Kyso is an comprehensive platform built to enhance collaboration & reproducibility in data science, a place where you can create and run data science projects in Jupyterlab, publish to the web, where Kyso renders the notebooks as beautiful data blogs. You can also deploy web-based data applications and dashboards with bokeh. Browse and discover cool studies published by other users to fork and run in your own environment.
Think of Kyso like Github, but for data science.
This page is your personal dashboard, where you can find all of your current projects and published notebooks.
Published Notebooks are your finshed Jupyter Notebooks, either published through Kyso's Jupyterlab extension or simply uploaded.
Workspaces are Kyso's Jupyterlab environments running on our general data science docker image.
Click on the
On the upload page, you can upload multiple files at once, but must choose a main notebook (.ipynb) file for Kyso to render on our frontend. Any other selected files will be attached and available if you open the publication in a workspace.
We're huge fans of Project Jupyter at Kyso, and we're going all-in on JupyterLab, the next-gen evolution of the Jupyter Notebook. JupyterLab is a fully extensible interactive computing environment, with all sorts of powerful features in a single customizable UI, file browser with rich outputs for images, CSVs, TSVs, and full terminal access.
Perhaps the feature we are most proud of is our new kyso publish extension. Pre-installed on Kyso's workspaces, this plugin allows anyone to publish to our platform from any Jupyterlab environment. We have made a bunch of example guides on how one can set up Jupyterlab environments on AWS, GCP, Azure and DigitalOcean virtual machines. This is of particular use to those, for example, running compute-intensive notebooks on a GPU-powered instance on any one of the above cloud solutions, that may not run as smoothly our machines. Now you can still publish your results as awesome blogs to Kyso.
Please find the install instructions on Github here.
These are your finished publications. Tell cool stories with data!
Once published you can hide or show your code, and even set a default for when others open up the post. Showing the code by default is perfect for educational notebooks, guides or those written for techincal readers. Select the Code hidden button on the right; next to each code visibility setting on the dropdown menu, you'll see a Make default option.
You can comment on & engage with your fellow data scientists on these blogs, fork onto your own profile or simply fire up the project in a Jupyterlab environemnt containing the notebook and any attached files.
Clicking on the 3 dots on the right-hand side will open up the drop-down menu as seen above, where you can print, view previous versions, embed, share or download the publication.
You can also tag your published notebooks with desriptive terms. Taking the example above, my publication is an intro to the work of renowned economist, Thomas Pikkety, and I created the plots using the bokeh plotting library. Accordingly, I've tagged the notebook with pikkety, economics, and bokeh. Once any given tag achieves a pre-defined number of tags, they will appear as collections on Kyso's explore page.
Here are some collections already on our landing page!
On your profile page you can edit your avatar and bio. This is a simple dashboard of all your published notebooks, the page that other users will see when they search for your work.
Search Kyso's explore page for interesting notebooks to read and perhaps fork. Notebooks on this page are ranked by publication date and popularity.
On our basic plan you have access to the following features: