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This app shows a double-blind join in Snowflake using Streamilt. Note that:
- Streamlit enables rich, non-trivial interactions such as generating synthetic data from scratch.
- This entire app required less than 200 lines of code!
This is the magic of Streamlit! Such interactions cannot be implemented in Retool or Tableau without torturing the underlying abstractions. By contrast, Streamlit presents an incredibly flexible language for expressing rich data apps in the ML age.
This is why Streamlit is actively deployed over half the Fortune 50!
- Check out streamlit.io
- Jump into our documentation
- Ask a question in our community forums
- Use a neural net to [analyze the Udacity Self-driving Car Image Dataset] (https://github.com/streamlit/demo-self-driving)
- Explore a [New York City rideshare dataset] (https://github.com/streamlit/demo-uber-nyc-pickups)