Jupyter and BeakerX are based on the idea of the lab notebook, brought to life in your web browser. Each notebook is a place for recording the written ideas, data, images, spreadsheets, diagrams, equations, and especially code, that one produces in the course of research. You can analyze, visualize, and document data and science, using multiple programming languages. BeakerX is an extension of Jupyter, including kernels for the JVM langauges, autotranslation between languages, interactive plots, tables, and more.
This is a beta release. There are known issues, please see our issue tracker. Your email feedback about anything is most welcome.
The Jupyter documentation covers interacting with code cells, markdown, and notebooks. The tutorials below show the features of the BeakerX extension.
Groovy, Java, Scala, Clojure, SQL, Kotlin.
Timing, Classpath and Imports, Properties, Heap Size and other JVM parameters, Defining New Magics.
Example and Interaction, Time Series and General APIs and Features, Category Plots and Bar Charts, Levels of Detail, Histograms, Heatmaps, Treemaps, Plot Actions, Plot Seamless Updates, Second Y Axis.
Groovy API including Actions, 64-Bit Integers and BigNums, Automatic Display of Simple Data Structures, Handling of Large Tables.
Tables including pandas integration, Time Series, Heatmaps, Category Plots, Treemaps, Histograms, EasyForm, Output Containers, Groovy Magic.
Media and MIME Outputs, Display of Null, Custom Displayers and jvm-repr
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EasyForm, Output Containers and Layout Managers, Groovy interface to Jupyter JS Widgets, Interactive recomputation.
Progress Reporting API, Initialization Cells, Get Code.
Tablesaw Pandas for the JVM.
Spark cluster computing based on Scala, and the Flint time series library.
DataVec (DeepLearning4j), STIL (Starlink Tables Infrastructure Library).
On the web at the homepage BeakerX.com, on GitHub, and on Two Sigma's Open Source site.
BeakerX's full source code and documentation are available on GitHub under the Apache 2.0 license.