🎈 New in 1.62: client-side validation & specialized input types for st.text_input, wrap parameter for layouts, widgets & labels, + more! A faster way to build and share data apps Get started in under a minute → Try a live playground in your browser The easiest way to try Streamlit before you install. → Build in public with Streamlit Community Cloud Public apps only. Totally free. You just need a GitHub account. → Build like a pro on Snowflake Unlimited private apps. Enterprise-grade reliability and security. Streamlit builds upon Embrace scripting import streamlit as st import pandas as pd st. write ( """ df = pd. read_csv ( "my_data.csv" ) st. line_chart ( df ) Weave in interaction Deploy instantly Build powerful apps Used in the world’s top data science groups “ Write production-level code while producing shareable artifacts. ” Kevin Zielnicki “ ...a great way to share machine learning models and analyses. ” Emmanuel Ameisen Insight Data Science “ Streamlit bridges experimentation and production. ” “ It's the next step in ML and data science tools. ” “ Streamlit apps are way easier to put together and iterate on. ” “ Streamlit democratizes building data apps. ” Compatible with Basically everything! See why developers Streamlit Really really pleased with @ streamlit so far. Used it to build a clickable prototype for a complex piece of a web application. It turned out faster and more flexible than everything else I could find. Highly recommended! # python # streamlit # prototyping Where were you my whole life @ streamlit I wanted someone like you since forever! If you do ML and work with Data @ streamlit will breathe life into your work. What an awesome library @ streamlit is !!!!!! So much productive, easy and flexible. From coding to deployment in just 2 days (since it was new for me). Probably i should boost up and do more projects using it. Tried @ streamlit today and believe me I regret spending those hours working on HTML and Javascript to build a Web apps for my Algorithms for demo. It's one of the fastest and simple way to make a web app and showcase your work using python # Python # MachineLearning This past week I played with @ streamlit to bring some advanced models + visuals to a non-technical team. Very easy to build & deploy and very impressive final product. Honestly, thinking more about it, I think this is a game-changer like IPython Notebooks were in 2013. https://twitter.com/calogica/status/1180844807259734016 I spent the day playing with Streamlit, which is like Shiny for python, and here's my initial review: It is very good. Put together this simple PCA dashboard with @ streamlit and @ plotlygraphs tonight. Streamlit is such a pleasure to use and will definitely be my first choice for my dashboarding needs https://github.com/benjaminjack/streamlit-pca # datascience The @ streamlit hype is real, this app went from zero to deployed in one night! # python # DataScience https://nba-roster-turnover.herokuapp.com/ Using @ streamlit and for the first time in a very long while, or ever, I don't swear under my breath while writing the UI/demo code for a # DataScience use-case. Heck it's even enjoyable! They do right everything Jupyter notebooks got wrong. In building end to end # MachineLearning # webapps my time distribution was: Actual logic and ml part : 20 % Frontend : 80% After @ streamlit it has become: Logic and ml part: 100% @ streamlit is Streamlit is a blessing for data scientists. There’s no two ways about it. It not only helps them to build ML web applications, but also conveniently share and demonstrate their models to stakeholders, customers and colleagues especially if they are non-technical It took me ~1 hour to build this dashboard (data is dummy) layout in @ streamlit . Using default Streamlit components. I think it would take 10 times longer with HTML/JS. Now I can focus on functionality , not on div alignment Code: https://github.com/katanaml/sparrow/tree/main/sparrow-ui Streamlit This one is just impressive. Create and deploy data-driven web apps in the simplest way possible. These apps look great, are easy to update, and can even be interactive. Check it out: https://streamlit.io/ Just spent this week using @ streamlit to build a live animated map I'd never heard of them before this week but very impressed with the speed from idea->data->visualisations Every new @ streamlit release feels like Christmas

I just discovered the most beautiful thing ever created. @ streamlit I friggin love you No hassle,no complications,no drama Just straight up works like a dream Ugh.....I could cry Machine learning just got a whole lot fun-er Que belleza celestial streamlit y su simplicidad para crear dashboards con Python en 2 segundos Not gonna lie. The hours I spend each week working in @ streamlit are my favorites. Productionizing your machine learning model is a mandatory part of your ML project lifecycle. In that context, I have found Streamlit to be very effective and practical, not to mention how fun it is. Really really pleased with @ streamlit so far. Used it to build a clickable prototype for a complex piece of a web application. It turned out faster and more flexible than everything else I could find. Highly recommended! # python # streamlit # prototyping Where were you my whole life @ streamlit I wanted someone like you since forever! If you do ML and work with Data @ streamlit will breathe life into your work. What an awesome library @ streamlit is !!!!!! So much productive, easy and flexible. From coding to deployment in just 2 days (since it was new for me). Probably i should boost up and do more projects using it. Tried @ streamlit today and believe me I regret spending those hours working on HTML and Javascript to build a Web apps for my Algorithms for demo. It's one of the fastest and simple way to make a web app and showcase your work using python # Python # MachineLearning This past week I played with @ streamlit to bring some advanced models + visuals to a non-technical team. Very easy to build & deploy and very impressive final product. Honestly, thinking more about it, I think this is a game-changer like IPython Notebooks were in 2013. https://twitter.com/calogica/status/1180844807259734016 I spent the day playing with Streamlit, which is