# Table of Contents

- [Streamlit • A faster way to build and share data apps](#streamlit-a-faster-way-to-build-and-share-data-apps)

---

# Streamlit • A faster way to build and share data apps

🚀 [Release 1.43 is here: accept files in chat, configure JSON columns, and more!](https://docs.streamlit.io/develop/quick-reference/release-notes)
 🤩

A faster way to build and share data apps
-----------------------------------------

Turn your data scripts into shareable web apps in minutes.  
All in pure Python. No front‑end experience required.

[Get started](/#install)
[Try the live playground!](/playground)

Play

Learn more with the

[Streamlit crash course on YouTube](https://www.youtube.com/watch?v=d7fnzDQ5qM8)

Trusted by **over 90% of Fortune 50** companies

As of 2024-11-15

Get started in under a minute
-----------------------------

Streamlit is an [open-source](https://github.com/streamlit/streamlit)
 app framework that is a breeze to get started with. Just install it like any other Python library:

`   pip install streamlit  ← Copy to clipboardCopied!   ``   streamlit hello  ← Copy to clipboardCopied!   `

And that's it! Next, check out our [documentation](https://docs.streamlit.io/get-started)
 and [forums](https://discuss.streamlit.io)
 for more.

Or you can skip local installation altogether:

*   [→\
    \
    Try a live playground in your browser\
    \
    The easiest way to try Streamlit before you install.](/playground)
    
*   [→\
    \
    Build in public with Streamlit Community Cloud\
    \
    Public apps only. Totally free. You just need a GitHub account.](https://share.streamlit.io/?utm_source=streamlit&utm_medium=referral&utm_campaign=rethink&utm_content=-ss-streamlit-io-getstarted)
    
*   [→\
    \
    Build like a pro on Snowflake\
    \
    Unlimited private apps. Enterprise-grade reliability and security.](https://signup.snowflake.com/?utm_source=streamlit&utm_medium=referral&utm_campaign=rethink&utm_content=-ss-streamlit-io-getstarted)
    

Streamlit builds upon
---------------------

three simple principles

Embrace scripting
-----------------

Build an app in a few lines of code with our [magically simple API](https://docs.streamlit.io/library/api-reference)
. Then see it automatically update as you iteratively save the source file.

MyApp.py

*   import streamlit as st
*   import pandas as pd

*   st.write("""
*   \# My first app
*   Hello \*world!\*
*   """)

*   df = pd.read\_csv("my\_data.csv")
*   st.line\_chart(df)

My App • Streamlit

My first app
------------

Hello world!

Weave in interaction
--------------------

Adding a widget is the same as [declaring a variable](https://docs.streamlit.io/library/get-started/main-concepts#widgets)
. No need to write a backend, define routes, handle HTTP requests, connect a frontend, write HTML, CSS, JavaScript, ...

Deploy instantly
----------------

The choice is yours — show off your public apps for free on [Streamlit Community Cloud](https://share.streamlit.io/?utm_source=streamlit&utm_medium=referral&utm_campaign=rethink&utm_content=-ss-streamlit-io-deployinstantly)
, go with [Snowflake](https://docs.snowflake.com/developer-guide/streamlit/about-streamlit)
 for enterprise‑grade deployment, or pick [something else entirely!](https://docs.streamlit.io/deploy/tutorials)

Build

**powerful**

apps
-------------------------

[View more →](/gallery)

Used in the world’s top data science groups
-------------------------------------------

### Neil Treat

#### Google X

“Write production-level code while producing shareable artifacts.”

### Kevin Zielnicki

#### Stitch Fix

“...a great way to share machine learning models and analyses.”

### Emmanuel Ameisen

#### Insight Data Science

“Streamlit bridges experimentation and production.”

### Dominik Moritz

#### Vega-Lite

“It's the next step in ML and data science tools.”

### Danny Nguyen

#### Yelp

“Streamlit apps are way easier to put together and iterate on.”

### Koen Havlik

#### Uber

“Streamlit democratizes building data apps.”

#### and...

Compatible with
---------------

Basically everything!

