Machine learning and data science code is easy to share but hard to use. GitHub overflows with models, algorithms, and datasets. But code is static. Can you play with the models? See the algorithms? Interact with the data? Doing so requires following complex instructions, installing packages, or reading dense code snippets. Frustrated by this, we decided that we need a simple, sharable "play" button for machine learning code.
There are two challenges here. The first is creating apps that make data science and machine learning code interactive. The second is sharing these apps so that the world can experience your work.
A year ago, we addressed the first challenge — creating — by releasing Streamlit, an open-source library that lets you transform Python scripts into interactive apps. Streamlit lets you easily demonstrate algorithms, play with models, manipulate data, and combine all of these superpowers into beautiful apps. The response has been tremendous. We just crossed our millionth download. Hundreds of thousands of Streamlit apps have been created all over the world. But creating great apps only solves half the problem.
Easily deploy and share your Streamlit apps
Today, we address the second challenge — sharing — by announcing a brand-new sharing platform for Streamlit. Streamlit sharing lets you deploy, manage, and share your apps – all for free! If you have a Streamlit app hosted publicly on GitHub, you are now one click away from sharing it with the world.
GitHub and Streamlit - Better Together
Streamlit sharing combines the best of Streamlit with the best of GitHub. From Streamlit you get a simple framework for creating incredibly rich and useful apps. From GitHub you inherit an incredible framework for social collaboration. Paste your GitHub link into Streamlit's sharing platform and almost instantly you have a live app. Or, click on the menu for any live app and see its source code on GitHub. Collaborate for free simply by forking and editing the code. It’s global, shareable, fork-able, collaborative data science!
Taken together, Streamlit and GitHub enable an incredibly rich and diverse ecosystem of useful apps – from dashboards to deep nets and beyond! (As former Carnegie Mellon folks, we're especially proud that students taking the Interactive Data Science class now submit their homework using Streamlit sharing 🤗) Here are some awesome examples of shared Streamlit apps that you can play with right now.
While this post has focused on open source applications, Streamlit is also used by thousands of companies to build sophisticated internal data tools. For example, Uber has deployed Streamlit company-wide, enabling data scientists to share their work throughout the company. Streamlit for Teams extends Streamlit’s sharing platform to bring secure, seamless app deployment, management, and collaboration within your enterprise. If you're interested please sign up for the beta for Streamlit for Teams.
Get Your Invitation to Streamlit Sharing
To celebrate the launch, we'll be releasing 1,000 invitations for Streamlit sharing - with more invites coming as our server capacity grows. If you don’t have one in your inbox already, please request an invite and we'll get you one soon.
The Streamlit Play Button
This new sharing superpower completes the Streamlit circle – from creation to sharing, and back again. So create! Share with the world! Let others see your work, fork, merge, and contribute the cycle of knowledge creation. In that spirit, we offer one last gift: This is our “play” button.
This brand-new badge helps others find and play with your Streamlit app. Embed it right into your GitHub
readme.md as follows:
Thank you all for inspiring us with you amazing creations. We're excited to see what you build and share. 🎈
A huge thank you from all of us at Streamlit to all of you in the community – and especially the inaugural Streamlit Creators, Ashish, Charly, Fanilo, José, Jesse, and Synode – for your kindness, your feature requests, your bug reports, and your enthusiasm. Special thanks also to all the launch app creators, Alex, Dan, Ines | Explosion, and finally Tyler who created not only the Goodreads app but also a great sharing tutorial.
This is a companion discussion topic for the original entry at https://blog.streamlit.io/introducing-streamlit-sharing/