BeakerX Interactive Widgets
BeakerX Interactive Widgets is a free, open-source collection of Jupyter kernels and extensions developed by Two Sigma, an investment management firm.
Publisher review
BeakerX Interactive Widgets is a free, open-source collection of Jupyter kernels and extensions developed by Two Sigma, an investment management firm. It is the successor to the Beaker Notebook, ported to the Jupyter ecosystem after the SciPy 2016 demo of Jupyter Lab. BeakerX is designed for data scientists and analysts who work with JVM languages—including Java, Scala, Groovy, Clojure, Kotlin, and SQL—alongside Python and JavaScript. It provides interactive widgets for time-series plotting, tables, forms, and more, making it suitable for exploratory data analysis, Spark cluster management, and polyglot programming within a single notebook environment. The tool is available via conda, pip, and Docker, and can be tested live on Binder without installation.
BeakerX operates by extending Jupyter with a shared base kernel that supports magics and classpath management across JVM languages. Its interactive widgets include time-series plots with nanosecond resolution, scatter plots, histograms, heatmaps, and treemaps, all of which remain interactive in saved notebooks and published web pages. The table widget automatically recognizes pandas dataframes and allows search, sort, drag, filter, format, select, graph, hide, pin, and export to CSV or clipboard. The Spark integration provides a GUI for configuration, status, progress, and interrupt of Spark jobs, with links to documentation and the standard Spark web UI. A data browser enables drag-and-drop of data into notebooks, and one-click publication converts notebook contents including interactive widgets into a GitHub gist viewable via nbviewer.
BeakerX competes primarily with other Jupyter-based interactive computing tools, such as Jupyter Notebook's native widgets and kernels, and commercial platforms like Databricks and Anaconda Enterprise. Its key differentiator is deep JVM language support and polyglot autotranslation, which allows data to be passed between languages in the same notebook. However, its polyglot translation is not as complete as the original Beaker Notebook, and it lacks the broad ecosystem of Python-only tools like Plotly or Bokeh. Two Sigma's involvement provides credibility but also means the project's development pace depends on a single corporate sponsor, unlike community-driven alternatives.
Honest trade-offs include limited Win32 support due to OpenJDK on Conda Forge not supporting it, though Win64 works with a custom JDK. The polyglot autotranslation feature is still a prototype and may not handle complex data types reliably. Installation via pip is possible but documentation emphasizes conda, which may frustrate users accustomed to pip-only workflows. Additionally, the project's focus on JVM languages may alienate pure Python users who prefer lighter-weight tools. Despite these limitations, BeakerX offers a unique combination of interactive widgets, Spark management, and multi-language support for teams invested in the JVM ecosystem.
How it works
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JVM kernel support
Supports Java, Scala, Groovy, Clojure, Kotlin, and SQL via a shared base kernel with magics and classpath management.
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Interactive plotting widgets
Provides time-series plots with nanosecond resolution, scatter plots, histograms, heatmaps, and treemaps that remain interactive in saved and published notebooks.
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Interactive table widget
Automatically recognizes pandas dataframes and enables search, sort, drag, filter, format, select, graph, hide, pin, and export to CSV or clipboard.
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Apache Spark integration
Includes a Spark magic with GUIs for configuration, status, progress, and interrupt of Spark jobs, plus links to documentation and the Spark web UI.
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Polyglot magics and autotranslation
Allows running multiple JVM languages in the same notebook with bidirectional autotranslation, though not as complete as the original Beaker Notebook.
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One-click publication
Converts the current notebook including interactive widgets into a GitHub gist viewable via nbviewer with a single click.
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Data browser with drag-and-drop
Provides a data browser that allows users to drag and drop data directly into the notebook for quick analysis.
Strengths and trade-offs
Strengths
- Supports six JVM languages (Java, Scala, Groovy, Clojure, Kotlin, SQL) plus Python and JavaScript in a single notebook environment.
- Interactive widgets for time-series plotting offer nanosecond resolution and remain functional in saved and published notebooks.
- Table widget automatically recognizes pandas dataframes and supports over ten operations including search, sort, drag, filter, and export to CSV.
- One-click publication converts notebook contents with interactive widgets into a GitHub gist viewable via nbviewer without additional steps.
Trade-offs
- Win32 is not supported due to OpenJDK on Conda Forge lacking Win32 support, though Win64 works with a custom JDK.