*   [![Bokeh](images/uploads/bokeh.png?nf_resize=fit&h=56)](https://bokeh.org)
    
*   [![Altair](/images/uploads/altair.png?nf_resize=fit&h=56)](https://altair-viz.github.io)
    
*   [![PyTorch](/images/uploads/pytorch.png?nf_resize=fit&h=56)](https://pytorch.org)
    
*   [![OpenCV](/images/uploads/opencv.png?nf_resize=fit&h=56)](https://opencv.org)
    
*   [![Deck.Gl](/images/uploads/deck-gl.png?nf_resize=fit&h=56)](https://deckgl.readthedocs.io/en/latest)
    
*   [![Pandas](/images/uploads/pandas.png?nf_resize=fit&h=56)](https://pandas.pydata.org)
    
*   [![Vega-Lite](/images/uploads/vega-lite.png?nf_resize=fit&h=56)](https://vega.github.io/vega-lite/)
    
*   [![Matplotlib](/images/uploads/matplotlib.png?nf_resize=fit&h=56)](https://matplotlib.org)
    
*   [![NumPy](/images/uploads/numpy.png?nf_resize=fit&h=56)](https://numpy.org)
    
*   [![Scikit Learn](/images/uploads/scikitlearn.png?nf_resize=fit&h=56)](https://scikit-learn.org)
    
*   [![Tensorflow](/images/uploads/tensorflow.png?nf_resize=fit&h=56)](https://www.tensorflow.org)
    
*   [![Plotly](/images/uploads/plotly.png?nf_resize=fit&h=56)](https://plotly.com)
    
*   [![Keras](/images/uploads/keras.png?nf_resize=fit&h=56)](https://keras.io)
    

And even more, with [Streamlit Components](https://docs.streamlit.io/components)
!  
Build your own, share with the community, bask in the glory.

See why developers ![](images/uploads/love.svg) Streamlit
---------------------------------------------------------

> Really really pleased with [~@~streamlit](https://twitter.com/streamlit "https://twitter.com/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! ![😎](https://abs.twimg.com/emoji/v2/72x72/1f60e.png) [~#~python](https://twitter.com/hashtag/python?src=hash "https://twitter.com/hashtag/python?src=hash")
>  [~#~streamlit](https://twitter.com/hashtag/streamlit?src=hash "https://twitter.com/hashtag/streamlit?src=hash")
>  [~#~prototyping](https://twitter.com/hashtag/prototyping?src=hash "https://twitter.com/hashtag/prototyping?src=hash")
> 
> [10](https://twitter.com/intent/like?tweet_id=1349853981628100615 "Like")
> [Permalink](https://twitter.com/maxwiertz/status/1349853981628100615)

> Where were you my whole life [~@~streamlit](https://twitter.com/streamlit "https://twitter.com/streamlit")
>  I wanted someone like you since forever!
> 
> [10](https://twitter.com/intent/like?tweet_id=1344391629612994561 "Like")
> [Permalink](https://twitter.com/saayedalam/status/1344391629612994561)

> If you do ML and work with Data[~@~streamlit](https://twitter.com/streamlit "https://twitter.com/streamlit")
>  will breathe life into your work.
> 
> [16](https://twitter.com/intent/like?tweet_id=1342252039397646338 "Like")
> [Permalink](https://twitter.com/trojrobert/status/1342252039397646338)

> What an awesome library [~@~streamlit](https://twitter.com/streamlit "https://twitter.com/streamlit")
>  is ![😍](https://abs.twimg.com/emoji/v2/72x72/1f60d.png)![😎](https://abs.twimg.com/emoji/v2/72x72/1f60e.png)![😍](https://abs.twimg.com/emoji/v2/72x72/1f60d.png)!!!!!! 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.![😎](https://abs.twimg.com/emoji/v2/72x72/1f60e.png)
> 
> [![View image on Twitter](https://pbs.twimg.com/media/Ebdw9gVX0AEbfNr?format=png)](https://twitter.com/Shubham28698/status/1276613322687647744)
> 
> [8](https://twitter.com/intent/like?tweet_id=1276613322687647744 "Like")
> [Permalink](https://twitter.com/Shubham28698/status/1276613322687647744)

> Tried [~@~streamlit](https://twitter.com/streamlit "https://twitter.com/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](https://twitter.com/hashtag/Python?src=hash "https://twitter.com/hashtag/Python?src=hash")
>  [~#~MachineLearning](https://twitter.com/hashtag/MachineLearning?src=hash "https://twitter.com/hashtag/MachineLearning?src=hash")
> 
> [8](https://twitter.com/intent/like?tweet_id=1253270743992856581 "Like")
> [Permalink](https://twitter.com/min2bro/status/1253270743992856581)

> This past week I played with [~@~streamlit](https://twitter.com/streamlit "https://twitter.com/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
> 
> [64](https://twitter.com/intent/like?tweet_id=1183795195420270593 "Like")
> [Permalink](https://twitter.com/Cmrn_DP/status/1183795195420270593)

> I spent the day playing with Streamlit, which is like Shiny for python, and here's my initial review:  
> It is very good.
> 
> [9](https://twitter.com/intent/like?tweet_id=1187523398693478400 "Like")
> [Permalink](https://twitter.com/drdrewsteen/status/1187523398693478400)

