Streamlit in Snowflake: Limitations, Best Practices, and Troubleshooting Guide

 

Introduction: Streamlit is a powerful tool for creating interactive data applications, but when using it in conjunction with Snowflake, certain limitations and considerations come into play. In this comprehensive guide, we'll explore the limitations and unsupported features of Streamlit in Snowflake, along with best practices to optimize your Streamlit apps for this environment. Additionally, we'll provide troubleshooting tips to address common issues that may arise during development.

Account Limitations and Unsupported Regions: Before diving into Streamlit development in Snowflake, it's crucial to understand account limitations. Streamlit in Snowflake is currently only available to accounts in AWS and Microsoft Azure commercial regions. Unfortunately, AWS PrivateLink and Azure Private Link are not supported at this time.

Data Retrieval Limits and Best Practices: Streamlit apps in Snowflake have a 32MB limit on data retrieval per query. To avoid exceeding this limit, it's essential to design your apps to retrieve data in smaller increments. Additionally, be aware that the Streamlit editor does not support stages with server-side encryption, which may impact your data retrieval process.

Multi-Page Apps and Snowflake Context Functions: While multi-page Streamlit apps are supported in Snowflake, there are some considerations to keep in mind. These apps can only be created using SQL commands, and individual page URLs are not supported. Furthermore, certain Snowflake context functions may return empty fields or NONE when used in Streamlit apps, requiring alternative approaches for personalization and data filtering.

Unsupported Features and Troubleshooting Tips: Several Streamlit features are not supported in Snowflake, including file uploaders, caching functionalities, custom components, and network access via the internet. If you encounter issues with your Streamlit app, troubleshooting steps such as checking domain allowlists, verifying WebSocket connections, and ensuring proper database privileges may help resolve them.

Conclusion: While Streamlit offers a seamless way to create interactive data applications, its integration with Snowflake comes with its own set of limitations and considerations. By understanding these constraints and following best practices, you can effectively leverage Streamlit in Snowflake to build robust and efficient data-driven applications for your organization's needs.