Why Stored procedures in Python in Snowflake? - Purpose & Use Cases

The Big Idea

What if you could turn repetitive, error-prone database tasks into a single click?

The Scenario

Imagine you have a big spreadsheet where you must update many rows one by one by hand every day.

Each update needs careful steps, and you have to repeat them exactly the same way each time.

The Problem

Doing this by hand is slow and tiring.

You might forget a step or make a typo, causing errors.

It's hard to keep track of what you did and fix mistakes.

The Solution

Stored procedures in Python let you write the update steps once as a small program inside your database.

Then you run it anytime, and it does all the work quickly and correctly.

Before vs After

✗ Before

UPDATE table SET value = value + 1 WHERE id = 1;
UPDATE table SET value = value + 1 WHERE id = 2;

✓ After

CREATE OR REPLACE PROCEDURE update_values()
  RETURNS STRING
  LANGUAGE PYTHON
  RUNTIME_VERSION = '3.12'
  HANDLER = 'run'
  AS $$
  def run(session):
    for i in range(1, 3):
      session.sql(f"UPDATE table SET value = value + 1 WHERE id = {i}").collect()
    return 'Done'
  $$;

What It Enables

You can automate complex database tasks safely and run them anytime with one command.

Real Life Example

A company updates sales data daily from many stores; using stored procedures in Python, they automate these updates without errors or delays.

Key Takeaways

Manual updates are slow and error-prone.

Stored procedures in Python automate and speed up database tasks.

This makes data management reliable and easy to repeat.