> Put together this simple PCA dashboard with [~@~streamlit](https://twitter.com/streamlit "https://twitter.com/streamlit")
>  and [~@~plotlygraphs](https://twitter.com/plotlygraphs "https://twitter.com/plotlygraphs")
>  tonight. Streamlit is such a pleasure to use and will definitely be my first choice for my dashboarding needs ![🔥](https://abs.twimg.com/emoji/v2/72x72/1f525.png) https://github.com/benjaminjack/streamlit-pca [~#~datascience](https://twitter.com/hashtag/datascience?src=hash "https://twitter.com/hashtag/datascience?src=hash")
> 
> [30](https://twitter.com/intent/like?tweet_id=1183594002202935301 "Like")
> [Permalink](https://twitter.com/benrjack/status/1183594002202935301)

> The [~@~streamlit](https://twitter.com/streamlit "https://twitter.com/streamlit")
>  hype is real, this app went from zero to deployed in one night! [~#~python](https://twitter.com/hashtag/python?src=hash "https://twitter.com/hashtag/python?src=hash")
>  [~#~DataScience](https://twitter.com/hashtag/DataScience?src=hash "https://twitter.com/hashtag/DataScience?src=hash")
>  https://nba-roster-turnover.herokuapp.com/
> 
> [![View image on Twitter](https://pbs.twimg.com/media/EHK_mx6WoAArqzL?format=jpg)](https://twitter.com/arvkevi/status/1185220341293047808)
> 
> [35](https://twitter.com/intent/like?tweet_id=1185220341293047808 "Like")
> [Permalink](https://twitter.com/arvkevi/status/1185220341293047808)

> Using [~@~streamlit](https://twitter.com/streamlit "https://twitter.com/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](https://twitter.com/hashtag/DataScience?src=hash "https://twitter.com/hashtag/DataScience?src=hash")
>  use-case. Heck it's even enjoyable! They do right everything Jupyter notebooks got wrong.
> 
> [7](https://twitter.com/intent/like?tweet_id=1188107289309433856 "Like")
> [Permalink](https://twitter.com/a_ghasemi/status/1188107289309433856)

> In building end to end [~#~MachineLearning](https://twitter.com/hashtag/MachineLearning?src=hash "https://twitter.com/hashtag/MachineLearning?src=hash")
>  [~#~webapps](https://twitter.com/hashtag/webapps?src=hash "https://twitter.com/hashtag/webapps?src=hash")
>  my time distribution was:  
> Actual logic and ml part : 20 %  
> Frontend : 80%  
>   
> After [~@~streamlit](https://twitter.com/streamlit "https://twitter.com/streamlit")
>  it has become:  
> Logic and ml part: 100%[~@~streamlit](https://twitter.com/streamlit "https://twitter.com/streamlit")
>  is ![❤️](https://abs.twimg.com/emoji/v2/72x72/2764.png)
> 
> [5](https://twitter.com/intent/like?tweet_id=1390964038050324486 "Like")
> [Permalink](https://twitter.com/AtharvaIngle7/status/1390964038050324486)

> 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
> 
> [1](https://twitter.com/intent/like?tweet_id=1380028715954970625 "Like")
> [Permalink](https://twitter.com/anuj_syal/status/1380028715954970625)

> It took me ~1 hour to build this dashboard (data is dummy) layout in [~@~streamlit](https://twitter.com/streamlit "https://twitter.com/streamlit")
> . Using default Streamlit components. I think it would take 10 times longer with HTML/JS. Now I can focus on functionality ![👍](https://abs.twimg.com/emoji/v2/72x72/1f44d.png), not on div alignment ![🤣](https://abs.twimg.com/emoji/v2/72x72/1f923.png)  
>   
> Code: https://github.com/katanaml/sparrow/tree/main/sparrow-ui
> 
> [![View image on Twitter](https://pbs.twimg.com/media/FeaIE1sXEAAhjUd?format=jpg)](https://twitter.com/andrejusb/status/1578099977036779520)
> 
> [764](https://twitter.com/intent/like?tweet_id=1578099977036779520 "Like")
> [Permalink](https://twitter.com/andrejusb/status/1578099977036779520)

> ![🏆](https://abs.twimg.com/emoji/v2/72x72/1f3c6.png) 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/
> 
> [1](https://twitter.com/intent/like?tweet_id=1575893719462469641 "Like")
> [Permalink](https://twitter.com/pablooomvc1/status/1575893719462469641)

