https://github.com/streamlit/snowflake-double-blind-demo
An example Streamlit app that demonstrates using Snowflake to join two datasets that use obfuscated IDs for data security
https://github.com/streamlit/snowflake-double-blind-demo
Last synced: 8 months ago
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An example Streamlit app that demonstrates using Snowflake to join two datasets that use obfuscated IDs for data security
- Host: GitHub
- URL: https://github.com/streamlit/snowflake-double-blind-demo
- Owner: streamlit
- Created: 2021-09-17T14:41:00.000Z (almost 5 years ago)
- Default Branch: master
- Last Pushed: 2024-03-20T16:19:49.000Z (over 2 years ago)
- Last Synced: 2025-01-29T10:36:26.866Z (over 1 year ago)
- Language: Python
- Size: 3.01 MB
- Stars: 4
- Watchers: 4
- Forks: 8
- Open Issues: 2
-
Metadata Files:
- Readme: README.md
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README
# Snowflake Double-blind Hash Demo
---
**👈 Select a mode from the dropdown on the left** to get started!
---
## 🐟 Summary
**This app shows a double-blind join in Snowflake using Streamilt.**
Note that:
1. Streamlit enables **rich, non-trivial interactions** such as generating synthetic
data from scratch.
2. [This entire
app](https://github.com/streamlit/snowflake-double-blind-demo/blob/master/streamlit_app.py)
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!
## 🐬 More information
- Check out [streamlit.io](https://streamlit.io)
- Jump into our [documentation](https://docs.streamlit.io)
- Ask a question in our [community forums](https://discuss.streamlit.io)
## 🦑 See more complex demos
- 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)