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beakerx - Beaker Extensions for Jupyter Notebook
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. And here is the cheatsheet.
jupyter notebook sql kotlindashboards - Jupyter Dashboards Layout Extension
The dashboards layout extension is an add-on for Jupyter Notebook. It lets you arrange your notebook outputs (text, plots, widgets, ...) in grid- or report-like layouts. It saves information about your layouts in your notebook document. Other people with the extension can open your notebook and view your layouts. For a sample of what's possible with the dashboard layout extension, have a look at the demo dashboard-notebooks in this repository.
dashboard jupyter jupyter-notebook ipython dashboardsdocker-stacks - Ready-to-run Docker images containing Jupyter applications
Jupyter Docker Stacks are a set of ready-to-run Docker images containing Jupyter applications and interactive computing tools. The two examples below may help you get started if you have Docker installed know which Docker image you want to use, and want to launch a single Jupyter Notebook server in a container.
notebook jupyter docker jupyterhubnbdime - Tools for diffing and merging of Jupyter notebooks.
nbdime provides tools for diffing and merging of Jupyter Notebooks. See the installation docs for more installation details and development installation instructions.
jupyterlab-extension jupyter jupyter-notebook diff diffing merge git hg mercurial mergetool merge-driver vcs version-controlnbviewer - Nbconvert as a webservice (rendering ipynb to static HTML)
Jupyter nbviewer is the web application behind The Jupyter Notebook Viewer, which is graciously hosted by Rackspace. Run this locally to get most of the features of nbviewer on your own network.
jupyterjupyter-scala - Lightweight Scala kernel for Jupyter / IPython 3
Jupyter Scala is a Scala kernel for Jupyter. It aims at being a versatile and easily extensible alternative to other Scala kernels or notebook UIs, building on both Jupyter and Ammonite. The current version is available for Scala 2.11. Support for Scala 2.10 could be added back, and 2.12 should be supported soon (via ammonium / Ammonite).
jupyter jupyter-notebook repl jupyter-kernelsjupyter-themes - Custom Jupyter Notebook Themes
While I love my job as a researcher, it doesn't exactly bring home the bacon. I mean.. it brings home some bacon... but like... not enough bacon? Right. Anyway, a colleague suggested I add an optional donation badge so users can help support projects like jupyter-themes (and the forthcoming lab-themes which will give users similar control over the look and feel of Jupyter Lab. Currently in early stages of development). I firmly believe that software is best served open and, as such, am committed to providing free and easy access to all my code. So if you can't make a financial contribution, then don't and pip install it anyway! But if you're sitting on some extra cash and enjoy using a package I've developed, then any amount helps and I greatly appreciate it.
jupyter jupyter-notebook theme css syntax-highlighting jupyter-themesgophernotes - The Go kernel for Jupyter notebooks and nteract.
Acknowledgements - This project utilizes a Go interpreter called gomacro under the hood to evaluate Go code interactively. The gophernotes logo was designed by the brilliant Marcus Olsson and was inspired by Renee French's original Go Gopher design. Important Note - gomacro relies on the plugin package when importing third party libraries. This package works reliably on Mac OS X only with Go 1.10.2+ as long as you never execute the command strip gophernotes. If you can only compile gophernotes with Go <= 1.10.1 on Mac, consider using the Docker install and run gophernotes/Jupyter in Docker.
jupyter jupyter-notebook kernel gophernotes zeromq nteract data-science machine-learning artificial-intelligence numerical-methodshydrogen - :atom: Run code interactively, inspect data, and plot
Hydrogen is an interactive coding environment that supports Python, R, JavaScript and other Jupyter kernels. Checkout our Documentation and Medium blog post to see what you can do with Hydrogen.
data-science jupyter ipython repl hydrogen atom jupyter-kernels nteract execute run julia torch ijulia irkernel itorch plot imagenteract - 📘 The interactive computing suite for you! ✨
nteract is first and foremost a dynamic tool to give you flexibility when writing code, exploring data, and authoring text to share insights about the data. Edit code, write prose, and visualize.
notebook nteract data-science repl ipython jupyter jupyter-notebook desktop-application react react-components zeromq monorepo electron datapapermill - 📚 Parameterize, execute, and analyze notebooks
Papermill is a tool for parameterizing, executing, and analyzing Jupyter Notebooks. To parameterize your notebook designate a cell with the tag parameters.
jupyter notebooks notebook-generator nteract publishing pipelinegeonotebook - A Jupyter notebook extension for geospatial visualization and analysis
GeoNotebook is an application that provides client/server environment with interactive visualization and analysis capabilities using Jupyter, GeoJS and other open source tools. Jointly developed by Kitware and NASA Ames. Documentation for GeoNotebook can be found at http://geonotebook.readthedocs.io.
notebook mapnik jupyter jupyter-notebook-extension tile-server opengeoscience analysisIRkernel - R kernel for Jupyter
Now both R versions are available as an R kernel in the notebook. If you have Jupyter installed, you can create a notebook using IRkernel from the dropdown menu.
jupyter jupyter-notebook jupyter-kernels r zmqIPython - Interactive Computing
IPython provides a rich toolkit to help you make the most of using Python interactively. It provides a Jupyter kernel to work with Python code in Jupyter notebooks and other interactive frontends.
interpreter python-interpreter curses terminal jupyter data-science notebook replScreenshot-to-code-in-Keras - A neural network that transforms a screenshot into a static website
This is the code for the article 'Turning design mockups into code with deep learning' on FloydHub's blog. Within three years deep learning will change front-end development. It will increase prototyping speed and lower the barrier for building software.
keras deep-learning seq2seq encoder-decoder lstm floydhub machine-learning cnn cnn-keras jupyter-notebook jupyterdeepo - A series of Docker images (and their generator) that allows you to quickly set up your deep learning research environment
If you want to share your data and configurations between the host (your machine or VM) and the container in which you are using Deepo, use the -v option, e.g. This will make /host/data from the host visible as /data in the container, and /host/config as /config. Such isolation reduces the chances of your containerized experiments overwriting or using wrong data.
deep-learning jupyter lasagne caffe tensorflow sonnet keras theano chainer torch pytorch mxnet cntk dockerfile-generator docker-image caffe2 onnxipyvolume - 3d plotting for Python in the Jupyter notebook based on IPython widgets using WebGL
3d plotting for Python in the Jupyter notebook based on IPython widgets using WebGL.
ipython-widget jupyter jupyter-notebook visualisation volume-rendering virtual-reality plotting dataviz scientific-visualization webgl threejs rendering-3d-volumes quiverpythonVSCode - This extension is now maintained in the Microsoft fork.
To see all available Python commands, open the Command Palette and type Python. The Microsoft Python Extension for Visual Studio Code collects usage data and sends it to Microsoft to help improve our products and services. Read our privacy statement to learn more. This extension respects the telemetry.enableTelemetry setting which you can learn more about at https://code.visualstudio.com/docs/supporting/faq#_how-to-disable-telemetry-reporting.
typescript visual-studio-code editor terminal python-terminal intellisense refactorings autopep8 pylint testing rename-refactorings extract jupyter sort-imports python-3-6 scientific pydocstyle linter django unittest multi-root-readyinteractive -
.NET Interactive takes the power of .NET and embeds it into your interactive experiences. Share code, explore data, write, and learn across your apps in ways you couldn't before. We recently introduced the .NET Interactive Notebooks extension for Visual Studio Code, which adds support for .NET Interactive using the new Visual Studio Code native notebook feature. We encourage you to try it out. If you'd like to contribute, you can start here.
data-science jupyter fsharp powershell interactive-programming
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