> Just spent this week using [~@~streamlit](https://twitter.com/streamlit "https://twitter.com/streamlit")
>  to build a live animated map ![🗺](https://abs.twimg.com/emoji/v2/72x72/1f5fa.png)  
>   
> I'd never heard of them before this week but very impressed with the speed from idea->data->visualisations ![📊](https://abs.twimg.com/emoji/v2/72x72/1f4ca.png)
> 
> [1](https://twitter.com/intent/like?tweet_id=1575610749434855425 "Like")
> [Permalink](https://twitter.com/hrrsnbbnt/status/1575610749434855425)

> Every new [~@~streamlit](https://twitter.com/streamlit "https://twitter.com/streamlit")
>  release feels like Christmas ![🎁](https://abs.twimg.com/emoji/v2/72x72/1f381.png)![🎅](https://abs.twimg.com/emoji/v2/72x72/1f385.png)![🎄](https://abs.twimg.com/emoji/v2/72x72/1f384.png)![❄](https://abs.twimg.com/emoji/v2/72x72/2744.png)
> 
> [4](https://twitter.com/intent/like?tweet_id=1569595251869761537 "Like")
> [Permalink](https://twitter.com/Lorenz_Web/status/1569595251869761537)

> I just discovered the most beautiful thing ever created.[~@~streamlit](https://twitter.com/streamlit "https://twitter.com/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
> 
> [20](https://twitter.com/intent/like?tweet_id=1469064990237859845 "Like")
> [Permalink](https://twitter.com/jo5h_ofall/status/1469064990237859845)

> Que belleza celestial streamlit y su simplicidad para crear dashboards con Python en 2 segundos
> 
> [7](https://twitter.com/intent/like?tweet_id=1459014368780296194 "Like")
> [Permalink](https://twitter.com/AldoEscobarLVP/status/1459014368780296194)

> Not gonna lie. The hours I spend each week working in [~@~streamlit](https://twitter.com/streamlit "https://twitter.com/streamlit")
>  are my favorites.
> 
> [3](https://twitter.com/intent/like?tweet_id=1456680003198861319 "Like")
> [Permalink](https://twitter.com/jtouellette/status/1456680003198861319)

> 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.
> 
> [6](https://twitter.com/intent/like?tweet_id=1407115419253620743 "Like")
> [Permalink](https://twitter.com/nainia_ayoub/status/1407115419253620743)

> Really really pleased with [~@~streamlit](https://twitter.com/streamlit "https://twitter.com/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! ![😎](https://abs.twimg.com/emoji/v2/72x72/1f60e.png) [~#~python](https://twitter.com/hashtag/python?src=hash "https://twitter.com/hashtag/python?src=hash")
>  [~#~streamlit](https://twitter.com/hashtag/streamlit?src=hash "https://twitter.com/hashtag/streamlit?src=hash")
>  [~#~prototyping](https://twitter.com/hashtag/prototyping?src=hash "https://twitter.com/hashtag/prototyping?src=hash")
> 
> [10](https://twitter.com/intent/like?tweet_id=1349853981628100615 "Like")
> [Permalink](https://twitter.com/maxwiertz/status/1349853981628100615)

> Where were you my whole life [~@~streamlit](https://twitter.com/streamlit "https://twitter.com/streamlit")
>  I wanted someone like you since forever!
> 
> [10](https://twitter.com/intent/like?tweet_id=1344391629612994561 "Like")
> [Permalink](https://twitter.com/saayedalam/status/1344391629612994561)

> If you do ML and work with Data[~@~streamlit](https://twitter.com/streamlit "https://twitter.com/streamlit")
>  will breathe life into your work.
> 
> [16](https://twitter.com/intent/like?tweet_id=1342252039397646338 "Like")
> [Permalink](https://twitter.com/trojrobert/status/1342252039397646338)

> What an awesome library [~@~streamlit](https://twitter.com/streamlit "https://twitter.com/streamlit")
>  is ![😍](https://abs.twimg.com/emoji/v2/72x72/1f60d.png)![😎](https://abs.twimg.com/emoji/v2/72x72/1f60e.png)![😍](https://abs.twimg.com/emoji/v2/72x72/1f60d.png)!!!!!! 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.![😎](https://abs.twimg.com/emoji/v2/72x72/1f60e.png)
> 
> [![View image on Twitter](https://pbs.twimg.com/media/Ebdw9gVX0AEbfNr?format=png)](https://twitter.com/Shubham28698/status/1276613322687647744)
> 
> [8](https://twitter.com/intent/like?tweet_id=1276613322687647744 "Like")
> [Permalink](https://twitter.com/Shubham28698/status/1276613322687647744)

