credit-scoring-with-snowpark

Credit Scoring with Snowpark & LocalStack

This notebook demonstrates how to use Snowpark for Python to perform exploratory data analysis (EDA) on a credit scoring dataset. This notebook uses LocalStack's Snowflake emulator to run Snowflake data pipelines locally.

Prerequisites

• A valid LocalStack for Snowflake license. Your license provides a LOCALSTACK_AUTH_TOKEN.
• localstack CLI with LOCALSTACK_AUTH_TOKEN environment variable set
• LocalStack Snowflake emulator
• Snowpark for Python
• Jupyter Notebook

Start LocalStack

export LOCALSTACK_AUTH_TOKEN=<your-auth-token>
localstack auth set-token $LOCALSTACK_AUTH_TOKEN
localstack start -s snowflake -d
localstack wait -t 30

Running the notebook

Start the LocalStack container using your preferred method. Ensure that you have access to LocalStack's Snowflake emulator. Start a Jupyter Notebook server and open the notebook in your browser.

jupyter notebook

Open the credit-scoring-eda.ipynb notebook and run the cells to see the results. Follow the instructions in the notebook to install the required packages and set up the Snowflake emulator.

License

This code is available under the Apache 2.0 license.