Getting Started with Kyso

#Getting-Started-with-Kyso

Here you'll find an overview of everything you can do on Kyso. We do our best to make this documentation clear and user friendly, but if you have any unanswered questions, please sign up to our slack channel to chat with the community or email us directly.

Kyso is an comprehensive platform built to enhance collaboration & reproducibility in data science, a place where you can create, upload and share your data-science notebooks, charts, datasets, code and articles. You can also create and run data science projects in our Jupyterlab workspaces, & publish to the web, where Kyso renders your jupyter and R notebooks as beautiful data blogs. Browse and discover cool studies published by other users to fork and run in your own environment.

For academic and corporate data science teams alike we have built the next-generation knowledge-repo.

Posting to Kyso

#Posting-to-Kyso
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There are multiple ways to share data science on Kyso. Click on New in the navigation bar at the top to see your options:

  • Write a post to create a post in our markdown editor.

  • You can create a post with Upload to upload a file or multiple files for the readers to browse. Choose a main file for Kyso to render on its frontend. Any other selected files will be attached and available to view.

  • Connect a Github Repository to sync your work on Github to Kyso. Before you connect a repository to Kyso it is recommended that you add a kyso.json file to the repo on Github that specifies the main file to render on Kyso. Note that this file can be changed and, once connected, any commits pushed to Github will be automatically reflected on the same repo on Kyso.

  • Or your can launch a Jupyterlab environment running on Kyso's data science docker image to start a project from scratch.

Note: Your kyso.json file on Github should be as follows:

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{
   "main": "yourfile.ipynb"
}

Explore & Discover

#Explore-&-Discover

You don't have to be a creator to use Kyso. Search Kyso's explore page for our latest and most popular posts to read. Publications on this page are ranked by publication date and popularity. If the post is a notebook, you can fork it (along with any attached data files) and run in your own Jupyterlab workspace.

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Data Science Profile & Dashboard

#Data-Science-Profile-&-Dashboard

Under My Dashboard you can find all of your current projects and past posts.

  • Studies are your past posts, either published through Kyso's Jupyterlab extension, created using our web editor or simply uploaded.

  • Workspaces are Kyso's Jupyterlab environments running on our general data science docker image.

On your dashboard you can also edit your avatar and biography. The first tab (Studies) is the page that other users will see when they search for you.

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Publications - Data Blogs

#Publications---Data-Blogs

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 posts, 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 all attached files.

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Above you can also share, print, view previous versions, embed, or download the post.

You can also tag your publications 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!

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Custom Jupyterlab Extension

#Custom-Jupyterlab-Extension

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.

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Teams

#Teams

We've just launched our team plan, which looks to build upong the existing knowledge repo. You can create a team in the space of just a few minutes. All of the features above are available to your team, but inside your team's sandbox.

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A Note on Kyso's Free Tier

#A-Note-on-Kyso's-Free-Tier

On our basic plan you have access to the following features:

  • Unlimited public publications.
  • Run only 1 workspace at any given time. Users can have an unlimited number of workspaces.
  • Maximum of 3 hours before workspace is shut down at any one time.
  • Low CPU priority.
  • Number of total hours across all workspaces is limited to a maximum of 10 hours per month.

Head over to our checkout page to upgrade to our pro plan. Contact us at support@kyso.io or request access here for info on our team and custom plans, coming soon!