> Tried [~@~streamlit](https://twitter.com/streamlit "https://twitter.com/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](https://twitter.com/hashtag/Python?src=hash "https://twitter.com/hashtag/Python?src=hash")
>  [~#~MachineLearning](https://twitter.com/hashtag/MachineLearning?src=hash "https://twitter.com/hashtag/MachineLearning?src=hash")
> 
> [8](https://twitter.com/intent/like?tweet_id=1253270743992856581 "Like")
> [Permalink](https://twitter.com/min2bro/status/1253270743992856581)

> This past week I played with [~@~streamlit](https://twitter.com/streamlit "https://twitter.com/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
> 
> [64](https://twitter.com/intent/like?tweet_id=1183795195420270593 "Like")
> [Permalink](https://twitter.com/Cmrn_DP/status/1183795195420270593)

> I spent the day playing with Streamlit, which is like Shiny for python, and here's my initial review:  
> It is very good.
> 
> [9](https://twitter.com/intent/like?tweet_id=1187523398693478400 "Like")
> [Permalink](https://twitter.com/drdrewsteen/status/1187523398693478400)

> Put together this simple PCA dashboard with [~@~streamlit](https://twitter.com/streamlit "https://twitter.com/streamlit")
>  and [~@~plotlygraphs](https://twitter.com/plotlygraphs "https://twitter.com/plotlygraphs")
>  tonight. Streamlit is such a pleasure to use and will definitely be my first choice for my dashboarding needs ![🔥](https://abs.twimg.com/emoji/v2/72x72/1f525.png) https://github.com/benjaminjack/streamlit-pca [~#~datascience](https://twitter.com/hashtag/datascience?src=hash "https://twitter.com/hashtag/datascience?src=hash")
> 
> [30](https://twitter.com/intent/like?tweet_id=1183594002202935301 "Like")
> [Permalink](https://twitter.com/benrjack/status/1183594002202935301)

> The [~@~streamlit](https://twitter.com/streamlit "https://twitter.com/streamlit")
>  hype is real, this app went from zero to deployed in one night! [~#~python](https://twitter.com/hashtag/python?src=hash "https://twitter.com/hashtag/python?src=hash")
>  [~#~DataScience](https://twitter.com/hashtag/DataScience?src=hash "https://twitter.com/hashtag/DataScience?src=hash")
>  https://nba-roster-turnover.herokuapp.com/
> 
> [![View image on Twitter](https://pbs.twimg.com/media/EHK_mx6WoAArqzL?format=jpg)](https://twitter.com/arvkevi/status/1185220341293047808)
> 
> [35](https://twitter.com/intent/like?tweet_id=1185220341293047808 "Like")
> [Permalink](https://twitter.com/arvkevi/status/1185220341293047808)

> Using [~@~streamlit](https://twitter.com/streamlit "https://twitter.com/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](https://twitter.com/hashtag/DataScience?src=hash "https://twitter.com/hashtag/DataScience?src=hash")
>  use-case. Heck it's even enjoyable! They do right everything Jupyter notebooks got wrong.
> 
> [7](https://twitter.com/intent/like?tweet_id=1188107289309433856 "Like")
> [Permalink](https://twitter.com/a_ghasemi/status/1188107289309433856)

> In building end to end [~#~MachineLearning](https://twitter.com/hashtag/MachineLearning?src=hash "https://twitter.com/hashtag/MachineLearning?src=hash")
>  [~#~webapps](https://twitter.com/hashtag/webapps?src=hash "https://twitter.com/hashtag/webapps?src=hash")
>  my time distribution was:  
> Actual logic and ml part : 20 %  
> Frontend : 80%  
>   
> After [~@~streamlit](https://twitter.com/streamlit "https://twitter.com/streamlit")
>  it has become:  
> Logic and ml part: 100%[~@~streamlit](https://twitter.com/streamlit "https://twitter.com/streamlit")
>  is ![❤️](https://abs.twimg.com/emoji/v2/72x72/2764.png)
> 
> [5](https://twitter.com/intent/like?tweet_id=1390964038050324486 "Like")
> [Permalink](https://twitter.com/AtharvaIngle7/status/1390964038050324486)

> 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
> 
> [1](https://twitter.com/intent/like?tweet_id=1380028715954970625 "Like")
> [Permalink](https://twitter.com/anuj_syal/status/1380028715954970625)