- Polyglot autotranslation is a prototype and not as complete as the original Beaker Notebook, potentially causing issues with complex data types.
- Installation via pip is possible but documentation focuses on conda, which may inconvenience users accustomed to pip-only workflows.
- The project's development pace depends on Two Sigma as a single corporate sponsor, unlike community-driven alternatives.
Pricing context
Free and open-source under the Apache 2.0 license.
Getting started with BeakerX Interactive Widgets
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Install BeakerX via conda
Open a terminal and run `conda install -c conda-forge beakerx`. This installs the BeakerX kernels and extensions into your Jupyter environment. Ensure you have conda installed; if not, install Miniconda or Anaconda first.
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Launch Jupyter Notebook
Run `jupyter notebook` in your terminal. This starts the Jupyter server and opens the notebook interface in your browser. BeakerX kernels will appear in the kernel selection menu.
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Create a new notebook
Click the 'New' button and select a BeakerX kernel, such as 'Java', 'Scala', or 'Groovy'. This creates a notebook where you can write code in the chosen JVM language and use BeakerX interactive widgets.
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Load data into a table widget
In a code cell, import a pandas DataFrame and display it using `table.show(df)`. The table widget automatically recognizes the DataFrame and enables search, sort, filter, and export operations.
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Publish notebook as a gist
Click the 'Publish' button in the notebook toolbar. BeakerX converts the notebook with interactive widgets into a GitHub gist. Share the gist URL for others to view via nbviewer.
Frequently Asked Questions
What is BeakerX Interactive Widgets?
BeakerX is a free, open-source collection of Jupyter kernels and extensions developed by Two Sigma. It supports JVM languages like Java, Scala, and Kotlin alongside Python and JavaScript, offering interactive widgets for plotting, tables, and Spark management in a single notebook.
How do I install BeakerX for Jupyter?
BeakerX can be installed via conda, pip, or Docker. The documentation emphasizes conda as the primary method, but pip installation is also possible. You can test it live on Binder without any installation, making it easy to evaluate before committing.
What JVM languages does BeakerX support?
BeakerX supports Java, Scala, Groovy, Clojure, Kotlin, and SQL through a shared base kernel with magics and classpath management. This allows running multiple JVM languages in the same notebook alongside Python and JavaScript for polyglot programming.
What interactive widgets does BeakerX offer?
BeakerX provides time-series plots with nanosecond resolution, scatter plots, histograms, heatmaps, and treemaps. Its table widget automatically recognizes pandas dataframes and supports search, sort, filter, and export to CSV. Widgets remain interactive in saved notebooks.
How does BeakerX integrate with Apache Spark?
BeakerX includes a Spark magic with GUIs for configuration, status, progress, and interrupt of Spark jobs. It provides links to documentation and the standard Spark web UI, making it easier to manage Spark clusters directly from a Jupyter notebook.
What are the limitations of BeakerX?
BeakerX lacks Win32 support due to OpenJDK limitations, and its polyglot autotranslation is a prototype that may not handle complex data types reliably. Installation documentation focuses on conda, and development pace depends on Two Sigma as a single corporate sponsor.
Alternatives
How BeakerX Interactive Widgets compares
Direct head-to-head against 2 competitors. Picked by 7wData.
BeakerX Interactive Widgets
- Pricing
- Free and open-source under the Apache 2.0 license.
- Target
- BeakerX Interactive Widgets is a free, open-source collection of Jupyter kernels and extensions developed by Two Sigma, an investment management firm.
- Strength
- Supports six JVM languages (Java, Scala, Groovy, Clojure, Kotlin, SQL) plus Python and JavaScript in a single notebook environment.
- Watch for
- Win32 is not supported due to OpenJDK on Conda Forge lacking Win32 support, though Win64 works with a custom JDK.
JupyterHub
- Pricing
- Free (open source)
- Target
- Data scientists, researchers, educators needing multi-user Jupyter environments
- Deployment
- Self-hosted, cloud
- Strength
- Multi-user notebook server with centralized management and authentication
- Watch for
- Complex setup and configuration for large deployments
Apache Zeppelin
- Pricing
- Free (open source)
- Target
- Data engineers and analysts needing polyglot notebooks with built-in visualization
- Deployment
- Self-hosted
- Strength
- Native support for multiple interpreters (Spark, SQL, Python) in one notebook
- Watch for
- Smaller community and fewer third-party integrations than Jupyter
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