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A Python app framework built specifically for Machine Learning and Data Science teams
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What is Streamlit?

It is the app framework specifically for Machine Learning and Data Science teams. You can rapidly build the tools you need. Build apps in a dozen lines of Python with a simple API.
Streamlit is a tool in the Machine Learning Tools category of a tech stack.
Streamlit is an open source tool with 8.1K GitHub stars and 723 GitHub forks. Here’s a link to Streamlit's open source repository on GitHub

Who uses Streamlit?


15 developers on StackShare have stated that they use Streamlit.

Streamlit Integrations

Python, TensorFlow, Pandas, Keras, and PyTorch are some of the popular tools that integrate with Streamlit. Here's a list of all 10 tools that integrate with Streamlit.

Why developers like Streamlit?

Here’s a list of reasons why companies and developers use Streamlit
Top Reasons
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Streamlit's Features

  • Free and open source
  • Build apps in a dozen lines of Python with a simple API
  • No callbacks
  • No hidden state
  • Works with TensorFlow, Keras, PyTorch, Pandas, Numpy, Matplotlib, Seaborn, Altair, Plotly, Bokeh, Vega-Lite, and more

Streamlit Alternatives & Comparisons

What are some alternatives to Streamlit?
Dash is an API Documentation Browser and Code Snippet Manager. Dash stores snippets of code and instantly searches offline documentation sets for 150+ APIs. You can even generate your own docsets or request docsets to be included.
The Jupyter Notebook is a web-based interactive computing platform. The notebook combines live code, equations, narrative text, visualizations, interactive dashboards and other media.
Flask is intended for getting started very quickly and was developed with best intentions in mind.
It is an open source R package that provides an elegant and powerful web framework for building web applications using R. It helps you turn your analyses into interactive web applications without requiring HTML, CSS, or JavaScript knowledge.
It is an interactive visualization library that targets modern web browsers for presentation. Its goal is to provide elegant, concise construction of versatile graphics, and to extend this capability with high-performance interactivity over very large or streaming datasets. It can help anyone who would like to quickly and easily create interactive plots, dashboards, and data applications.
See all alternatives

Streamlit's Followers
52 developers follow Streamlit to keep up with related blogs and decisions.
Steven Kolawole
Raghav Dave
Andres Ramirez
Tanner Johnston
Jan Router
meghana gv
Nathalie AKAKPO
Wander Leandro de Carvalho