> It took me ~1 hour to build this dashboard (data is dummy) layout in [~@~streamlit](https://twitter.com/streamlit "https://twitter.com/streamlit")
> . Using default Streamlit components. I think it would take 10 times longer with HTML/JS. Now I can focus on functionality ![👍](https://abs.twimg.com/emoji/v2/72x72/1f44d.png), not on div alignment ![🤣](https://abs.twimg.com/emoji/v2/72x72/1f923.png)  
>   
> Code: https://github.com/katanaml/sparrow/tree/main/sparrow-ui
> 
> [![View image on Twitter](https://pbs.twimg.com/media/FeaIE1sXEAAhjUd?format=jpg)](https://twitter.com/andrejusb/status/1578099977036779520)
> 
> [764](https://twitter.com/intent/like?tweet_id=1578099977036779520 "Like")
> [Permalink](https://twitter.com/andrejusb/status/1578099977036779520)

> ![🏆](https://abs.twimg.com/emoji/v2/72x72/1f3c6.png) 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/
> 
> [1](https://twitter.com/intent/like?tweet_id=1575893719462469641 "Like")
> [Permalink](https://twitter.com/pablooomvc1/status/1575893719462469641)

> Just spent this week using [~@~streamlit](https://twitter.com/streamlit "https://twitter.com/streamlit")
>  to build a live animated map ![🗺](https://abs.twimg.com/emoji/v2/72x72/1f5fa.png)  
>   
> I'd never heard of them before this week but very impressed with the speed from idea->data->visualisations ![📊](https://abs.twimg.com/emoji/v2/72x72/1f4ca.png)
> 
> [1](https://twitter.com/intent/like?tweet_id=1575610749434855425 "Like")
> [Permalink](https://twitter.com/hrrsnbbnt/status/1575610749434855425)

> Every new [~@~streamlit](https://twitter.com/streamlit "https://twitter.com/streamlit")
>  release feels like Christmas ![🎁](https://abs.twimg.com/emoji/v2/72x72/1f381.png)![🎅](https://abs.twimg.com/emoji/v2/72x72/1f385.png)![🎄](https://abs.twimg.com/emoji/v2/72x72/1f384.png)![❄](https://abs.twimg.com/emoji/v2/72x72/2744.png)
> 
> [4](https://twitter.com/intent/like?tweet_id=1569595251869761537 "Like")
> [Permalink](https://twitter.com/Lorenz_Web/status/1569595251869761537)

> I just discovered the most beautiful thing ever created.[~@~streamlit](https://twitter.com/streamlit "https://twitter.com/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
> 
> [20](https://twitter.com/intent/like?tweet_id=1469064990237859845 "Like")
> [Permalink](https://twitter.com/jo5h_ofall/status/1469064990237859845)

> Que belleza celestial streamlit y su simplicidad para crear dashboards con Python en 2 segundos
> 
> [7](https://twitter.com/intent/like?tweet_id=1459014368780296194 "Like")
> [Permalink](https://twitter.com/AldoEscobarLVP/status/1459014368780296194)

> Not gonna lie. The hours I spend each week working in [~@~streamlit](https://twitter.com/streamlit "https://twitter.com/streamlit")
>  are my favorites.
> 
> [3](https://twitter.com/intent/like?tweet_id=1456680003198861319 "Like")
> [Permalink](https://twitter.com/jtouellette/status/1456680003198861319)

> 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.
> 
> [6](https://twitter.com/intent/like?tweet_id=1407115419253620743 "Like")
> [Permalink](https://twitter.com/nainia_ayoub/status/1407115419253620743)

> Really really pleased with [~@~streamlit](https://twitter.com/streamlit "https://twitter.com/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! ![😎](https://abs.twimg.com/emoji/v2/72x72/1f60e.png) [~#~python](https://twitter.com/hashtag/python?src=hash "https://twitter.com/hashtag/python?src=hash")
>  [~#~streamlit](https://twitter.com/hashtag/streamlit?src=hash "https://twitter.com/hashtag/streamlit?src=hash")
>  [~#~prototyping](https://twitter.com/hashtag/prototyping?src=hash "https://twitter.com/hashtag/prototyping?src=hash")
> 
> [10](https://twitter.com/intent/like?tweet_id=1349853981628100615 "Like")
> [Permalink](https://twitter.com/maxwiertz/status/1349853981628100615)

> Where were you my whole life [~@~streamlit](https://twitter.com/streamlit "https://twitter.com/streamlit")
>  I wanted someone like you since forever!
> 
> [10](https://twitter.com/intent/like?tweet_id=1344391629612994561 "Like")
> [Permalink](https://twitter.com/saayedalam/status/1344391629612994561)

> If you do ML and work with Data[~@~streamlit](https://twitter.com/streamlit "https://twitter.com/streamlit")
>  will breathe life into your work.
> 
> [16](https://twitter.com/intent/like?tweet_id=1342252039397646338 "Like")
> [Permalink](https://twitter.com/trojrobert/status/1342252039397646338)

