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Programming in Snowflake

All demo code for my Udemy course Programming in Snowflake Masterclass 2024 Hands-On! - get for the LOWEST-PRICE on the previous link! Refer to individual sections for local documentation.

Programming in Snowflake

Project Setup

(1) Install and configure Visual Studio Code (VSCode).

(2) From VSCode Extensions tab, install the Snowflake Extension.

(3) Clone the current public GitHub repository, then open the newly created programming-in-snowflake/ folder from VSCode:

git clone https://github.com/cristiscu/programming-in-snowflake.git

(4) Install and use a Python version 3.9 for our project (as latest versions are not usually installed in Snowflake).

(5) In a Terminal window from VSCode, create a virtual environment for this Python version. If you have multiple installations of Python on your computer, a path to python.exe may be required. My 3.9 version was installed in the ~\AppData\Local\Programs\Python\Python39\ folder, but yours could be elsewhere:

~\AppData\Local\Programs\Python\Python39\python -m venv venv

(6) A new venv/ folder was created (and already added to .gitignore!). Select the new virtual environment (your prompt should get a "(venv)" prefix):

venv/scripts/activate

(7) Install all Python dependencies for this project with:

pip install -r requirements.txt

(8) Install SnowCD.

(9) Install SnowSQL.

(10) Add in your ~.snowsql\config file your own Snowflake accountname and username, as connection parameters. Mine were:

[connections.my_conn]
accountname = FHB91278
username = cristiscu

(11) Save your Snowflake account password in a SNOWSQL_PWD environment variable (that only you can see and have access to).

(12) For each individual lecture, switch to the related sections/ subfolder, than take one of the following actions, as instructed, depending on that specific use case:

  • Copy and paste SQL file contents into Snowsight SQL Worksheets. Or run the SQL statements directly from this project, if you installed the Snowflake Extension.
  • Execute Streamlit apps as local web applications, with commands like streamlit run app.py (where app.py is your entry point Python file). Terminate the sessions with CTRL+C.
  • Execute single Python files with commands like python app.py (change app.py to your actual Python file name).

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