BeakerX is a collection of JVM kernels and interactive widgets for plotting, tables, autotranslation, and other extensions to Jupyter Notebook. BeakerX is in beta and under active development.
The documentation consists of tutorial notebooks on GitHub. You can try it in the cloud for free with Binder.
BeakerX is the successor to the Beaker Notebook (source code archive). It comes from Two Sigma Open Source. Yes we are hiring.
This README is for developers. Users should see the documentation on the homepage for how to install and run BeakerX.
conda create -y -n beakerx 'python>=3' nodejs pandas openjdk maven py4j
source activate beakerx
conda config --env --add pinned_packages 'openjdk>8.0.121'
conda install -y -c conda-forge ipywidgets
(cd beakerx; pip install -e . --verbose)
beakerx install
conda create -y -n labx 'python>=3' nodejs pandas openjdk maven py4j
source activate labx
conda config --env --add pinned_packages 'openjdk>8.0.121'
conda install -y -c conda-forge jupyterlab
(cd beakerx; pip install -e . --verbose)
beakerx install
jupyter labextension install @jupyter-widgets/jupyterlab-manager
(cd js/lab; jupyter labextension install .)
docker run -p 8888:8888 beakerx/beakerx
The kernels are installed to run out of the repo, so just a local build should suffice:
(cd kernel; ./gradlew build)
The notebook extensions are installed to run out of the repo, so just a local build should suffice:
(cd js/notebook; yarn install)
The Java and TypeScript unit tests are run with every build. See test/README.md for how to run the e2e tests.
BeakerX is a collection of kernels and extensions for Jupyter. The code is organized into subdirectories as follows:
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beakerx The Python packages. The main beakerx package has:
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a customized KernelSpec to allow BeakerX to configure the JVMs that run the kernels,
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a server extension for the javadoc, settings, and version endpoints,
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the beakerx command line program, which has the bkr2ipynb converter, the py4j server, utilities, install, and uninstall functions.
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the Python API for the runtime (tables, plots, easyform), including automatically installing a displayer for pandas tables, and autotranslation;
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the nbextension webpack (compiled JavaScript, TypeScript, CSS, fonts, images); and
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the compiled Java JARs of each of the kernels, and a directory of shared JARs.
There is a separate python package (beakerx_magics) for the
%%groovymagic so it can be loaded without loading the regular beakerx package (which would turn on display of pandas tables with our table widget).BeakerX configures ipython to automatically load the magics in the beakerx_magics package,
%load_extis not required.The groovy magic uses the standard Jupyter API, jupyter_client.manager.KernelManager to start the kernel. It then proxies Comm into the inner kernel.
This package also has the py4j support for the
%%pythonmagic. In order for the JVM kernels to be able to start Jupyter kernels they need to be able to call into Python. There is abeakerx py4j_serversubcommand for this purpose (for internal use, not for the user). It calls into the groovy magic with its Comm proxy, implemented in Python. -
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doc Documentation consisting of executable tutorial notebooks. StartHere.ipynb at the top level links to these and is the intended way to navigate them. There is a subdirectory for each language.
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docker configuration files for creating the Docker image. There is a subdirectory docker/base for an image with BeakerX's dependencies (the Ubuntu and conda packages). The main image is built by compiling BeakerX and installing BeakerX in the base image.
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js There are two subdirectories of JavaScript and TypeScript, js/lab and js/notebook. New code is being written in TypeScript.
The lab subdirectory has the extension for Jupyter Lab (distributed by npm). Notebook has two extensions, one for the widgets (which are included in Lab as well, and are also separately distributed with npm for embedded applications such as nbviewer), and one for the notebook application. This adds a tab to the tree view with our options panel.
And for regular notebook pages the extension handles: running initialization cells, publication, autotranslation, the getCodeCells and runByTag APIs, callbacks for table and plot actions, UI customizations such as changing the fonts, allowing wide code cells, and disabling autosave.
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kernel The Java implementation of the kernels is here. The main directory is kernel/base which has generic code for all the languages. The base kernel has classes for Jupyter's Comm protocol (a layer over ZMQ), magics, the classpath (including loading from maven), and the kernel parts of the widget APIs.
There is also a subdirectory for each language which has the evaluator for that language. Scala has wrappers for the widgets so they have native types.
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test The e2e tests, which are made with webdriver (selenium, chromedriver, jasmine).
See CONTRIBUTING.md.
See RELEASE.md.
BeakerX contains and depends on many projects including:
The kernel is originally derived from lappsgrid, but has been rewritten in Java and refactored and expanded.
The Java support uses Adrian Witas' org.abstractmeta.toolbox.
ANTLR Copyright (c) 2012 Terence Parr and Sam Harwell
d3 Copyright (c) 2010-2015, Michael Bostock
IPython Copyright (c) 2008-2014, IPython Development Team Copyright (c) 2001-2007, Fernando Perez Copyright (c) 2001, Janko Hauser Copyright (c) 2001, Nathaniel Gray
The table of contents and init cells extensions come from: IPython-contrib Copyright (c) 2013-2015, IPython-contrib Developers
Scala Copyright (c) 2002-2015 EPFL Copyright (c) 2011-2015 Typesafe, Inc.
Guava Copyright (C) 2012 The Guava Authors
Apache Spark Copyright (C) 2014 and onwards The Apache Software Foundation.
H2 database engine This software contains unmodified binary redistributions for H2 database engine (http://www.h2database.com/), which is dual licensed and available under the MPL 2.0 (Mozilla Public License) or under the EPL 1.0 (Eclipse Public License). An original copy of the license agreement can be found at: http://www.h2database.com/html/license.html