> What an awesome library [~@~streamlit](https://twitter.com/streamlit "https://twitter.com/streamlit")
>  is ![😍](https://abs.twimg.com/emoji/v2/72x72/1f60d.png)![😎](https://abs.twimg.com/emoji/v2/72x72/1f60e.png)![😍](https://abs.twimg.com/emoji/v2/72x72/1f60d.png)!!!!!! 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.![😎](https://abs.twimg.com/emoji/v2/72x72/1f60e.png)
> 
> [![View image on Twitter](https://pbs.twimg.com/media/Ebdw9gVX0AEbfNr?format=png)](https://twitter.com/Shubham28698/status/1276613322687647744)
> 
> [8](https://twitter.com/intent/like?tweet_id=1276613322687647744 "Like")
> [Permalink](https://twitter.com/Shubham28698/status/1276613322687647744)

> Tried [~@~streamlit](https://twitter.com/streamlit "https://twitter.com/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](https://twitter.com/hashtag/Python?src=hash "https://twitter.com/hashtag/Python?src=hash")
>  [~#~MachineLearning](https://twitter.com/hashtag/MachineLearning?src=hash "https://twitter.com/hashtag/MachineLearning?src=hash")
> 
> [8](https://twitter.com/intent/like?tweet_id=1253270743992856581 "Like")
> [Permalink](https://twitter.com/min2bro/status/1253270743992856581)

> This past week I played with [~@~streamlit](https://twitter.com/streamlit "https://twitter.com/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
> 
> [64](https://twitter.com/intent/like?tweet_id=1183795195420270593 "Like")
> [Permalink](https://twitter.com/Cmrn_DP/status/1183795195420270593)

> I spent the day playing with Streamlit, which is like Shiny for python, and here's my initial review:  
> It is very good.
> 
> [9](https://twitter.com/intent/like?tweet_id=1187523398693478400 "Like")
> [Permalink](https://twitter.com/drdrewsteen/status/1187523398693478400)

> Put together this simple PCA dashboard with [~@~streamlit](https://twitter.com/streamlit "https://twitter.com/streamlit")
>  and [~@~plotlygraphs](https://twitter.com/plotlygraphs "https://twitter.com/plotlygraphs")
>  tonight. Streamlit is such a pleasure to use and will definitely be my first choice for my dashboarding needs ![🔥](https://abs.twimg.com/emoji/v2/72x72/1f525.png) https://github.com/benjaminjack/streamlit-pca [~#~datascience](https://twitter.com/hashtag/datascience?src=hash "https://twitter.com/hashtag/datascience?src=hash")
> 
> [30](https://twitter.com/intent/like?tweet_id=1183594002202935301 "Like")
> [Permalink](https://twitter.com/benrjack/status/1183594002202935301)

> The [~@~streamlit](https://twitter.com/streamlit "https://twitter.com/streamlit")
>  hype is real, this app went from zero to deployed in one night! [~#~python](https://twitter.com/hashtag/python?src=hash "https://twitter.com/hashtag/python?src=hash")
>  [~#~DataScience](https://twitter.com/hashtag/DataScience?src=hash "https://twitter.com/hashtag/DataScience?src=hash")
>  https://nba-roster-turnover.herokuapp.com/
> 
> [![View image on Twitter](https://pbs.twimg.com/media/EHK_mx6WoAArqzL?format=jpg)](https://twitter.com/arvkevi/status/1185220341293047808)
> 
> [35](https://twitter.com/intent/like?tweet_id=1185220341293047808 "Like")
> [Permalink](https://twitter.com/arvkevi/status/1185220341293047808)

> Using [~@~streamlit](https://twitter.com/streamlit "https://twitter.com/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](https://twitter.com/hashtag/DataScience?src=hash "https://twitter.com/hashtag/DataScience?src=hash")
>  use-case. Heck it's even enjoyable! They do right everything Jupyter notebooks got wrong.
> 
> [7](https://twitter.com/intent/like?tweet_id=1188107289309433856 "Like")
> [Permalink](https://twitter.com/a_ghasemi/status/1188107289309433856)

