Streamlit

Streamlit

Streamlit is an open-source Python library for building web apps and dashboards quickly and easily. It allows you to create interactive data apps in Python without needing to know any JavaScript or HTML.
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python web-app dashboard

Streamlit: Build Web Apps & Dashboards Quickly

Streamlit is an open-source Python library for building web apps and dashboards quickly and easily. It allows you to create interactive data apps in Python without needing to know any JavaScript or HTML.

What is Streamlit?

Streamlit is an open-source Python library that makes it easy to create beautiful, customizable web apps and dashboards in Python. With Streamlit, you can quickly build interactive apps to share data analyses, models, and more without needing to know any JavaScript or HTML.

Some key features of Streamlit:

  • Turns Python scripts into web apps with a few lines of code. No need to deal with JavaScript or front-end frameworks.
  • Makes it simple to create custom layouts, media elements, widgets, graphs/charts, etc. Streamlit handles the front-end for you.
  • Interactive widgets allow viewers to adjust parameters and see results update live.
  • Works with all major Python data science libraries like pandas, NumPy, Matplotlib, scikit-learn, etc.
  • Includes easy publishing and sharing options to send apps to colleagues or deploy online.
  • Offers extensive custom theming capabilities to brand your web apps.
  • Active open-source community behind continued development and improvements.

In summary, Streamlit dramatically lowers the barrier for data scientists and ML engineers to translate their work into web apps and share results with non-technical audiences.

Streamlit Features

Features

  1. Quickly create web apps and dashboards in Python
  2. Interactive widgets for user input
  3. Support for major Python data science libraries
  4. Real-time updates as code changes
  5. Open-source and free

Pricing

  • Open Source

Pros

Very fast and easy to build apps

No need to know frontend web dev

Great for data science workflows

Active community support

Cons

Limited customization compared to full web frameworks

Hosting and deployment requires setup

Less flexibility than JavaScript-based tools


The Best Streamlit Alternatives

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