Streamlit Releases Version 1.0
SAN FRANCISCO, Oct. 5, 2021 — Streamlit, the creators of a fast and powerful app framework for machine learning and data science, today announced that Streamlit 1.0 is generally available. The open source project has more than 16,000 GitHub stars, has been downloaded more than 4.5 million times and is used by more than 10,000 organizations, including more than half of the Fortune 50.
Streamlit is a powerful and easy-to-use framework that lets data scientists quickly build web apps to access and explore machine learning models, advanced algorithms and complex data types. These apps are used for everything from advanced analytics dashboards to sales and marketing tools based off of the latest predictive algorithms. Streamlit’s unique workflow is 10x faster than other alternatives, making it possible for data scientists to go from idea to deployed app in only a few hours.
Compared to existing dashboarding tools, Streamlit offers a far greater range of AI-powered use-cases:
- Apps that combine different APIs to produce new insights for sales, marketing and product
- Apps that surface custom product recommendations for sales people to pitch
- Data exploration apps that let non-technical users explore SQL data via AWS S3, BigQuery, Snowflake or any internal or cloud database
- Data labeling apps to annotate new types of data for machine learning or data cleaning
- Apps that take data on user cohorts and generate targeted promotional coupons
- Fraud detection apps to understand how different detection models trade off detection rates and total dollar loss
- ROI tools that help companies land deals by showing what if analysis to customers
- Apps for procurement teams to know what types of inventory to buy based on the latest trends
- Apps for optimizing operations such as where to place electric bike chargers for the highest utilization
- Model comparison apps for ML teams to compare models side by side to see performance changes
“Streamlit shows the incredible power of community-driven software to disrupt industries,” said Adrien Treuille, co-founder and CEO of Streamlit. “Declaring 1.0 is a major achievement for Streamilt’s incredible development team and community. And we’re just getting started. What we’ve done in the past two years is nothing compared to what’s coming next!”
Streamlit users love Streamlit for the flexibility and power that it provides:
- Joanna Tang, Senior Data Scientist at Squarespace, said: “Streamlit is great because it lets non-technical audiences understand the metrics we develop.”
- Tyler Richards, Data Scientist from Facebook Research who recently authored a book about Streamlit, said: ”Streamlit makes my work so much more impactful by helping me quickly turn my analyses into beautiful, dynamic web apps.”
- Charlie Lefrak, Software Engineer from Mapbox, said: “I use Streamlit for everything from spinning up prototypes, exploring and interrogating data and creating finished business analytics products.”
- Chinmay Gaikwad, Senior Systems Engineer at Infosys, said: “Building and deploying an ML model have never been easier. Thanks to Streamlit, it makes building web apps super easy and I would highly recommend it for data science projects.”
- Amit Marathe, Director of AI & ML at Inseego Corp, said: “If you want to impress your boss with a quick data visualization dashboard, you can build a simple and beautiful data visualization dashboard in a couple hours using Streamlit!”
- Eric Sims, Sr. Analyst, Strategy & Analytics at LendingTree, said: “Deploying on Streamlit was ridiculously easy – took 5 minutes tops, probably less, actually.”
Streamlit 1.0 has added many powerful features since it was first introduced:
- Improvements to app speed and responsiveness: Improvements to caching, switching to Apache Arrow for serialization and memory management updates have resulted in major gains for speed and responsiveness.
- Customization with app layout primitives and theming: Columns, sidebar, wide mode, expanders, dark mode and customizable themes mean that users can now lay out their apps and match it to their ideal style of company brand.
- Ability to create complex apps by adding statefulness: With the addition of Session State and forms, users can now choose when their app re-runs and it lets users do complex things like pagination, annotation or even creating games.
- An amazing ecosystem of components and integrations: Users can extend their apps even further by writing their own components or use ones from the community including integrations, more libraries like SpaCy, HiPlot, Folium and Observable and new functionality like sending and receiving video or drawing on a canvas.
Streamlit’s 2022 Roadmap
Today Streamlit is also sharing its roadmap for 2022 for Streamlit: https://share.streamlit.io/streamlit/roadmap.
- Make Magical Apps: Streamlit has already made it 10x faster to make great apps but now it wants to make those apps even better. That means an unbeatable set of widgets — everything from sortable/filterable/editable databases and tables, clickable charts, image selectors and editors, amazing audio and video players and uploaders, and a lot more options for layout and customization.
- First-Class Developer Experience: Streamlit wants everything about coding a Streamlit app to be an amazing experience. So it will be working on everything from making it easier to connect to data sources, easier to cache and interact with data, and easier debugging.
- Enhance the Viewer Experience: Ultimately users are developing apps for someone else to view them so it also wants to help them make great apps for their viewers. It is thinking about how to give a viewer experience distinct from the developer experience, so viewers can more easily understand and interact with the app and give direct feedback.
- Rapidly Expand the Ecosystem: The community has already given so much to Streamlit and it wants to make it even easier for users to share code, components, apps, and answers — so it is going to be launching new features that make it easier to get started with new apps, find code snippets, search for the right component to add to apps, engage with the worldwide community, and get recognized for what users contribute to the community.
Streamlit makes creating web apps from Python fast and easy. Data scientists are able to go from data and models to deployed apps in a matter of hours and only a handful of lines of code. Streamlit is backed by Sequoia, Gradient Ventures and GGV Capital. For more information, visit http://streamlit.ioor.