My First Streamlit app on Snowflake

Last week I followed a Python Essentials course at The School of Data Science in The Hague. At a certain point we discussed Streamlit. This open-source framework could be a potential Power BI killer when it comes to visualising data and interacting with data. Interesting enough to check it out. It became even more interesting when I saw the following announcement the next day; Snowflake to Acquire Streamlit.

Before I will dive into the possibilities of Snowflake and Streamlit, I thought I would try out an easy example. Therefore I followed two examples from Snowflake and Streamlit and combined it to one example.

  1. Getting started with Python – link
  2. Connect Streamlit to Snowflake – link

Setting up

First I had to make sure that I could use Python and Streamlit in combination with Snowflake. I have Anaconda installed on my local machine. Within Anaconda I have made a separate environment to check work this example out. In this environment I installed Streamlit and the Snowflake Connector for Python.

In combination with my Snowflake-account all should be in place to get things going.

Getting Started with Python

Following the Getting started with Python-guide, I’ll make sure I can interact with Snowflake from Python. First I have to validate whether the connection from Python with Snowflake can be made. In the QuickStart you can see that the credentials are visible in the .py-file.

ctx = snowflake.connector.connect( user='<your_user_name>’, password='<your_password>’, account='<your_account_name>’ )

If you do not want that, there is an alternative solution with a separate file for the credentials and a reference to that file in the .py-file. I created a short example.

  1. Credentials
  2. Validate

In the Credentials-file you can register the various components necassary to connect to Snowflake:

  • account (mandatory)
  • user (mandatory)
  • warehouse
  • role
  • database
  • schema
  • password (mandatory)

From within the Validate-file you can reference the Credentials-file. First you specify the location of the the Credentials-file. Then you make sure that the Validate-file can read from the Credentials-file. Then you create several variables (at least, username, password and account) with the information specified in the the Credentials-file.

If you use this setup and you use version control like Git, make sure to put the credentials file in .gitignore.

Creating my first Streamlit App

In Github I uploaded my first Streamlit App. It’s nothing more than a Python-script which consists of a few blocks:

  • Setting up the connection to Snowflake
  • Creating Snowflake-objects
  • Loading Data
  • Doing the Streamlit-magic

Finally running the Python-script; streamlit run <path to Python-file>

Made with Streamlit

The end result of my first Streamlit app is a non-interactive web application. Just to see how easy it is to connect Python and Streamlit to Snowflake. In a following blogpost, I will find out how easy it is to make an interactive web application in Streamlit.

Thanks for reading and till next time.

Daan Bakboord – DaAnalytics

Bekijk ook:

Snowflake’s Data Classification in Snowsight

Snowflake Data Governance directly from Snowsight

Last year I blogged about how to use Snowflake functionality to; “Know your Data”. Especially in these times where Generative AI becomes more and more mainstream, it’s essential to know what data is input for the LLM’s. Now Snowflake has made this a few clicks easier, offering classifying functionalities directly from Snowsight.

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