> In building end to end [~#~MachineLearning](https://twitter.com/hashtag/MachineLearning?src=hash "https://twitter.com/hashtag/MachineLearning?src=hash")
>  [~#~webapps](https://twitter.com/hashtag/webapps?src=hash "https://twitter.com/hashtag/webapps?src=hash")
>  my time distribution was:  
> Actual logic and ml part : 20 %  
> Frontend : 80%  
>   
> After [~@~streamlit](https://twitter.com/streamlit "https://twitter.com/streamlit")
>  it has become:  
> Logic and ml part: 100%[~@~streamlit](https://twitter.com/streamlit "https://twitter.com/streamlit")
>  is ![❤️](https://abs.twimg.com/emoji/v2/72x72/2764.png)
> 
> [5](https://twitter.com/intent/like?tweet_id=1390964038050324486 "Like")
> [Permalink](https://twitter.com/AtharvaIngle7/status/1390964038050324486)

> 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
> 
> [1](https://twitter.com/intent/like?tweet_id=1380028715954970625 "Like")
> [Permalink](https://twitter.com/anuj_syal/status/1380028715954970625)

> It took me ~1 hour to build this dashboard (data is dummy) layout in [~@~streamlit](https://twitter.com/streamlit "https://twitter.com/streamlit")
> . Using default Streamlit components. I think it would take 10 times longer with HTML/JS. Now I can focus on functionality ![👍](https://abs.twimg.com/emoji/v2/72x72/1f44d.png), not on div alignment ![🤣](https://abs.twimg.com/emoji/v2/72x72/1f923.png)  
>   
> Code: https://github.com/katanaml/sparrow/tree/main/sparrow-ui
> 
> [![View image on Twitter](https://pbs.twimg.com/media/FeaIE1sXEAAhjUd?format=jpg)](https://twitter.com/andrejusb/status/1578099977036779520)
> 
> [764](https://twitter.com/intent/like?tweet_id=1578099977036779520 "Like")
> [Permalink](https://twitter.com/andrejusb/status/1578099977036779520)

> ![🏆](https://abs.twimg.com/emoji/v2/72x72/1f3c6.png) 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/
> 
> [1](https://twitter.com/intent/like?tweet_id=1575893719462469641 "Like")
> [Permalink](https://twitter.com/pablooomvc1/status/1575893719462469641)

> Just spent this week using [~@~streamlit](https://twitter.com/streamlit "https://twitter.com/streamlit")
>  to build a live animated map ![🗺](https://abs.twimg.com/emoji/v2/72x72/1f5fa.png)  
>   
> I'd never heard of them before this week but very impressed with the speed from idea->data->visualisations ![📊](https://abs.twimg.com/emoji/v2/72x72/1f4ca.png)
> 
> [1](https://twitter.com/intent/like?tweet_id=1575610749434855425 "Like")
> [Permalink](https://twitter.com/hrrsnbbnt/status/1575610749434855425)

> Every new [~@~streamlit](https://twitter.com/streamlit "https://twitter.com/streamlit")
>  release feels like Christmas ![🎁](https://abs.twimg.com/emoji/v2/72x72/1f381.png)![🎅](https://abs.twimg.com/emoji/v2/72x72/1f385.png)![🎄](https://abs.twimg.com/emoji/v2/72x72/1f384.png)![❄](https://abs.twimg.com/emoji/v2/72x72/2744.png)
> 
> [4](https://twitter.com/intent/like?tweet_id=1569595251869761537 "Like")
> [Permalink](https://twitter.com/Lorenz_Web/status/1569595251869761537)

> I just discovered the most beautiful thing ever created.[~@~streamlit](https://twitter.com/streamlit "https://twitter.com/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
> 
> [20](https://twitter.com/intent/like?tweet_id=1469064990237859845 "Like")
> [Permalink](https://twitter.com/jo5h_ofall/status/1469064990237859845)

> Que belleza celestial streamlit y su simplicidad para crear dashboards con Python en 2 segundos
> 
> [7](https://twitter.com/intent/like?tweet_id=1459014368780296194 "Like")
> [Permalink](https://twitter.com/AldoEscobarLVP/status/1459014368780296194)

> Not gonna lie. The hours I spend each week working in [~@~streamlit](https://twitter.com/streamlit "https://twitter.com/streamlit")
>  are my favorites.
> 
> [3](https://twitter.com/intent/like?tweet_id=1456680003198861319 "Like")
> [Permalink](https://twitter.com/jtouellette/status/1456680003198861319)

> 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.
> 
> [6](https://twitter.com/intent/like?tweet_id=1407115419253620743 "Like")
> [Permalink](https://twitter.com/nainia_ayoub/status/1407115419253620743)

Deploy on enterprise
--------------------

Try Streamlit in Snowflake. Code in the browser, collaborate with Git, deploy in one click. With the security and reliability of Snowflake.

[Learn more](https://signup.snowflake.com/?utm_source=streamlit&utm_medium=referral&utm_campaign=rethink&utm_content=-ss-streamlit-io-pagebottom)

---