload the extension (note: you'll need to wait for webpack to finish, which can take 10s+ at times).Uninstallpipuninstallgquantlab
jupyterlabextensionuninstallgquantlab