like Shiny for python, and here's my initial review: It is very good. Put together this simple PCA dashboard with @ streamlit and @ plotlygraphs tonight. Streamlit is such a pleasure to use and will definitely be my first choice for my dashboarding needs https://github.com/benjaminjack/streamlit-pca # datascience The @ streamlit hype is real, this app went from zero to deployed in one night! # python # DataScience https://nba-roster-turnover.herokuapp.com/ Using @ streamlit and for the first time in a very long while, or ever, I don't swear under my breath while writing the UI/demo code for a # DataScience use-case. Heck it's even enjoyable! They do right everything Jupyter notebooks got wrong. In building end to end # MachineLearning # webapps my time distribution was: Actual logic and ml part : 20 % Frontend : 80% After @ streamlit it has become: Logic and ml part: 100% @ streamlit is Streamlit is a blessing for data scientists. There’s no two ways about it. It not only helps them to build ML web applications, but also conveniently share and demonstrate their models to stakeholders, customers and colleagues especially if they are non-technical It took me ~1 hour to build this dashboard (data is dummy) layout in @ streamlit . Using default Streamlit components. I think it would take 10 times longer with HTML/JS. Now I can focus on functionality , not on div alignment Code: https://github.com/katanaml/sparrow/tree/main/sparrow-ui Streamlit This one is just impressive. Create and deploy data-driven web apps in the simplest way possible. These apps look great, are easy to update, and can even be interactive. Check it out: https://streamlit.io/ Just spent this week using @ streamlit to build a live animated map I'd never heard of them before this week but very impressed with the speed from idea->data->visualisations Every new @ streamlit release feels like Christmas I just discovered the most beautiful thing ever created. @ streamlit I friggin love you No hassle,no complications,no drama Just straight up works like a dream Ugh.....I could cry Machine learning just got a whole lot fun-er Que belleza celestial streamlit y su simplicidad para crear dashboards con Python en 2 segundos Not gonna lie. The hours I spend each week working in @ streamlit are my favorites. Productionizing your machine learning model is a mandatory part of your ML project lifecycle. In that context, I have found Streamlit to be very effective and practical, not to mention how fun it is. Really really pleased with @ streamlit so far. Used it to build a clickable prototype for a complex piece of a web application. It turned out faster and more flexible than everything else I could find. Highly recommended! # python # streamlit # prototyping Where were you my whole life @ streamlit I wanted someone like you since forever! If you do ML and work with Data @ streamlit will breathe life into your work. What an awesome library @ streamlit is !!!!!! So much productive, easy and flexible. From coding to deployment in just 2 days (since it was new for me). Probably i should boost up and do more projects using it. Tried @ streamlit today and believe me I regret spending those hours working on HTML and Javascript to build a Web apps for my Algorithms for demo. It's one of the fastest and simple way to make a web app and showcase your work using python # Python # MachineLearning This past week I played with @ streamlit to bring some advanced models + visuals to a non-technical team. Very easy to build & deploy and very impressive final product. Honestly, thinking more about it, I think this is a game-changer like IPython Notebooks were in 2013. https://twitter.com/calogica/status/1180844807259734016 I spent the day playing with Streamlit, which is like Shiny for python, and here's my initial review: It is very good. Put together this simple PCA dashboard with @ streamlit and @ plotlygraphs tonight. Streamlit is such a pleasure to use and will definitely be my first choice for my dashboarding needs https://github.com/benjaminjack/streamlit-pca # datascience The @ streamlit hype is real, this app went from zero to deployed in one night! # python # DataScience https://nba-roster-turnover.herokuapp.com/ Using @ streamlit and for the first time in a very long while, or ever, I don't swear under my breath while writing the UI/demo code for a # DataScience use-case. Heck it's even enjoyable! They do right everything Jupyter notebooks got wrong. In building end to end # MachineLearning # webapps my time distribution was: Actual logic and ml part : 20 % Frontend : 80% After @ streamlit it has become: Logic and ml part: 100% @ streamlit is Streamlit is a blessing for data scientists. There’s no two ways about it. It not only helps them to build ML web applications, but also conveniently share and demonstrate their models to stakeholders, customers and colleagues especially if they are non-technical It took me ~1 hour to build this dashboard (data is dummy) layout in @ streamlit . Using default Streamlit components. I think it would take 10 times longer with HTML/JS. Now I can focus on functionality , not on div alignment Code: https://github.com/katanaml/sparrow/tree/main/sparrow-ui Streamlit This one is just impressive. Create and deploy data-driven web apps in the simplest way possible. These apps look great, are easy to update, and can even be interactive. Check it out: https://streamlit.io/ Just spent this week using @ streamlit to build a live animated map I'd never heard of them before this week but very impressed with the speed from idea->data->visualisations Every new @ streamlit release feels like Christmas I just discovered the most beautiful thing ever created. @ streamlit I friggin love you No hassle,no complications,no drama Just straight up works like a dream Ugh.....I could cry Machine learning just got a whole lot fun-er Que belleza celestial streamlit y su simplicidad para crear dashboards con Python en 2 segundos Not gonna lie. The hours I spend each week working in @ streamlit are my favorites. Productionizing your machine learning model is a mandatory part of your ML project lifecycle. In that context, I have found Streamlit to be very effective and practical, not to mention how fun it is. Deploy on enterprise